Practice Management

From Medically Home Group, Boston, MA.

Brick-and-mortar hospitals in the United States have historically been considered the dominant setting for providing care to patients. The coordination and delivery of care has previously been bound to physical hospitals largely because multidisciplinary services were only accessible in an individual location. While the fundamental make-up of these services remains unchanged, these services are now available in alternate settings. Some of these services include access to a patient care team, supplies, diagnostics, pharmacy, and advanced therapeutic interventions. Presently, the physical environment is becoming increasingly irrelevant as the core of what makes the traditional hospital—the professional staff, collaborative work processes, and the dynamics of the space—have all been translated into a modern digitally integrated environment. The elements necessary to providing safe, effective care in a physical hospital setting are now available in a patient’s home.

Impetus for the Model

As hospitals reconsider how and where they deliver patient care because of limited resources, the hospital-at-home model has gained significant momentum and interest. This model transforms a home into a hospital. The inpatient acute care episode is entirely substituted with an intensive at-home hospital admission enabled by technology, multidisciplinary teams, and ancillary services. Furthermore, patients requiring post-acute support can be transitioned to their next phase of care seamlessly. Given the nationwide nursing shortage, aging population, challenges uncovered by the COVID-19 pandemic, rising hospital costs, nurse/provider burnout related to challenging work environments, and capacity constraints, a shift toward the combination of virtual and in-home care is imperative. The hospital-at-home model has been associated with superior patient outcomes, including reduced risks of delirium, improved functional status, improved patient and family member satisfaction, reduced mortality, reduced readmissions, and significantly lower costs.¹ COVID-19 alone has unmasked major facility-based deficiencies and limitations of our health care system. While the pandemic is not the impetus for the hospital-at-home model, the extended stress of this event has created a unique opportunity to reimagine and transform our health care delivery system so that it is less fragmented and more flexible.

Nursing in the Model

Nursing is central to the hospital-at-home model. Virtual nurses provide meticulous care plan oversight, assessment, and documentation across in-home service providers, to ensure holistic, safe, transparent, and continuous progression toward care plan milestones. The virtual nurse monitors patients using in-home technology that is set up at the time of admission. Connecting with patients to verify social and medical needs, the virtual nurse advocates for their patients and uses these technologies to care and deploy on-demand hands-on services to the patient. Service providers such as paramedics, infusion nurses, or home health nurses may be deployed to provide services in the patient’s home. By bringing in supplies, therapeutics, and interdisciplinary team members, the capabilities of a brick-and-mortar hospital are replicated in the home. All actions that occur wherever the patient is receiving care are overseen by professional nursing staff; in short, virtual nurses are the equivalent of bedside nurses in the brick-and-mortar health care facilities.

Potential Benefits

There are many benefits to the hospital-at-home model (Table). This health care model can be particularly helpful for patients who require frequent admission to acute care facilities, and is well suited for patients with a range of conditions, including those with COVID-19, pneumonia, cellulitis, or congestive heart failure. This care model helps eliminate some of the stressors for patients who have chronic illnesses or other conditions that require frequent hospital admissions. Patients can independently recover at home and can also be surrounded by their loved ones and pets while recovering. This care approach additionally eliminates the risk of hospital-acquired infections and injuries. The hospital-at-home model allows for increased mobility,² as patients are familiar with their surroundings, resulting in reduced onset of delirium. Additionally, patients with improved mobility performance are less likely to experience negative health outcomes.³ There is less chance of sleep disruption as the patient is sleeping in their own bed—no unfamiliar roommate, no call bells or health care personnel frequently coming into the room. The in-home technology set up for remote patient monitoring is designed with the user in mind. Ease of use empowers the patient to collaborate with their care team on their own terms and center the priorities of themselves and their families.

Positive Outcomes

The hospital-at-home model is associated with positive outcomes. The authors of a systematic review identified 10 randomized controlled trials of hospital-at-home programs (with a total of 1372 patients), but were able to obtain data for only 5 of these trials (with a total of 844 patients).⁴ They found a 38% reduction in 6-month mortality for patients who received hospital care at home, as well as significantly higher patient satisfaction across a range of medical conditions, including patients with cellulitis and community-acquired pneumonia, as well as elderly patients with multiple medical conditions. The authors concluded that hospital care at home was less expensive than admission to an acute care hospital.⁴ Similarly, a meta-analysis done by Caplan et al⁵ that included 61 randomized controlled trials concluded that hospital at home is associated with reductions in mortality, readmission rates, and cost, and increases in patient and caregiver satisfaction. Levine et al² found reduced costs and utilization with home hospitalization compared to in-hospital care, as well as improved patient mobility status.

The home is the ideal place to empower patients and caregivers to engage in self-management.² Receiving hospital care at home eliminates the need for dealing with transportation arrangements, traffic, road tolls, and time/scheduling constraints, or finding care for a dependent family member, some of the many stressors that may be experienced by patients who require frequent trips to the hospital. For patients who may not be clinically suitable candidates for hospital at home, such as those requiring critical care intervention and support, the brick-and-mortar hospital is still the appropriate site of care. The hospital-at-home model helps prevent bed shortages in brick-and-mortar hospital settings by allowing hospital care at home for patients who meet preset criteria. These patients can be hospitalized in alternative locations such as their own homes or the residence of a friend. This helps increase health system capacity as well as resiliency.

In addition to expanding safe and appropriate treatment spaces, the hospital-at-home model helps increase access to care for patients during nonstandard hours, including weekends, holidays, or when the waiting time in the emergency room is painfully long. Furthermore, providing care in the home gives the clinical team valuable insight into the patient’s daily life and routine. Performing medication reconciliation with the medicine cabinet in sight and dietary education in a patient’s kitchen are powerful touch points.² For example, a patient with congestive heart failure who must undergo diuresis is much more likely to meet their care goals when their home diet is aligned with the treatment goal. By being able to see exactly what is in a patient’s pantry and fridge, the care team can create a much more tailored approach to sodium intake and fluid management. Providers can create and execute true patient-centric care as they gain direct insight into the patient’s lifestyle, which is clearly valuable when creating care plans for complex chronic health issues.

Although there are clear benefits to hospital at home, how to best implement and scale this model presents a challenge. In addition to educating patients and families about this model of care, health care systems must expand their hospital-at-home programs and provide education about this model to clinical staff and trainees, and insurers must create reimbursement paradigms. Patients meeting eligibility criteria to enroll in hospital at home is the easiest hurdle, as hospital-at-home programs function best when they enroll and service as many patients as possible, including underserved populations.

Upfront Costs and Cost Savings

While there are upfront costs to set up technology and coordinate services, hospital at home also provides significant total cost savings when compared to coordination associated with brick-and-mortar admission. Hospital care accounts for about one-third of total medical expenditures and is a leading cause of debt.² Eliminating fixed hospital costs such as facility, overhead, and equipment costs through adoption of the hospital-at-home model can lead to a reduction in expenditures. It has been found that fewer laboratory and diagnostic tests are ordered for hospital-at-home patients when compared to similar patients in brick-and-mortar hospital settings, with comparable or better clinical patient outcomes.⁶ Furthermore, it is estimated that there are cost savings of 19% to 30% when compared to traditional inpatient care.⁶ Without legislative action, upon the end of the current COVID-19 public health emergency, the Centers for Medicare & Medicaid Service’s Acute Hospital Care at Home waiver will terminate. This could slow down scaling of the model.However, over the past 2 years there has been enough buy-in from major health systems and patients to continue the momentum of the model’s growth. When setting up a hospital-at-home program, it would be wise to consider a few factors: where in the hospital or health system entity structure the hospital-at-home program will reside, which existing resources can be leveraged within the hospital or health system, and what are the state or federal regulatory requirements for such a program. This type of program continues to fill gaps within the US health care system, meeting the needs of widely overlooked populations and increasing access to essential ancillary services.

Conclusion

It is time to consider our bias toward hospital-first options when managing the care needs of our patients. Health care providers have the option to advocate for holistic care, better experience, and better outcomes. Home-based options are safe, equitable, and patient-centric. Increased costs, consumerism, and technology have pushed us to think about alternative approaches to patient care delivery, and the pandemic created a unique opportunity to see just how far the health care system could stretch itself with capacity constraints, insufficient resources, and staff shortages. In light of new possibilities, it is time to reimagine and transform our health care delivery system so that it is unified, seamless, cohesive, and flexible.

Corresponding author: Payal Sharma, DNP, MSN, RN, FNP-BC, CBN; [email protected].

Disclosures: None reported.

From Medically Home Group, Boston, MA.

Brick-and-mortar hospitals in the United States have historically been considered the dominant setting for providing care to patients. The coordination and delivery of care has previously been bound to physical hospitals largely because multidisciplinary services were only accessible in an individual location. While the fundamental make-up of these services remains unchanged, these services are now available in alternate settings. Some of these services include access to a patient care team, supplies, diagnostics, pharmacy, and advanced therapeutic interventions. Presently, the physical environment is becoming increasingly irrelevant as the core of what makes the traditional hospital—the professional staff, collaborative work processes, and the dynamics of the space—have all been translated into a modern digitally integrated environment. The elements necessary to providing safe, effective care in a physical hospital setting are now available in a patient’s home.

Impetus for the Model

As hospitals reconsider how and where they deliver patient care because of limited resources, the hospital-at-home model has gained significant momentum and interest. This model transforms a home into a hospital. The inpatient acute care episode is entirely substituted with an intensive at-home hospital admission enabled by technology, multidisciplinary teams, and ancillary services. Furthermore, patients requiring post-acute support can be transitioned to their next phase of care seamlessly. Given the nationwide nursing shortage, aging population, challenges uncovered by the COVID-19 pandemic, rising hospital costs, nurse/provider burnout related to challenging work environments, and capacity constraints, a shift toward the combination of virtual and in-home care is imperative. The hospital-at-home model has been associated with superior patient outcomes, including reduced risks of delirium, improved functional status, improved patient and family member satisfaction, reduced mortality, reduced readmissions, and significantly lower costs.¹ COVID-19 alone has unmasked major facility-based deficiencies and limitations of our health care system. While the pandemic is not the impetus for the hospital-at-home model, the extended stress of this event has created a unique opportunity to reimagine and transform our health care delivery system so that it is less fragmented and more flexible.

Nursing in the Model

Nursing is central to the hospital-at-home model. Virtual nurses provide meticulous care plan oversight, assessment, and documentation across in-home service providers, to ensure holistic, safe, transparent, and continuous progression toward care plan milestones. The virtual nurse monitors patients using in-home technology that is set up at the time of admission. Connecting with patients to verify social and medical needs, the virtual nurse advocates for their patients and uses these technologies to care and deploy on-demand hands-on services to the patient. Service providers such as paramedics, infusion nurses, or home health nurses may be deployed to provide services in the patient’s home. By bringing in supplies, therapeutics, and interdisciplinary team members, the capabilities of a brick-and-mortar hospital are replicated in the home. All actions that occur wherever the patient is receiving care are overseen by professional nursing staff; in short, virtual nurses are the equivalent of bedside nurses in the brick-and-mortar health care facilities.

Potential Benefits

There are many benefits to the hospital-at-home model (Table). This health care model can be particularly helpful for patients who require frequent admission to acute care facilities, and is well suited for patients with a range of conditions, including those with COVID-19, pneumonia, cellulitis, or congestive heart failure. This care model helps eliminate some of the stressors for patients who have chronic illnesses or other conditions that require frequent hospital admissions. Patients can independently recover at home and can also be surrounded by their loved ones and pets while recovering. This care approach additionally eliminates the risk of hospital-acquired infections and injuries. The hospital-at-home model allows for increased mobility,² as patients are familiar with their surroundings, resulting in reduced onset of delirium. Additionally, patients with improved mobility performance are less likely to experience negative health outcomes.³ There is less chance of sleep disruption as the patient is sleeping in their own bed—no unfamiliar roommate, no call bells or health care personnel frequently coming into the room. The in-home technology set up for remote patient monitoring is designed with the user in mind. Ease of use empowers the patient to collaborate with their care team on their own terms and center the priorities of themselves and their families.

Positive Outcomes

The hospital-at-home model is associated with positive outcomes. The authors of a systematic review identified 10 randomized controlled trials of hospital-at-home programs (with a total of 1372 patients), but were able to obtain data for only 5 of these trials (with a total of 844 patients).⁴ They found a 38% reduction in 6-month mortality for patients who received hospital care at home, as well as significantly higher patient satisfaction across a range of medical conditions, including patients with cellulitis and community-acquired pneumonia, as well as elderly patients with multiple medical conditions. The authors concluded that hospital care at home was less expensive than admission to an acute care hospital.⁴ Similarly, a meta-analysis done by Caplan et al⁵ that included 61 randomized controlled trials concluded that hospital at home is associated with reductions in mortality, readmission rates, and cost, and increases in patient and caregiver satisfaction. Levine et al² found reduced costs and utilization with home hospitalization compared to in-hospital care, as well as improved patient mobility status.

The home is the ideal place to empower patients and caregivers to engage in self-management.² Receiving hospital care at home eliminates the need for dealing with transportation arrangements, traffic, road tolls, and time/scheduling constraints, or finding care for a dependent family member, some of the many stressors that may be experienced by patients who require frequent trips to the hospital. For patients who may not be clinically suitable candidates for hospital at home, such as those requiring critical care intervention and support, the brick-and-mortar hospital is still the appropriate site of care. The hospital-at-home model helps prevent bed shortages in brick-and-mortar hospital settings by allowing hospital care at home for patients who meet preset criteria. These patients can be hospitalized in alternative locations such as their own homes or the residence of a friend. This helps increase health system capacity as well as resiliency.

In addition to expanding safe and appropriate treatment spaces, the hospital-at-home model helps increase access to care for patients during nonstandard hours, including weekends, holidays, or when the waiting time in the emergency room is painfully long. Furthermore, providing care in the home gives the clinical team valuable insight into the patient’s daily life and routine. Performing medication reconciliation with the medicine cabinet in sight and dietary education in a patient’s kitchen are powerful touch points.² For example, a patient with congestive heart failure who must undergo diuresis is much more likely to meet their care goals when their home diet is aligned with the treatment goal. By being able to see exactly what is in a patient’s pantry and fridge, the care team can create a much more tailored approach to sodium intake and fluid management. Providers can create and execute true patient-centric care as they gain direct insight into the patient’s lifestyle, which is clearly valuable when creating care plans for complex chronic health issues.

Although there are clear benefits to hospital at home, how to best implement and scale this model presents a challenge. In addition to educating patients and families about this model of care, health care systems must expand their hospital-at-home programs and provide education about this model to clinical staff and trainees, and insurers must create reimbursement paradigms. Patients meeting eligibility criteria to enroll in hospital at home is the easiest hurdle, as hospital-at-home programs function best when they enroll and service as many patients as possible, including underserved populations.

Upfront Costs and Cost Savings

While there are upfront costs to set up technology and coordinate services, hospital at home also provides significant total cost savings when compared to coordination associated with brick-and-mortar admission. Hospital care accounts for about one-third of total medical expenditures and is a leading cause of debt.² Eliminating fixed hospital costs such as facility, overhead, and equipment costs through adoption of the hospital-at-home model can lead to a reduction in expenditures. It has been found that fewer laboratory and diagnostic tests are ordered for hospital-at-home patients when compared to similar patients in brick-and-mortar hospital settings, with comparable or better clinical patient outcomes.⁶ Furthermore, it is estimated that there are cost savings of 19% to 30% when compared to traditional inpatient care.⁶ Without legislative action, upon the end of the current COVID-19 public health emergency, the Centers for Medicare & Medicaid Service’s Acute Hospital Care at Home waiver will terminate. This could slow down scaling of the model.However, over the past 2 years there has been enough buy-in from major health systems and patients to continue the momentum of the model’s growth. When setting up a hospital-at-home program, it would be wise to consider a few factors: where in the hospital or health system entity structure the hospital-at-home program will reside, which existing resources can be leveraged within the hospital or health system, and what are the state or federal regulatory requirements for such a program. This type of program continues to fill gaps within the US health care system, meeting the needs of widely overlooked populations and increasing access to essential ancillary services.

Conclusion

It is time to consider our bias toward hospital-first options when managing the care needs of our patients. Health care providers have the option to advocate for holistic care, better experience, and better outcomes. Home-based options are safe, equitable, and patient-centric. Increased costs, consumerism, and technology have pushed us to think about alternative approaches to patient care delivery, and the pandemic created a unique opportunity to see just how far the health care system could stretch itself with capacity constraints, insufficient resources, and staff shortages. In light of new possibilities, it is time to reimagine and transform our health care delivery system so that it is unified, seamless, cohesive, and flexible.

Corresponding author: Payal Sharma, DNP, MSN, RN, FNP-BC, CBN; [email protected].

Disclosures: None reported.

From Medically Home Group, Boston, MA.

Brick-and-mortar hospitals in the United States have historically been considered the dominant setting for providing care to patients. The coordination and delivery of care has previously been bound to physical hospitals largely because multidisciplinary services were only accessible in an individual location. While the fundamental make-up of these services remains unchanged, these services are now available in alternate settings. Some of these services include access to a patient care team, supplies, diagnostics, pharmacy, and advanced therapeutic interventions. Presently, the physical environment is becoming increasingly irrelevant as the core of what makes the traditional hospital—the professional staff, collaborative work processes, and the dynamics of the space—have all been translated into a modern digitally integrated environment. The elements necessary to providing safe, effective care in a physical hospital setting are now available in a patient’s home.

Impetus for the Model

As hospitals reconsider how and where they deliver patient care because of limited resources, the hospital-at-home model has gained significant momentum and interest. This model transforms a home into a hospital. The inpatient acute care episode is entirely substituted with an intensive at-home hospital admission enabled by technology, multidisciplinary teams, and ancillary services. Furthermore, patients requiring post-acute support can be transitioned to their next phase of care seamlessly. Given the nationwide nursing shortage, aging population, challenges uncovered by the COVID-19 pandemic, rising hospital costs, nurse/provider burnout related to challenging work environments, and capacity constraints, a shift toward the combination of virtual and in-home care is imperative. The hospital-at-home model has been associated with superior patient outcomes, including reduced risks of delirium, improved functional status, improved patient and family member satisfaction, reduced mortality, reduced readmissions, and significantly lower costs.¹ COVID-19 alone has unmasked major facility-based deficiencies and limitations of our health care system. While the pandemic is not the impetus for the hospital-at-home model, the extended stress of this event has created a unique opportunity to reimagine and transform our health care delivery system so that it is less fragmented and more flexible.

Nursing in the Model

Nursing is central to the hospital-at-home model. Virtual nurses provide meticulous care plan oversight, assessment, and documentation across in-home service providers, to ensure holistic, safe, transparent, and continuous progression toward care plan milestones. The virtual nurse monitors patients using in-home technology that is set up at the time of admission. Connecting with patients to verify social and medical needs, the virtual nurse advocates for their patients and uses these technologies to care and deploy on-demand hands-on services to the patient. Service providers such as paramedics, infusion nurses, or home health nurses may be deployed to provide services in the patient’s home. By bringing in supplies, therapeutics, and interdisciplinary team members, the capabilities of a brick-and-mortar hospital are replicated in the home. All actions that occur wherever the patient is receiving care are overseen by professional nursing staff; in short, virtual nurses are the equivalent of bedside nurses in the brick-and-mortar health care facilities.

Potential Benefits

There are many benefits to the hospital-at-home model (Table). This health care model can be particularly helpful for patients who require frequent admission to acute care facilities, and is well suited for patients with a range of conditions, including those with COVID-19, pneumonia, cellulitis, or congestive heart failure. This care model helps eliminate some of the stressors for patients who have chronic illnesses or other conditions that require frequent hospital admissions. Patients can independently recover at home and can also be surrounded by their loved ones and pets while recovering. This care approach additionally eliminates the risk of hospital-acquired infections and injuries. The hospital-at-home model allows for increased mobility,² as patients are familiar with their surroundings, resulting in reduced onset of delirium. Additionally, patients with improved mobility performance are less likely to experience negative health outcomes.³ There is less chance of sleep disruption as the patient is sleeping in their own bed—no unfamiliar roommate, no call bells or health care personnel frequently coming into the room. The in-home technology set up for remote patient monitoring is designed with the user in mind. Ease of use empowers the patient to collaborate with their care team on their own terms and center the priorities of themselves and their families.

Positive Outcomes

The hospital-at-home model is associated with positive outcomes. The authors of a systematic review identified 10 randomized controlled trials of hospital-at-home programs (with a total of 1372 patients), but were able to obtain data for only 5 of these trials (with a total of 844 patients).⁴ They found a 38% reduction in 6-month mortality for patients who received hospital care at home, as well as significantly higher patient satisfaction across a range of medical conditions, including patients with cellulitis and community-acquired pneumonia, as well as elderly patients with multiple medical conditions. The authors concluded that hospital care at home was less expensive than admission to an acute care hospital.⁴ Similarly, a meta-analysis done by Caplan et al⁵ that included 61 randomized controlled trials concluded that hospital at home is associated with reductions in mortality, readmission rates, and cost, and increases in patient and caregiver satisfaction. Levine et al² found reduced costs and utilization with home hospitalization compared to in-hospital care, as well as improved patient mobility status.

The home is the ideal place to empower patients and caregivers to engage in self-management.² Receiving hospital care at home eliminates the need for dealing with transportation arrangements, traffic, road tolls, and time/scheduling constraints, or finding care for a dependent family member, some of the many stressors that may be experienced by patients who require frequent trips to the hospital. For patients who may not be clinically suitable candidates for hospital at home, such as those requiring critical care intervention and support, the brick-and-mortar hospital is still the appropriate site of care. The hospital-at-home model helps prevent bed shortages in brick-and-mortar hospital settings by allowing hospital care at home for patients who meet preset criteria. These patients can be hospitalized in alternative locations such as their own homes or the residence of a friend. This helps increase health system capacity as well as resiliency.

In addition to expanding safe and appropriate treatment spaces, the hospital-at-home model helps increase access to care for patients during nonstandard hours, including weekends, holidays, or when the waiting time in the emergency room is painfully long. Furthermore, providing care in the home gives the clinical team valuable insight into the patient’s daily life and routine. Performing medication reconciliation with the medicine cabinet in sight and dietary education in a patient’s kitchen are powerful touch points.² For example, a patient with congestive heart failure who must undergo diuresis is much more likely to meet their care goals when their home diet is aligned with the treatment goal. By being able to see exactly what is in a patient’s pantry and fridge, the care team can create a much more tailored approach to sodium intake and fluid management. Providers can create and execute true patient-centric care as they gain direct insight into the patient’s lifestyle, which is clearly valuable when creating care plans for complex chronic health issues.

Although there are clear benefits to hospital at home, how to best implement and scale this model presents a challenge. In addition to educating patients and families about this model of care, health care systems must expand their hospital-at-home programs and provide education about this model to clinical staff and trainees, and insurers must create reimbursement paradigms. Patients meeting eligibility criteria to enroll in hospital at home is the easiest hurdle, as hospital-at-home programs function best when they enroll and service as many patients as possible, including underserved populations.

Upfront Costs and Cost Savings

While there are upfront costs to set up technology and coordinate services, hospital at home also provides significant total cost savings when compared to coordination associated with brick-and-mortar admission. Hospital care accounts for about one-third of total medical expenditures and is a leading cause of debt.² Eliminating fixed hospital costs such as facility, overhead, and equipment costs through adoption of the hospital-at-home model can lead to a reduction in expenditures. It has been found that fewer laboratory and diagnostic tests are ordered for hospital-at-home patients when compared to similar patients in brick-and-mortar hospital settings, with comparable or better clinical patient outcomes.⁶ Furthermore, it is estimated that there are cost savings of 19% to 30% when compared to traditional inpatient care.⁶ Without legislative action, upon the end of the current COVID-19 public health emergency, the Centers for Medicare & Medicaid Service’s Acute Hospital Care at Home waiver will terminate. This could slow down scaling of the model.However, over the past 2 years there has been enough buy-in from major health systems and patients to continue the momentum of the model’s growth. When setting up a hospital-at-home program, it would be wise to consider a few factors: where in the hospital or health system entity structure the hospital-at-home program will reside, which existing resources can be leveraged within the hospital or health system, and what are the state or federal regulatory requirements for such a program. This type of program continues to fill gaps within the US health care system, meeting the needs of widely overlooked populations and increasing access to essential ancillary services.

Conclusion

It is time to consider our bias toward hospital-first options when managing the care needs of our patients. Health care providers have the option to advocate for holistic care, better experience, and better outcomes. Home-based options are safe, equitable, and patient-centric. Increased costs, consumerism, and technology have pushed us to think about alternative approaches to patient care delivery, and the pandemic created a unique opportunity to see just how far the health care system could stretch itself with capacity constraints, insufficient resources, and staff shortages. In light of new possibilities, it is time to reimagine and transform our health care delivery system so that it is unified, seamless, cohesive, and flexible.

Corresponding author: Payal Sharma, DNP, MSN, RN, FNP-BC, CBN; [email protected].

Disclosures: None reported.

The Institute of Medicine brought much-needed attention to the need for process improvement in medicine with its seminal report To Err Is Human: Building a Safer Health System, which was issued in 1999, leading to the quality movement’s call to close health care performance gaps in Crossing the Quality Chasm: A New Health System for the 21st Century.^1,2 Quality improvement science in medicine has evolved over the past 2 decades to include a broad spectrum of approaches, from agile improvement to continuous learning and improvement. Current efforts focus on Lean-based process improvement along with a reduction in variation in clinical practice to align practice with the principles of evidence-based medicine in a patient-centered approach.³ Further, the definition of quality improvement under the Affordable Care Act was framed as an equitable, timely, value-based, patient-centered approach to achieving population-level health goals.⁴ Thus, the science of quality improvement drives the core principles of care delivery improvement, and the rigorous evidence needed to expand innovation is embedded within the same framework.^5,6 In clinical practice, quality improvement projects aim to define gaps and then specific steps are undertaken to improve the evidence-based practice of a specific process. The overarching goal is to enhance the efficacy of the practice by reducing waste within a particular domain. Thus, quality improvement and implementation research eventually unify how clinical practice is advanced concurrently to bridge identified gaps.⁷

System redesign through a patient-centered framework forms the core of an overarching strategy to support system-level processes. Both require a deep understanding of the fields of quality improvement science and implementation science.⁸ Furthermore, aligning clinical research needs, system aims, patients’ values, and clinical care give the new design a clear path forward. Patient-centered improvement includes the essential elements of system redesign around human factors, including communication, physical resources, and updated information during episodes of care. The patient-centered improvement design is juxtaposed with care planning and establishing continuum of care processes.⁹ It is essential to note that safety is rooted within the quality domain as a top priority in medicine.¹⁰ The best implementation methods and approaches are discussed and debated, and the improvement progress continues on multiple fronts.¹¹ Patient safety systems are implemented simultaneously during the redesign phase. Moreover, identifying and testing the health care delivery methods in the era of competing strategic priorities to achieve the desirable clinical outcomes highlights the importance of implementation, while contemplating the methods of dissemination, scalability, and sustainability of the best evidence-based clinical practice.

The cycle of quality improvement research completes the system implementation efforts. The conceptual framework of quality improvement includes multiple areas of care and transition, along with applying the best clinical practices in a culture that emphasizes continuous improvement and learning. At the same time, the operating principles should include continuous improvement in a simple and continuous system of learning as a core concept. Our proposed implementation approach involves taking simple and practical steps while separating the process from the outcomes measures, extracting effectiveness throughout the process. It is essential to keep in mind that building a proactive and systematic improvement environment requires a framework for safety, reliability, and effective care, as well as the alignment of the physical system, communication, and professional environment and culture (Figure).

In summary, system design for quality improvement research should incorporate the principles and conceptual framework that embody effective implementation strategies, with a focus on operational and practical steps. Continuous improvement will be reached through the multidimensional development of current health care system metrics and the incorporation of implementation science methods.

Corresponding author: Ebrahim Barkoudah, MD, MPH, Department of Medicine, Brigham and Women’s Hospital, Boston, MA; [email protected]

Disclosures: None reported.

The Institute of Medicine brought much-needed attention to the need for process improvement in medicine with its seminal report To Err Is Human: Building a Safer Health System, which was issued in 1999, leading to the quality movement’s call to close health care performance gaps in Crossing the Quality Chasm: A New Health System for the 21st Century.^1,2 Quality improvement science in medicine has evolved over the past 2 decades to include a broad spectrum of approaches, from agile improvement to continuous learning and improvement. Current efforts focus on Lean-based process improvement along with a reduction in variation in clinical practice to align practice with the principles of evidence-based medicine in a patient-centered approach.³ Further, the definition of quality improvement under the Affordable Care Act was framed as an equitable, timely, value-based, patient-centered approach to achieving population-level health goals.⁴ Thus, the science of quality improvement drives the core principles of care delivery improvement, and the rigorous evidence needed to expand innovation is embedded within the same framework.^5,6 In clinical practice, quality improvement projects aim to define gaps and then specific steps are undertaken to improve the evidence-based practice of a specific process. The overarching goal is to enhance the efficacy of the practice by reducing waste within a particular domain. Thus, quality improvement and implementation research eventually unify how clinical practice is advanced concurrently to bridge identified gaps.⁷

System redesign through a patient-centered framework forms the core of an overarching strategy to support system-level processes. Both require a deep understanding of the fields of quality improvement science and implementation science.⁸ Furthermore, aligning clinical research needs, system aims, patients’ values, and clinical care give the new design a clear path forward. Patient-centered improvement includes the essential elements of system redesign around human factors, including communication, physical resources, and updated information during episodes of care. The patient-centered improvement design is juxtaposed with care planning and establishing continuum of care processes.⁹ It is essential to note that safety is rooted within the quality domain as a top priority in medicine.¹⁰ The best implementation methods and approaches are discussed and debated, and the improvement progress continues on multiple fronts.¹¹ Patient safety systems are implemented simultaneously during the redesign phase. Moreover, identifying and testing the health care delivery methods in the era of competing strategic priorities to achieve the desirable clinical outcomes highlights the importance of implementation, while contemplating the methods of dissemination, scalability, and sustainability of the best evidence-based clinical practice.

The cycle of quality improvement research completes the system implementation efforts. The conceptual framework of quality improvement includes multiple areas of care and transition, along with applying the best clinical practices in a culture that emphasizes continuous improvement and learning. At the same time, the operating principles should include continuous improvement in a simple and continuous system of learning as a core concept. Our proposed implementation approach involves taking simple and practical steps while separating the process from the outcomes measures, extracting effectiveness throughout the process. It is essential to keep in mind that building a proactive and systematic improvement environment requires a framework for safety, reliability, and effective care, as well as the alignment of the physical system, communication, and professional environment and culture (Figure).

In summary, system design for quality improvement research should incorporate the principles and conceptual framework that embody effective implementation strategies, with a focus on operational and practical steps. Continuous improvement will be reached through the multidimensional development of current health care system metrics and the incorporation of implementation science methods.

Corresponding author: Ebrahim Barkoudah, MD, MPH, Department of Medicine, Brigham and Women’s Hospital, Boston, MA; [email protected]

Disclosures: None reported.

The Institute of Medicine brought much-needed attention to the need for process improvement in medicine with its seminal report To Err Is Human: Building a Safer Health System, which was issued in 1999, leading to the quality movement’s call to close health care performance gaps in Crossing the Quality Chasm: A New Health System for the 21st Century.^1,2 Quality improvement science in medicine has evolved over the past 2 decades to include a broad spectrum of approaches, from agile improvement to continuous learning and improvement. Current efforts focus on Lean-based process improvement along with a reduction in variation in clinical practice to align practice with the principles of evidence-based medicine in a patient-centered approach.³ Further, the definition of quality improvement under the Affordable Care Act was framed as an equitable, timely, value-based, patient-centered approach to achieving population-level health goals.⁴ Thus, the science of quality improvement drives the core principles of care delivery improvement, and the rigorous evidence needed to expand innovation is embedded within the same framework.^5,6 In clinical practice, quality improvement projects aim to define gaps and then specific steps are undertaken to improve the evidence-based practice of a specific process. The overarching goal is to enhance the efficacy of the practice by reducing waste within a particular domain. Thus, quality improvement and implementation research eventually unify how clinical practice is advanced concurrently to bridge identified gaps.⁷

System redesign through a patient-centered framework forms the core of an overarching strategy to support system-level processes. Both require a deep understanding of the fields of quality improvement science and implementation science.⁸ Furthermore, aligning clinical research needs, system aims, patients’ values, and clinical care give the new design a clear path forward. Patient-centered improvement includes the essential elements of system redesign around human factors, including communication, physical resources, and updated information during episodes of care. The patient-centered improvement design is juxtaposed with care planning and establishing continuum of care processes.⁹ It is essential to note that safety is rooted within the quality domain as a top priority in medicine.¹⁰ The best implementation methods and approaches are discussed and debated, and the improvement progress continues on multiple fronts.¹¹ Patient safety systems are implemented simultaneously during the redesign phase. Moreover, identifying and testing the health care delivery methods in the era of competing strategic priorities to achieve the desirable clinical outcomes highlights the importance of implementation, while contemplating the methods of dissemination, scalability, and sustainability of the best evidence-based clinical practice.

The cycle of quality improvement research completes the system implementation efforts. The conceptual framework of quality improvement includes multiple areas of care and transition, along with applying the best clinical practices in a culture that emphasizes continuous improvement and learning. At the same time, the operating principles should include continuous improvement in a simple and continuous system of learning as a core concept. Our proposed implementation approach involves taking simple and practical steps while separating the process from the outcomes measures, extracting effectiveness throughout the process. It is essential to keep in mind that building a proactive and systematic improvement environment requires a framework for safety, reliability, and effective care, as well as the alignment of the physical system, communication, and professional environment and culture (Figure).

In summary, system design for quality improvement research should incorporate the principles and conceptual framework that embody effective implementation strategies, with a focus on operational and practical steps. Continuous improvement will be reached through the multidimensional development of current health care system metrics and the incorporation of implementation science methods.

Corresponding author: Ebrahim Barkoudah, MD, MPH, Department of Medicine, Brigham and Women’s Hospital, Boston, MA; [email protected]

Disclosures: None reported.

From the Department of Cardiothoracic Surgery, Stanford University, Stanford, CA.

Abstract

Complex cardiac patients are often referred for surgery or palliative care based on the risk of perioperative mortality. This decision ignores factors such as quality of life or duration of life in either surgery or the palliative path. Here, we propose a model to numerically assess and compare the value of surgery vs palliation. This model includes quality and duration of life, as well as risk of perioperative mortality, and involves a patient’s preferences in the decision-making process.

For each pathway, surgery or palliative care, a value is calculated and compared to a normal life value (no disease symptoms and normal life expectancy). The formula is adjusted for the risk of operative mortality. The model produces a ratio of the value of surgery to the value of palliative care that signifies the superiority of one or another. This model calculation presents an objective estimated numerical value to compare the value of surgery and palliative care. It can be applied to every decision-making process before surgery. In general, if a procedure has the potential to significantly extend life in a patient who otherwise has a very short life expectancy with palliation only, performing high-risk surgery would be a reasonable option. A model that provides a numerical value for surgery vs palliative care and includes quality and duration of life in each pathway could be a useful tool for cardiac surgeons in decision making regarding high-risk surgery.

Keywords: high-risk surgery, palliative care, quality of life, life expectancy.

Patients with complex cardiovascular disease are occasionally considered inoperable due to the high risk of surgical mortality. When the risk of perioperative mortality (POM) is predicted to be too high, surgical intervention is denied, and patients are often referred to palliative care. The risk of POM in cardiac surgery is often calculated using large-scale databases, such as the Society of Thoracic Surgeons (STS) records. The STS risk models, which are regularly updated, are based on large data sets and incorporate precise statistical methods for risk adjustment.¹ In general, these calculators provide a percentage value that defines the magnitude of the risk of death, and then an arbitrary range is selected to categorize the procedure as low, medium, or high risk or inoperable status. The STS database does not set a cutoff point or range to define “operability.” Assigning inoperable status to a certain risk rate is problematic, with many ethical, legal, and moral implications, and for this reason, it has mostly remained undefined. In contrast, the low- and medium-risk ranges are easier to define. Another limitation encountered in the STS database is the lack of risk data for less common but very high-risk procedures, such as a triple valve replacement.

A common example where risk classification has been defined is in patients who are candidates for surgical vs transcatheter aortic valve replacement. Some groups have described a risk of <4% as low risk, 4% to 8% as intermediate risk, >8% as high risk, and >15% as inoperable²; for some other groups, a risk of POM >50% is considered extreme risk or inoperable.^3,4 This procedure-specific classification is a useful decision-making tool and helps the surgeon perform an initial risk assessment to allocate a specific patient to a group—operable or nonoperable—only by calculating the risk of surgical death. However, this allocation method does not provide any information on how and when death occurs in either group. These 2 parameters of how and when death occurs define the quality of life (QOL) and the duration of life (DOL), respectively, and together could be considered as the value of life in each pathway. A survivor of a high-risk surgery may benefit from good quality and extended life (a high value), or, on the other end of the spectrum, a high-risk patient who does not undergo surgery is spared the mortality risk of the surgery but dies sooner (low value) with symptoms due to the natural course of the untreated disease.

The central question is, if a surgery is high risk but has the potential of providing a good value (for those who survive it), what QOL and DOL values are acceptable to risk or to justify accepting and proceeding with a risky surgery? Or how high a POM risk is justified to proceed with surgery rather than the alternative palliative care with a certain quality and duration? It is obvious that a decision-making process that is based on POM cannot compare the value of surgery (Vs) and the value of palliation (Vp). Furthermore, it ignores patient preferences and their input, as these are excluded from this decision-making process.

To be able to include QOL and DOL in any decision making, one must precisely describe these parameters. Both QOL and DOL are used for estimation of disease burden by health care administrators, public health experts, insurance agencies, and others. Multiple models have been proposed and used to estimate the overall burden of the disease. Most of the models for this purpose are created for large-scale economic purposes and not for decision making in individual cases.

An important measure is the quality-adjusted life year (QALY). This is an important parameter since it includes both measures of quality and quantity of life.^5,6 QALY is a simplified measure to assess the value of health outcomes, and it has been used in economic calculations to assess mainly the cost-effectiveness of various interventions. We sought to evaluate the utility of a similar method in adding further insight into the surgical decision-making process. In this article, we propose a simple model to compare the value of surgery vs palliative care, similar to QALY. This model includes and adjusts for the quality and the quantity of life, in addition to the risk of POM, in the decision-making process for high-risk patients.

The Model

The 2 decision pathways, surgery and palliative care, are compared for their value. We define the value as the product of QOL and DOL in each pathway and use the severity of the symptoms as a surrogate for QOL. If duration and quality were depicted on the x and y axes of a graph (Figure 1), then the area under the curve would represent the collective value in each situation. Figure 2 shows the timeline and the different pathways with each decision. The value in each situation is calculated in relation to the full value, which is represented as the value of normal life (Vn), that is, life without disease and with normal life expectancy. The values of each decision pathway, the value of surgery (Vs) and the value of palliation (Vp), are then compared to define the benefit for each decision as follows:

If Vs/Vp > 1, the benefit is toward surgery;

If Vs/Vp < 1, the benefit is for palliative care.

Definitions

Both quality and duration of life are presented on a 1-10 scale, 1 being the lowest and 10 the highest value, to yield a product with a value of 100 in normal, disease-free life. Any lower value is presented as a percentage to represent the comparison to the full value. QOL is determined by degradation of full quality with the average level of symptoms. DOL is calculated as a lost time (period of time from death after a specific intervention [surgery or palliation] until death at normal life expectancy) in fraction of full life (death at life expectancy). The Vs is adjusted to exclude the nonsurvivors using the chance of survival (100 – POM risk).

For the DOL under any condition, a 10-year survival rate could be used as a surrogate in this formula. Compared to life expectancy value, using the 10-year survival rate simplifies the calculation since cardiac diseases are more prevalent in older age, close to or beyond the average life expectancy value.

Using the time intervals from the timeline in Figure 2:

dh = time interval from diagnosis to death at life expectancy

dg = time interval from diagnosis to death after successful surgery

df = time interval from diagnosis to death after palliative care

Duration for palliative care:

Duration for surgery:

Adjustment: This value is calculated for those who survive the surgery. To adjust for the POM, it is multiplied by the 100 − POM risk.

Since value is the base for comparison in this model, and it is the product of 2 equally important factors in the formula (severity and duration of symptoms), a factor of 10 was chosen to yield a value of 100, which represents 100% health or absence of symptoms for any duration.

After elimination of normal life expectancy, form the numerator and denominator:

To adjust for surgical outcomes in special circumstances where less than optimal or standard surgical results are expected (eg, in very rare surgeries, limited resource institutions, or suboptimal postoperative surgical care), an optional coefficient R can be added to the numerator (surgical value). This optional coefficient, with values such as 0.8, 0.9 (to degrade the value of surgery) or 1 (standard surgical outcome), adjusts for variability in interinstitutional surgical results or surgeon variability. No coefficient is added to the denominator since palliative care provides minimal differences between clinicians and hospitals. Thus, the final adjusted formula would be as follows:

Example

A 60-year-old patient with a 10% POM risk needs to be allocated to surgical or palliative care. With palliative care, if this patient lived 6 years with average symptoms grade 4, the Vp would be 20; that is, 20% of the normal life value (if he lived 18 years instead without the disease).

Using the formula for calculation of value in each pathway:

With adjustment of 90% survival chance in surgery, 53 × 90% = 48%. In this example, Vs/Vp = 48/20 = 2.4, showing a significant benefit for surgical care. Notably, the unknown value of normal life expectancy is not needed for the calculation of Vs/Vp, since it is the same in both pathways and it is eliminated by calculation in fraction.

Based on this formula, since the duration of surgical symptoms is short, no matter how severe these are, if the potential duration of life after surgery is high (represented by smaller area under the curve in Figure 1), the numerator becomes larger and the value of the surgery grows. For example, if a patient with a 15% risk of POM, which is generally considered inoperable, lives 5 years, as opposed to 2 years with palliative care with mild symptoms (eg 3/10), Vs/Vp would be 2.7, still showing a significant benefit for surgical care.

Discussion

Any surgical intervention is offered with 2 goals in mind, improving QOL and extending DOL. In a high-risk patient, surgery might be declined due to a high risk of POM, and the patient is offered palliative care, which other than providing symptom relief does not change the course of disease and eventually the patient will die due to the untreated disease. In this decision-making method, mostly completed by a care team only, a potential risk of death due to surgery which possibly could cure the patient is traded for immediate survival; however, the symptomatic course ensues until death. This mostly unilateral decision-making process by a care team, which incorporates minimal input from the patient or ignores patient preferences altogether, is based only on POM risk, and roughly includes a single parameter: years of potential life lost (YPLL). YPLL is a measure of premature mortality, and in the setting of surgical intervention, YPLL is the number of years a patient would lose unless a successful surgery were undertaken. Obviously, patients would live longer if a surgery that was intended to save them failed.

In this article, we proposed a simple method to quantify each decision to decide whether to operate or choose surgical care vs palliative care. Since quality and duration of life are both end factors clinicians and patients aspire to in each decision, they can be considered together as the value of each decision. We believe a numerical framework would provide an objective way to assist both the patient at high risk and the care team in the decision-making process.

The 2 parameters we consider are DOL and QOL. DOL, or survival, can be extracted from large-scale data using statistical methods that have been developed to predict survival under various conditions, such as Kaplan-Meier curves. These methods present the chance of survival in percentages in a defined time frame, such as a 5- or 10-year period.

While the DOL is a numerical parameter and quantifiable, the QOL is a more complex entity. This subjective parameter bears multiple definitions, aspects, and categories, and therefore multiple scales for quantification of QOL have been proposed. These scales have been used extensively for the purpose of health determination in health care policy and economic planning. Most scales acknowledge that QOL is multifactorial and includes interrelated aspects such as mental and socioeconomic factors. We have also noticed that QOL is better determined by the palliative care team than surgeons, so including these care providers in the decision-making process might reduce surgeon bias.

Since our purpose here is only to assist with the decision on medical intervention, we focus on physical QOL. Multiple scales are used to assess health-related QOL, such as the Assessment of Quality of Life (AQoL)-8D,⁷ EuroQol-5 Dimension (EQ-5D),⁸ 15D,⁹ and the 36-Item Short Form Survey (SF-36).¹⁰ These complex scales are built for systematic reviews, and they are not practical for a clinical user. To simplify and keep this practical, we define QOL by using the severity or grade of symptoms related to the disease the patient has on a scale of 0 to 10. The severity of symptoms can be easily determined using available scales. An applicable scale for this purpose is the Edmonton Symptom Assessment Scale (ESAS), which has been in use for years and has evolved as a useful tool in the medical field.¹¹

Once DOL and QOL are determined on a 1-10 scale, the multiplied value then provides a product that we consider a value. The highest value hoped for in each decision is the achievement of the best QOL and DOL, a value of 100. In Figure 1, a graphic presentation of value in each decision is best seen as the area under the curve. As shown, a successful surgery, even when accompanied by significant symptoms during initial recovery, has a chance (100 – risk of POM%) to gain a larger area under curve (value) by achieving a longer life with no or fewer symptoms. However, in palliative care, progressing disease and even palliated symptoms with a shorter life expectancy impose a large burden on the patient and a much lower value. Note that in this calculation, life expectancy, which is an important but unpredictable factor, is initially included; however, by ratio comparison, it is eliminated, simplifying the calculation further.

Using this formula in different settings reveals that high-risk surgery has a greater potential to reduce YPLL in the general population. Based on this formula, compared to a surgery with potential to significantly extend DOL, a definite shorter and symptomatic life course with palliative care makes it a significantly less favorable option. In fact, in the cardiovascular field, palliative care has minimal or no effect on natural history, as the mechanism of illness is mechanical, such as occlusion of coronary arteries or valve dysfunction, leading eventually to heart failure and death. In a study by Xu et al, although palliative care reduced readmission rates and improved symptoms on a variety of scales, there was no effect on mortality and QOL in patients with heart failure.¹²

No model in this field has proven to be ideal, and this model bears multiple limitations as well. We have used severity of symptoms as a surrogate for QOL based on the fact that cardiac patients with different pathologies who are untreated will have a common final pathway with development of heart failure symptoms that dictate their QOL. Also, grading QOL is a difficult task at times. Even a model such as QALY, which is one of the most used, is not a perfect model and is not free of problems.⁶ The difference in surgical results and life expectancy between sexes and ethnic groups might be a source of bias in this formula. Also, multiple factors directly and indirectly affect QOL and DOL and create inaccuracies; therefore, making an exact science from an inexact one naturally relies on multiple assumptions. Although it has previously been shown that most POM occurs in a short period of time after cardiac surgery,¹³ long-term complications that potentially degrade QOL are not included in this model. By applying this model, one must assume indefinite economic resources. Moreover, applying a single mathematical model in a biologic system and in the general population has intrinsic shortcomings, and it must overlook many other factors (eg, ethical, legal). For example, it will be hard to justify a failed surgery with 15% risk of POM undertaken to eliminate the severe long-lasting symptoms of a disease, while the outcome of a successful surgery with a 20% risk of POM that adds life and quality would be ignored in the current health care system. Thus, regardless of the significant potential, most surgeons would waive a surgery based solely on the percentage rate of POM, perhaps using other terms such as ”peri-nonoperative mortality.”

Conclusion

We have proposed a simple and practical formula for decision making regarding surgical vs palliative care in high-risk patients. By assigning a value that is composed of QOL and DOL in each pathway and including the risk of POM, a ratio of values provides a numerical estimation that can be used to show preference over a specific decision. An advantage of this formula, in addition to presenting an arithmetic value that is easier to understand, is that it can be used in shared decision making with patients. We emphasize that this model is only a preliminary concept at this time and has not been tested or validated for clinical use. Validation of such a model will require extensive work and testing within a large-scale population. We hope that this article will serve as a starting point for the development of other models, and that this formula will become more sophisticated with fewer limitations through larger multidisciplinary efforts in the future.

Corresponding author: Rabin Gerrah, MD, Good Samaritan Regional Medical Center, 3640 NW Samaritan Drive, Suite 100B, Corvallis, OR 97330; [email protected].

Disclosures: None reported.

From the Department of Cardiothoracic Surgery, Stanford University, Stanford, CA.

Abstract

Complex cardiac patients are often referred for surgery or palliative care based on the risk of perioperative mortality. This decision ignores factors such as quality of life or duration of life in either surgery or the palliative path. Here, we propose a model to numerically assess and compare the value of surgery vs palliation. This model includes quality and duration of life, as well as risk of perioperative mortality, and involves a patient’s preferences in the decision-making process.

For each pathway, surgery or palliative care, a value is calculated and compared to a normal life value (no disease symptoms and normal life expectancy). The formula is adjusted for the risk of operative mortality. The model produces a ratio of the value of surgery to the value of palliative care that signifies the superiority of one or another. This model calculation presents an objective estimated numerical value to compare the value of surgery and palliative care. It can be applied to every decision-making process before surgery. In general, if a procedure has the potential to significantly extend life in a patient who otherwise has a very short life expectancy with palliation only, performing high-risk surgery would be a reasonable option. A model that provides a numerical value for surgery vs palliative care and includes quality and duration of life in each pathway could be a useful tool for cardiac surgeons in decision making regarding high-risk surgery.

Keywords: high-risk surgery, palliative care, quality of life, life expectancy.

Patients with complex cardiovascular disease are occasionally considered inoperable due to the high risk of surgical mortality. When the risk of perioperative mortality (POM) is predicted to be too high, surgical intervention is denied, and patients are often referred to palliative care. The risk of POM in cardiac surgery is often calculated using large-scale databases, such as the Society of Thoracic Surgeons (STS) records. The STS risk models, which are regularly updated, are based on large data sets and incorporate precise statistical methods for risk adjustment.¹ In general, these calculators provide a percentage value that defines the magnitude of the risk of death, and then an arbitrary range is selected to categorize the procedure as low, medium, or high risk or inoperable status. The STS database does not set a cutoff point or range to define “operability.” Assigning inoperable status to a certain risk rate is problematic, with many ethical, legal, and moral implications, and for this reason, it has mostly remained undefined. In contrast, the low- and medium-risk ranges are easier to define. Another limitation encountered in the STS database is the lack of risk data for less common but very high-risk procedures, such as a triple valve replacement.

A common example where risk classification has been defined is in patients who are candidates for surgical vs transcatheter aortic valve replacement. Some groups have described a risk of <4% as low risk, 4% to 8% as intermediate risk, >8% as high risk, and >15% as inoperable²; for some other groups, a risk of POM >50% is considered extreme risk or inoperable.^3,4 This procedure-specific classification is a useful decision-making tool and helps the surgeon perform an initial risk assessment to allocate a specific patient to a group—operable or nonoperable—only by calculating the risk of surgical death. However, this allocation method does not provide any information on how and when death occurs in either group. These 2 parameters of how and when death occurs define the quality of life (QOL) and the duration of life (DOL), respectively, and together could be considered as the value of life in each pathway. A survivor of a high-risk surgery may benefit from good quality and extended life (a high value), or, on the other end of the spectrum, a high-risk patient who does not undergo surgery is spared the mortality risk of the surgery but dies sooner (low value) with symptoms due to the natural course of the untreated disease.

The central question is, if a surgery is high risk but has the potential of providing a good value (for those who survive it), what QOL and DOL values are acceptable to risk or to justify accepting and proceeding with a risky surgery? Or how high a POM risk is justified to proceed with surgery rather than the alternative palliative care with a certain quality and duration? It is obvious that a decision-making process that is based on POM cannot compare the value of surgery (Vs) and the value of palliation (Vp). Furthermore, it ignores patient preferences and their input, as these are excluded from this decision-making process.

To be able to include QOL and DOL in any decision making, one must precisely describe these parameters. Both QOL and DOL are used for estimation of disease burden by health care administrators, public health experts, insurance agencies, and others. Multiple models have been proposed and used to estimate the overall burden of the disease. Most of the models for this purpose are created for large-scale economic purposes and not for decision making in individual cases.

An important measure is the quality-adjusted life year (QALY). This is an important parameter since it includes both measures of quality and quantity of life.^5,6 QALY is a simplified measure to assess the value of health outcomes, and it has been used in economic calculations to assess mainly the cost-effectiveness of various interventions. We sought to evaluate the utility of a similar method in adding further insight into the surgical decision-making process. In this article, we propose a simple model to compare the value of surgery vs palliative care, similar to QALY. This model includes and adjusts for the quality and the quantity of life, in addition to the risk of POM, in the decision-making process for high-risk patients.

The Model

The 2 decision pathways, surgery and palliative care, are compared for their value. We define the value as the product of QOL and DOL in each pathway and use the severity of the symptoms as a surrogate for QOL. If duration and quality were depicted on the x and y axes of a graph (Figure 1), then the area under the curve would represent the collective value in each situation. Figure 2 shows the timeline and the different pathways with each decision. The value in each situation is calculated in relation to the full value, which is represented as the value of normal life (Vn), that is, life without disease and with normal life expectancy. The values of each decision pathway, the value of surgery (Vs) and the value of palliation (Vp), are then compared to define the benefit for each decision as follows:

If Vs/Vp > 1, the benefit is toward surgery;

If Vs/Vp < 1, the benefit is for palliative care.

Definitions

Both quality and duration of life are presented on a 1-10 scale, 1 being the lowest and 10 the highest value, to yield a product with a value of 100 in normal, disease-free life. Any lower value is presented as a percentage to represent the comparison to the full value. QOL is determined by degradation of full quality with the average level of symptoms. DOL is calculated as a lost time (period of time from death after a specific intervention [surgery or palliation] until death at normal life expectancy) in fraction of full life (death at life expectancy). The Vs is adjusted to exclude the nonsurvivors using the chance of survival (100 – POM risk).

For the DOL under any condition, a 10-year survival rate could be used as a surrogate in this formula. Compared to life expectancy value, using the 10-year survival rate simplifies the calculation since cardiac diseases are more prevalent in older age, close to or beyond the average life expectancy value.

Using the time intervals from the timeline in Figure 2:

dh = time interval from diagnosis to death at life expectancy

dg = time interval from diagnosis to death after successful surgery

df = time interval from diagnosis to death after palliative care

Duration for palliative care:

Duration for surgery:

Adjustment: This value is calculated for those who survive the surgery. To adjust for the POM, it is multiplied by the 100 − POM risk.

Since value is the base for comparison in this model, and it is the product of 2 equally important factors in the formula (severity and duration of symptoms), a factor of 10 was chosen to yield a value of 100, which represents 100% health or absence of symptoms for any duration.

After elimination of normal life expectancy, form the numerator and denominator:

To adjust for surgical outcomes in special circumstances where less than optimal or standard surgical results are expected (eg, in very rare surgeries, limited resource institutions, or suboptimal postoperative surgical care), an optional coefficient R can be added to the numerator (surgical value). This optional coefficient, with values such as 0.8, 0.9 (to degrade the value of surgery) or 1 (standard surgical outcome), adjusts for variability in interinstitutional surgical results or surgeon variability. No coefficient is added to the denominator since palliative care provides minimal differences between clinicians and hospitals. Thus, the final adjusted formula would be as follows:

Example

A 60-year-old patient with a 10% POM risk needs to be allocated to surgical or palliative care. With palliative care, if this patient lived 6 years with average symptoms grade 4, the Vp would be 20; that is, 20% of the normal life value (if he lived 18 years instead without the disease).

Using the formula for calculation of value in each pathway:

With adjustment of 90% survival chance in surgery, 53 × 90% = 48%. In this example, Vs/Vp = 48/20 = 2.4, showing a significant benefit for surgical care. Notably, the unknown value of normal life expectancy is not needed for the calculation of Vs/Vp, since it is the same in both pathways and it is eliminated by calculation in fraction.

Based on this formula, since the duration of surgical symptoms is short, no matter how severe these are, if the potential duration of life after surgery is high (represented by smaller area under the curve in Figure 1), the numerator becomes larger and the value of the surgery grows. For example, if a patient with a 15% risk of POM, which is generally considered inoperable, lives 5 years, as opposed to 2 years with palliative care with mild symptoms (eg 3/10), Vs/Vp would be 2.7, still showing a significant benefit for surgical care.

Discussion

Any surgical intervention is offered with 2 goals in mind, improving QOL and extending DOL. In a high-risk patient, surgery might be declined due to a high risk of POM, and the patient is offered palliative care, which other than providing symptom relief does not change the course of disease and eventually the patient will die due to the untreated disease. In this decision-making method, mostly completed by a care team only, a potential risk of death due to surgery which possibly could cure the patient is traded for immediate survival; however, the symptomatic course ensues until death. This mostly unilateral decision-making process by a care team, which incorporates minimal input from the patient or ignores patient preferences altogether, is based only on POM risk, and roughly includes a single parameter: years of potential life lost (YPLL). YPLL is a measure of premature mortality, and in the setting of surgical intervention, YPLL is the number of years a patient would lose unless a successful surgery were undertaken. Obviously, patients would live longer if a surgery that was intended to save them failed.

In this article, we proposed a simple method to quantify each decision to decide whether to operate or choose surgical care vs palliative care. Since quality and duration of life are both end factors clinicians and patients aspire to in each decision, they can be considered together as the value of each decision. We believe a numerical framework would provide an objective way to assist both the patient at high risk and the care team in the decision-making process.

The 2 parameters we consider are DOL and QOL. DOL, or survival, can be extracted from large-scale data using statistical methods that have been developed to predict survival under various conditions, such as Kaplan-Meier curves. These methods present the chance of survival in percentages in a defined time frame, such as a 5- or 10-year period.

While the DOL is a numerical parameter and quantifiable, the QOL is a more complex entity. This subjective parameter bears multiple definitions, aspects, and categories, and therefore multiple scales for quantification of QOL have been proposed. These scales have been used extensively for the purpose of health determination in health care policy and economic planning. Most scales acknowledge that QOL is multifactorial and includes interrelated aspects such as mental and socioeconomic factors. We have also noticed that QOL is better determined by the palliative care team than surgeons, so including these care providers in the decision-making process might reduce surgeon bias.

Since our purpose here is only to assist with the decision on medical intervention, we focus on physical QOL. Multiple scales are used to assess health-related QOL, such as the Assessment of Quality of Life (AQoL)-8D,⁷ EuroQol-5 Dimension (EQ-5D),⁸ 15D,⁹ and the 36-Item Short Form Survey (SF-36).¹⁰ These complex scales are built for systematic reviews, and they are not practical for a clinical user. To simplify and keep this practical, we define QOL by using the severity or grade of symptoms related to the disease the patient has on a scale of 0 to 10. The severity of symptoms can be easily determined using available scales. An applicable scale for this purpose is the Edmonton Symptom Assessment Scale (ESAS), which has been in use for years and has evolved as a useful tool in the medical field.¹¹

Once DOL and QOL are determined on a 1-10 scale, the multiplied value then provides a product that we consider a value. The highest value hoped for in each decision is the achievement of the best QOL and DOL, a value of 100. In Figure 1, a graphic presentation of value in each decision is best seen as the area under the curve. As shown, a successful surgery, even when accompanied by significant symptoms during initial recovery, has a chance (100 – risk of POM%) to gain a larger area under curve (value) by achieving a longer life with no or fewer symptoms. However, in palliative care, progressing disease and even palliated symptoms with a shorter life expectancy impose a large burden on the patient and a much lower value. Note that in this calculation, life expectancy, which is an important but unpredictable factor, is initially included; however, by ratio comparison, it is eliminated, simplifying the calculation further.

Using this formula in different settings reveals that high-risk surgery has a greater potential to reduce YPLL in the general population. Based on this formula, compared to a surgery with potential to significantly extend DOL, a definite shorter and symptomatic life course with palliative care makes it a significantly less favorable option. In fact, in the cardiovascular field, palliative care has minimal or no effect on natural history, as the mechanism of illness is mechanical, such as occlusion of coronary arteries or valve dysfunction, leading eventually to heart failure and death. In a study by Xu et al, although palliative care reduced readmission rates and improved symptoms on a variety of scales, there was no effect on mortality and QOL in patients with heart failure.¹²

No model in this field has proven to be ideal, and this model bears multiple limitations as well. We have used severity of symptoms as a surrogate for QOL based on the fact that cardiac patients with different pathologies who are untreated will have a common final pathway with development of heart failure symptoms that dictate their QOL. Also, grading QOL is a difficult task at times. Even a model such as QALY, which is one of the most used, is not a perfect model and is not free of problems.⁶ The difference in surgical results and life expectancy between sexes and ethnic groups might be a source of bias in this formula. Also, multiple factors directly and indirectly affect QOL and DOL and create inaccuracies; therefore, making an exact science from an inexact one naturally relies on multiple assumptions. Although it has previously been shown that most POM occurs in a short period of time after cardiac surgery,¹³ long-term complications that potentially degrade QOL are not included in this model. By applying this model, one must assume indefinite economic resources. Moreover, applying a single mathematical model in a biologic system and in the general population has intrinsic shortcomings, and it must overlook many other factors (eg, ethical, legal). For example, it will be hard to justify a failed surgery with 15% risk of POM undertaken to eliminate the severe long-lasting symptoms of a disease, while the outcome of a successful surgery with a 20% risk of POM that adds life and quality would be ignored in the current health care system. Thus, regardless of the significant potential, most surgeons would waive a surgery based solely on the percentage rate of POM, perhaps using other terms such as ”peri-nonoperative mortality.”

Conclusion

We have proposed a simple and practical formula for decision making regarding surgical vs palliative care in high-risk patients. By assigning a value that is composed of QOL and DOL in each pathway and including the risk of POM, a ratio of values provides a numerical estimation that can be used to show preference over a specific decision. An advantage of this formula, in addition to presenting an arithmetic value that is easier to understand, is that it can be used in shared decision making with patients. We emphasize that this model is only a preliminary concept at this time and has not been tested or validated for clinical use. Validation of such a model will require extensive work and testing within a large-scale population. We hope that this article will serve as a starting point for the development of other models, and that this formula will become more sophisticated with fewer limitations through larger multidisciplinary efforts in the future.

Corresponding author: Rabin Gerrah, MD, Good Samaritan Regional Medical Center, 3640 NW Samaritan Drive, Suite 100B, Corvallis, OR 97330; [email protected].

Disclosures: None reported.

From the Department of Cardiothoracic Surgery, Stanford University, Stanford, CA.

Abstract

Complex cardiac patients are often referred for surgery or palliative care based on the risk of perioperative mortality. This decision ignores factors such as quality of life or duration of life in either surgery or the palliative path. Here, we propose a model to numerically assess and compare the value of surgery vs palliation. This model includes quality and duration of life, as well as risk of perioperative mortality, and involves a patient’s preferences in the decision-making process.

For each pathway, surgery or palliative care, a value is calculated and compared to a normal life value (no disease symptoms and normal life expectancy). The formula is adjusted for the risk of operative mortality. The model produces a ratio of the value of surgery to the value of palliative care that signifies the superiority of one or another. This model calculation presents an objective estimated numerical value to compare the value of surgery and palliative care. It can be applied to every decision-making process before surgery. In general, if a procedure has the potential to significantly extend life in a patient who otherwise has a very short life expectancy with palliation only, performing high-risk surgery would be a reasonable option. A model that provides a numerical value for surgery vs palliative care and includes quality and duration of life in each pathway could be a useful tool for cardiac surgeons in decision making regarding high-risk surgery.

Keywords: high-risk surgery, palliative care, quality of life, life expectancy.

Patients with complex cardiovascular disease are occasionally considered inoperable due to the high risk of surgical mortality. When the risk of perioperative mortality (POM) is predicted to be too high, surgical intervention is denied, and patients are often referred to palliative care. The risk of POM in cardiac surgery is often calculated using large-scale databases, such as the Society of Thoracic Surgeons (STS) records. The STS risk models, which are regularly updated, are based on large data sets and incorporate precise statistical methods for risk adjustment.¹ In general, these calculators provide a percentage value that defines the magnitude of the risk of death, and then an arbitrary range is selected to categorize the procedure as low, medium, or high risk or inoperable status. The STS database does not set a cutoff point or range to define “operability.” Assigning inoperable status to a certain risk rate is problematic, with many ethical, legal, and moral implications, and for this reason, it has mostly remained undefined. In contrast, the low- and medium-risk ranges are easier to define. Another limitation encountered in the STS database is the lack of risk data for less common but very high-risk procedures, such as a triple valve replacement.

A common example where risk classification has been defined is in patients who are candidates for surgical vs transcatheter aortic valve replacement. Some groups have described a risk of <4% as low risk, 4% to 8% as intermediate risk, >8% as high risk, and >15% as inoperable²; for some other groups, a risk of POM >50% is considered extreme risk or inoperable.^3,4 This procedure-specific classification is a useful decision-making tool and helps the surgeon perform an initial risk assessment to allocate a specific patient to a group—operable or nonoperable—only by calculating the risk of surgical death. However, this allocation method does not provide any information on how and when death occurs in either group. These 2 parameters of how and when death occurs define the quality of life (QOL) and the duration of life (DOL), respectively, and together could be considered as the value of life in each pathway. A survivor of a high-risk surgery may benefit from good quality and extended life (a high value), or, on the other end of the spectrum, a high-risk patient who does not undergo surgery is spared the mortality risk of the surgery but dies sooner (low value) with symptoms due to the natural course of the untreated disease.

The central question is, if a surgery is high risk but has the potential of providing a good value (for those who survive it), what QOL and DOL values are acceptable to risk or to justify accepting and proceeding with a risky surgery? Or how high a POM risk is justified to proceed with surgery rather than the alternative palliative care with a certain quality and duration? It is obvious that a decision-making process that is based on POM cannot compare the value of surgery (Vs) and the value of palliation (Vp). Furthermore, it ignores patient preferences and their input, as these are excluded from this decision-making process.

To be able to include QOL and DOL in any decision making, one must precisely describe these parameters. Both QOL and DOL are used for estimation of disease burden by health care administrators, public health experts, insurance agencies, and others. Multiple models have been proposed and used to estimate the overall burden of the disease. Most of the models for this purpose are created for large-scale economic purposes and not for decision making in individual cases.

An important measure is the quality-adjusted life year (QALY). This is an important parameter since it includes both measures of quality and quantity of life.^5,6 QALY is a simplified measure to assess the value of health outcomes, and it has been used in economic calculations to assess mainly the cost-effectiveness of various interventions. We sought to evaluate the utility of a similar method in adding further insight into the surgical decision-making process. In this article, we propose a simple model to compare the value of surgery vs palliative care, similar to QALY. This model includes and adjusts for the quality and the quantity of life, in addition to the risk of POM, in the decision-making process for high-risk patients.

The Model

The 2 decision pathways, surgery and palliative care, are compared for their value. We define the value as the product of QOL and DOL in each pathway and use the severity of the symptoms as a surrogate for QOL. If duration and quality were depicted on the x and y axes of a graph (Figure 1), then the area under the curve would represent the collective value in each situation. Figure 2 shows the timeline and the different pathways with each decision. The value in each situation is calculated in relation to the full value, which is represented as the value of normal life (Vn), that is, life without disease and with normal life expectancy. The values of each decision pathway, the value of surgery (Vs) and the value of palliation (Vp), are then compared to define the benefit for each decision as follows:

If Vs/Vp > 1, the benefit is toward surgery;

If Vs/Vp < 1, the benefit is for palliative care.

Definitions

Both quality and duration of life are presented on a 1-10 scale, 1 being the lowest and 10 the highest value, to yield a product with a value of 100 in normal, disease-free life. Any lower value is presented as a percentage to represent the comparison to the full value. QOL is determined by degradation of full quality with the average level of symptoms. DOL is calculated as a lost time (period of time from death after a specific intervention [surgery or palliation] until death at normal life expectancy) in fraction of full life (death at life expectancy). The Vs is adjusted to exclude the nonsurvivors using the chance of survival (100 – POM risk).

For the DOL under any condition, a 10-year survival rate could be used as a surrogate in this formula. Compared to life expectancy value, using the 10-year survival rate simplifies the calculation since cardiac diseases are more prevalent in older age, close to or beyond the average life expectancy value.

Using the time intervals from the timeline in Figure 2:

dh = time interval from diagnosis to death at life expectancy

dg = time interval from diagnosis to death after successful surgery

df = time interval from diagnosis to death after palliative care

Duration for palliative care:

Duration for surgery:

Adjustment: This value is calculated for those who survive the surgery. To adjust for the POM, it is multiplied by the 100 − POM risk.

Since value is the base for comparison in this model, and it is the product of 2 equally important factors in the formula (severity and duration of symptoms), a factor of 10 was chosen to yield a value of 100, which represents 100% health or absence of symptoms for any duration.

After elimination of normal life expectancy, form the numerator and denominator:

To adjust for surgical outcomes in special circumstances where less than optimal or standard surgical results are expected (eg, in very rare surgeries, limited resource institutions, or suboptimal postoperative surgical care), an optional coefficient R can be added to the numerator (surgical value). This optional coefficient, with values such as 0.8, 0.9 (to degrade the value of surgery) or 1 (standard surgical outcome), adjusts for variability in interinstitutional surgical results or surgeon variability. No coefficient is added to the denominator since palliative care provides minimal differences between clinicians and hospitals. Thus, the final adjusted formula would be as follows:

Example

A 60-year-old patient with a 10% POM risk needs to be allocated to surgical or palliative care. With palliative care, if this patient lived 6 years with average symptoms grade 4, the Vp would be 20; that is, 20% of the normal life value (if he lived 18 years instead without the disease).

Using the formula for calculation of value in each pathway:

With adjustment of 90% survival chance in surgery, 53 × 90% = 48%. In this example, Vs/Vp = 48/20 = 2.4, showing a significant benefit for surgical care. Notably, the unknown value of normal life expectancy is not needed for the calculation of Vs/Vp, since it is the same in both pathways and it is eliminated by calculation in fraction.

Based on this formula, since the duration of surgical symptoms is short, no matter how severe these are, if the potential duration of life after surgery is high (represented by smaller area under the curve in Figure 1), the numerator becomes larger and the value of the surgery grows. For example, if a patient with a 15% risk of POM, which is generally considered inoperable, lives 5 years, as opposed to 2 years with palliative care with mild symptoms (eg 3/10), Vs/Vp would be 2.7, still showing a significant benefit for surgical care.

Discussion

Any surgical intervention is offered with 2 goals in mind, improving QOL and extending DOL. In a high-risk patient, surgery might be declined due to a high risk of POM, and the patient is offered palliative care, which other than providing symptom relief does not change the course of disease and eventually the patient will die due to the untreated disease. In this decision-making method, mostly completed by a care team only, a potential risk of death due to surgery which possibly could cure the patient is traded for immediate survival; however, the symptomatic course ensues until death. This mostly unilateral decision-making process by a care team, which incorporates minimal input from the patient or ignores patient preferences altogether, is based only on POM risk, and roughly includes a single parameter: years of potential life lost (YPLL). YPLL is a measure of premature mortality, and in the setting of surgical intervention, YPLL is the number of years a patient would lose unless a successful surgery were undertaken. Obviously, patients would live longer if a surgery that was intended to save them failed.

In this article, we proposed a simple method to quantify each decision to decide whether to operate or choose surgical care vs palliative care. Since quality and duration of life are both end factors clinicians and patients aspire to in each decision, they can be considered together as the value of each decision. We believe a numerical framework would provide an objective way to assist both the patient at high risk and the care team in the decision-making process.

The 2 parameters we consider are DOL and QOL. DOL, or survival, can be extracted from large-scale data using statistical methods that have been developed to predict survival under various conditions, such as Kaplan-Meier curves. These methods present the chance of survival in percentages in a defined time frame, such as a 5- or 10-year period.

While the DOL is a numerical parameter and quantifiable, the QOL is a more complex entity. This subjective parameter bears multiple definitions, aspects, and categories, and therefore multiple scales for quantification of QOL have been proposed. These scales have been used extensively for the purpose of health determination in health care policy and economic planning. Most scales acknowledge that QOL is multifactorial and includes interrelated aspects such as mental and socioeconomic factors. We have also noticed that QOL is better determined by the palliative care team than surgeons, so including these care providers in the decision-making process might reduce surgeon bias.

Since our purpose here is only to assist with the decision on medical intervention, we focus on physical QOL. Multiple scales are used to assess health-related QOL, such as the Assessment of Quality of Life (AQoL)-8D,⁷ EuroQol-5 Dimension (EQ-5D),⁸ 15D,⁹ and the 36-Item Short Form Survey (SF-36).¹⁰ These complex scales are built for systematic reviews, and they are not practical for a clinical user. To simplify and keep this practical, we define QOL by using the severity or grade of symptoms related to the disease the patient has on a scale of 0 to 10. The severity of symptoms can be easily determined using available scales. An applicable scale for this purpose is the Edmonton Symptom Assessment Scale (ESAS), which has been in use for years and has evolved as a useful tool in the medical field.¹¹

Once DOL and QOL are determined on a 1-10 scale, the multiplied value then provides a product that we consider a value. The highest value hoped for in each decision is the achievement of the best QOL and DOL, a value of 100. In Figure 1, a graphic presentation of value in each decision is best seen as the area under the curve. As shown, a successful surgery, even when accompanied by significant symptoms during initial recovery, has a chance (100 – risk of POM%) to gain a larger area under curve (value) by achieving a longer life with no or fewer symptoms. However, in palliative care, progressing disease and even palliated symptoms with a shorter life expectancy impose a large burden on the patient and a much lower value. Note that in this calculation, life expectancy, which is an important but unpredictable factor, is initially included; however, by ratio comparison, it is eliminated, simplifying the calculation further.

Using this formula in different settings reveals that high-risk surgery has a greater potential to reduce YPLL in the general population. Based on this formula, compared to a surgery with potential to significantly extend DOL, a definite shorter and symptomatic life course with palliative care makes it a significantly less favorable option. In fact, in the cardiovascular field, palliative care has minimal or no effect on natural history, as the mechanism of illness is mechanical, such as occlusion of coronary arteries or valve dysfunction, leading eventually to heart failure and death. In a study by Xu et al, although palliative care reduced readmission rates and improved symptoms on a variety of scales, there was no effect on mortality and QOL in patients with heart failure.¹²

No model in this field has proven to be ideal, and this model bears multiple limitations as well. We have used severity of symptoms as a surrogate for QOL based on the fact that cardiac patients with different pathologies who are untreated will have a common final pathway with development of heart failure symptoms that dictate their QOL. Also, grading QOL is a difficult task at times. Even a model such as QALY, which is one of the most used, is not a perfect model and is not free of problems.⁶ The difference in surgical results and life expectancy between sexes and ethnic groups might be a source of bias in this formula. Also, multiple factors directly and indirectly affect QOL and DOL and create inaccuracies; therefore, making an exact science from an inexact one naturally relies on multiple assumptions. Although it has previously been shown that most POM occurs in a short period of time after cardiac surgery,¹³ long-term complications that potentially degrade QOL are not included in this model. By applying this model, one must assume indefinite economic resources. Moreover, applying a single mathematical model in a biologic system and in the general population has intrinsic shortcomings, and it must overlook many other factors (eg, ethical, legal). For example, it will be hard to justify a failed surgery with 15% risk of POM undertaken to eliminate the severe long-lasting symptoms of a disease, while the outcome of a successful surgery with a 20% risk of POM that adds life and quality would be ignored in the current health care system. Thus, regardless of the significant potential, most surgeons would waive a surgery based solely on the percentage rate of POM, perhaps using other terms such as ”peri-nonoperative mortality.”

Conclusion

We have proposed a simple and practical formula for decision making regarding surgical vs palliative care in high-risk patients. By assigning a value that is composed of QOL and DOL in each pathway and including the risk of POM, a ratio of values provides a numerical estimation that can be used to show preference over a specific decision. An advantage of this formula, in addition to presenting an arithmetic value that is easier to understand, is that it can be used in shared decision making with patients. We emphasize that this model is only a preliminary concept at this time and has not been tested or validated for clinical use. Validation of such a model will require extensive work and testing within a large-scale population. We hope that this article will serve as a starting point for the development of other models, and that this formula will become more sophisticated with fewer limitations through larger multidisciplinary efforts in the future.

Corresponding author: Rabin Gerrah, MD, Good Samaritan Regional Medical Center, 3640 NW Samaritan Drive, Suite 100B, Corvallis, OR 97330; [email protected].

Disclosures: None reported.

There is a feeling of exhaustion, being unable to shake a lingering cold, suffering from frequent headaches and gastrointestinal disturbances, sleeplessness and shortness of breath ...

That was how burnout was described by clinical psychologist Herbert Freudenberger, PhD, who first used the phrase in a paper back in 1974, after observing the emotional depletion and accompanying psychosomatic symptoms among volunteer staff of a free clinic in New York City. He called it “burnout,” a term borrowed from the slang of substance abusers.

It has now been established beyond a shadow of a doubt that burnout is a serious issue facing physicians across specialties, albeit some more intensely than others. But with the constant barrage of stories published on an almost daily basis, along with studies and surveys, it begs the question: Are physicians getting tired of hearing about burnout? In other words, are they getting “burned out” about burnout?

Some have suggested that the focus should be more on tackling burnout and instituting viable solutions rather than rehashing the problem.

There haven’t been studies or surveys on this question, but several experts have offered their opinion.

Jonathan Fisher, MD, a cardiologist and organizational well-being and resiliency leader at Novant Health, Charlotte, N.C., cautioned that he hesitates to speak about what physicians in general believe. “We are a diverse group of nearly 1 million in the United States alone,” he said.

But he noted that there is a specific phenomenon among burned-out health care providers who are “burned out on burnout.”

“Essentially, the underlying thought is ‘talk is cheap and we want action,’” said Dr. Fisher, who is chair and co-founder of the Ending Physician Burnout Global Summit that was held in 2021. “This reaction is often a reflection of disheartened physicians’ sense of hopelessness and cynicism that systemic change to improve working conditions will happen in our lifetime.”

Dr. Fisher explained that “typically, anyone suffering – physicians or nonphysicians – cares more about ending the suffering as soon as possible than learning its causes, but to alleviate suffering at its core – including the emotional suffering of burnout – we must understand the many causes.”

“To address both the organizational and individual drivers of burnout requires a keen awareness of the thoughts, fears, and dreams of physicians, health care executives, and all other stakeholders in health care,” he added.

Burnout, of course, is a very real problem. The 2022 Medscape Physician Burnout & Depression Report found that nearly half of all respondents (47%) said they are burned out, which was higher than the prior year. Perhaps not surprisingly, burnout among emergency physicians took the biggest leap, jumping from 43% in 2021 to 60% this year. More than half of critical care physicians (56%) also reported that they were burned out.

The World Health Organization’s International Classification of Diseases (ICD-11) – the official compendium of diseases – has categorized burnout as a “syndrome” that results from “chronic workplace stress that has not been successfully managed.” It is considered to be an occupational phenomenon and is not classified as a medical condition.

But whether or not physicians are burned out on hearing about burnout remains unclear. “I am not sure if physicians are tired of hearing about ‘burnout,’ but I do think that they want to hear about solutions that go beyond just telling them to take better care of themselves,” said Anne Thorndike, MD, MPH, an internal medicine physician at Massachusetts General Hospital and associate professor of medicine at Harvard Medical School, Boston. “There are major systematic factors that contribute to physicians burning out.”
 

Why talk about negative outcomes?

Jonathan Ripp, MD, MPH, however, is familiar with this sentiment. “‘Why do we keep identifying a problem without solutions’ is certainly a sentiment that is being expressed,” he said. “It’s a negative outcome, so why do we keep talking about negative outcomes?”

Dr. Ripp, who is a professor of medicine, medical education, and geriatrics and palliative medicine; the senior associate dean for well-being and resilience; and chief wellness officer at Icahn School of Medicine at Mount Sinai, New York, is also a well-known expert and researcher in burnout and physician well-being.

He noted that burnout was one of the first “tools” used as a metric to measure well-being, but it is a negative measurement. “It’s been around a long time, so it has a lot of evidence,” said Dr. Ripp. “But that said, there are other ways of measuring well-being without a negative association, and ways of measuring meaning in work – fulfillment and satisfaction, and so on. It should be balanced.”

But for the average physician not familiar with the long legacy of research, they may be frustrated by this situation. “Then they ask, ‘Why are you just showing me more of this instead of doing something about it?’ but we are actually doing something about it,” said Dr. Ripp.

There are many efforts underway, he explained, but it’s a challenging and complex issue. “There are numerous drivers impacting the well-being of any given segment within the health care workforce,” he said. “It will also vary by discipline and location, and there are also a host of individual factors that may have very little to do with the work environment. There are some very well-established efforts for an organizational approach, but it remains to be seen which is the most effective.”

But in broad strokes, he continued, it’s about tackling the system and not about making an individual more resilient. “Individuals that do engage in activities that improve resilience do better, but that’s not what this is about – it’s not going to solve the problem,” said Dr. Ripp. “Those of us like myself, who are working in this space, are trying to promote a culture of well-being – at the system level.”

The question is how to enable the workforce to do their best work in an efficient way so that the balance of their activities are not the meaningless aspects. “And instead, shoot that balance to the meaningful aspects of work,” he added. “There are enormous challenges, but even though we are working on solutions, I can see how the individual may not see that – they may say, ‘Stop telling me to be resilient, stop telling me there’s a problem,’ but we’re working on it.”
 

Moving medicine forward

James Jerzak, MD, a family physician in Green Bay, Wisc., and physician lead at Bellin Health, noted that “it seems to me that doctors aren’t burned out talking about burnout, but they are burned out hearing that the solution to burnout is simply for them to become more resilient,” he said. “In actuality, the path to dealing with this huge problem is to make meaningful systemic changes in how medicine is practiced.”

He reiterated that medical care has become increasingly complex, with the aging of the population; the increasing incidence of chronic diseases, such as diabetes; the challenges with the increasing cost of care, higher copays, and lack of health insurance for a large portion of the country; and general incivility toward health care workers that was exacerbated by the pandemic.

“This has all led to significantly increased stress levels for medical workers,” he said. “Couple all of that with the increased work involved in meeting the demands of the electronic health record, and it is clear that the current situation is unsustainable.”

In his own health care system, moving medicine forward has meant advancing team-based care, which translates to expanding teams to include adequate support for physicians. This strategy addressed problems in health care delivery, part of which is burnout.

“In many systems practicing advanced team-based care, the ancillary staff – medical assistants, LPNs, and RNs – play an enhanced role in the patient visit and perform functions such as quality care gap closure, medication review and refill pending, pending orders, and helping with documentation,” he said. “Although the current health care workforce shortages has created challenges, there are a lot of innovative approaches being tried [that are] aimed at providing solutions.”

The second key factor is for systems is to develop robust support for their providers with a broad range of team members, such as case managers, clinical pharmacists, diabetic educators, care coordinators, and others. “The day has passed where individual physicians can effectivity manage all of the complexities of care, especially since there are so many nonclinical factors affecting care,” said Dr. Jerzak.

“The recent focus on the social determinants of health and health equity underlies the fact that it truly takes a team of health care professionals working together to provide optimal care for patients,” he said.

Dr. Thorndike, who mentors premedical and medical trainees, has pointed out that burnout begins way before an individual enters the workplace as a doctor. Burnout begins in the earliest stages of medical practice, with the application process to medical school. The admissions process extends over a 12-month period, causing a great deal of “toxic stress.”

One study found that, compared with non-premedical students, premedical students had greater depression severity and emotional exhaustion.

“The current system of medical school admissions ignores the toll that the lengthy and emotionally exhausting process takes on aspiring physicians,” she said. “This is just one example of many in training and health care that requires physicians to set aside their own lives to achieve their goals and to provide the best possible care to others.”

A version of this article first appeared on Medscape.com.

There is a feeling of exhaustion, being unable to shake a lingering cold, suffering from frequent headaches and gastrointestinal disturbances, sleeplessness and shortness of breath ...

That was how burnout was described by clinical psychologist Herbert Freudenberger, PhD, who first used the phrase in a paper back in 1974, after observing the emotional depletion and accompanying psychosomatic symptoms among volunteer staff of a free clinic in New York City. He called it “burnout,” a term borrowed from the slang of substance abusers.

It has now been established beyond a shadow of a doubt that burnout is a serious issue facing physicians across specialties, albeit some more intensely than others. But with the constant barrage of stories published on an almost daily basis, along with studies and surveys, it begs the question: Are physicians getting tired of hearing about burnout? In other words, are they getting “burned out” about burnout?

Some have suggested that the focus should be more on tackling burnout and instituting viable solutions rather than rehashing the problem.

There haven’t been studies or surveys on this question, but several experts have offered their opinion.

Jonathan Fisher, MD, a cardiologist and organizational well-being and resiliency leader at Novant Health, Charlotte, N.C., cautioned that he hesitates to speak about what physicians in general believe. “We are a diverse group of nearly 1 million in the United States alone,” he said.

But he noted that there is a specific phenomenon among burned-out health care providers who are “burned out on burnout.”

“Essentially, the underlying thought is ‘talk is cheap and we want action,’” said Dr. Fisher, who is chair and co-founder of the Ending Physician Burnout Global Summit that was held in 2021. “This reaction is often a reflection of disheartened physicians’ sense of hopelessness and cynicism that systemic change to improve working conditions will happen in our lifetime.”

Dr. Fisher explained that “typically, anyone suffering – physicians or nonphysicians – cares more about ending the suffering as soon as possible than learning its causes, but to alleviate suffering at its core – including the emotional suffering of burnout – we must understand the many causes.”

“To address both the organizational and individual drivers of burnout requires a keen awareness of the thoughts, fears, and dreams of physicians, health care executives, and all other stakeholders in health care,” he added.

Burnout, of course, is a very real problem. The 2022 Medscape Physician Burnout & Depression Report found that nearly half of all respondents (47%) said they are burned out, which was higher than the prior year. Perhaps not surprisingly, burnout among emergency physicians took the biggest leap, jumping from 43% in 2021 to 60% this year. More than half of critical care physicians (56%) also reported that they were burned out.

The World Health Organization’s International Classification of Diseases (ICD-11) – the official compendium of diseases – has categorized burnout as a “syndrome” that results from “chronic workplace stress that has not been successfully managed.” It is considered to be an occupational phenomenon and is not classified as a medical condition.

But whether or not physicians are burned out on hearing about burnout remains unclear. “I am not sure if physicians are tired of hearing about ‘burnout,’ but I do think that they want to hear about solutions that go beyond just telling them to take better care of themselves,” said Anne Thorndike, MD, MPH, an internal medicine physician at Massachusetts General Hospital and associate professor of medicine at Harvard Medical School, Boston. “There are major systematic factors that contribute to physicians burning out.”
 

Why talk about negative outcomes?

Jonathan Ripp, MD, MPH, however, is familiar with this sentiment. “‘Why do we keep identifying a problem without solutions’ is certainly a sentiment that is being expressed,” he said. “It’s a negative outcome, so why do we keep talking about negative outcomes?”

Dr. Ripp, who is a professor of medicine, medical education, and geriatrics and palliative medicine; the senior associate dean for well-being and resilience; and chief wellness officer at Icahn School of Medicine at Mount Sinai, New York, is also a well-known expert and researcher in burnout and physician well-being.

He noted that burnout was one of the first “tools” used as a metric to measure well-being, but it is a negative measurement. “It’s been around a long time, so it has a lot of evidence,” said Dr. Ripp. “But that said, there are other ways of measuring well-being without a negative association, and ways of measuring meaning in work – fulfillment and satisfaction, and so on. It should be balanced.”

But for the average physician not familiar with the long legacy of research, they may be frustrated by this situation. “Then they ask, ‘Why are you just showing me more of this instead of doing something about it?’ but we are actually doing something about it,” said Dr. Ripp.

There are many efforts underway, he explained, but it’s a challenging and complex issue. “There are numerous drivers impacting the well-being of any given segment within the health care workforce,” he said. “It will also vary by discipline and location, and there are also a host of individual factors that may have very little to do with the work environment. There are some very well-established efforts for an organizational approach, but it remains to be seen which is the most effective.”

But in broad strokes, he continued, it’s about tackling the system and not about making an individual more resilient. “Individuals that do engage in activities that improve resilience do better, but that’s not what this is about – it’s not going to solve the problem,” said Dr. Ripp. “Those of us like myself, who are working in this space, are trying to promote a culture of well-being – at the system level.”

The question is how to enable the workforce to do their best work in an efficient way so that the balance of their activities are not the meaningless aspects. “And instead, shoot that balance to the meaningful aspects of work,” he added. “There are enormous challenges, but even though we are working on solutions, I can see how the individual may not see that – they may say, ‘Stop telling me to be resilient, stop telling me there’s a problem,’ but we’re working on it.”
 

Moving medicine forward

James Jerzak, MD, a family physician in Green Bay, Wisc., and physician lead at Bellin Health, noted that “it seems to me that doctors aren’t burned out talking about burnout, but they are burned out hearing that the solution to burnout is simply for them to become more resilient,” he said. “In actuality, the path to dealing with this huge problem is to make meaningful systemic changes in how medicine is practiced.”

He reiterated that medical care has become increasingly complex, with the aging of the population; the increasing incidence of chronic diseases, such as diabetes; the challenges with the increasing cost of care, higher copays, and lack of health insurance for a large portion of the country; and general incivility toward health care workers that was exacerbated by the pandemic.

“This has all led to significantly increased stress levels for medical workers,” he said. “Couple all of that with the increased work involved in meeting the demands of the electronic health record, and it is clear that the current situation is unsustainable.”

In his own health care system, moving medicine forward has meant advancing team-based care, which translates to expanding teams to include adequate support for physicians. This strategy addressed problems in health care delivery, part of which is burnout.

“In many systems practicing advanced team-based care, the ancillary staff – medical assistants, LPNs, and RNs – play an enhanced role in the patient visit and perform functions such as quality care gap closure, medication review and refill pending, pending orders, and helping with documentation,” he said. “Although the current health care workforce shortages has created challenges, there are a lot of innovative approaches being tried [that are] aimed at providing solutions.”

The second key factor is for systems is to develop robust support for their providers with a broad range of team members, such as case managers, clinical pharmacists, diabetic educators, care coordinators, and others. “The day has passed where individual physicians can effectivity manage all of the complexities of care, especially since there are so many nonclinical factors affecting care,” said Dr. Jerzak.

“The recent focus on the social determinants of health and health equity underlies the fact that it truly takes a team of health care professionals working together to provide optimal care for patients,” he said.

Dr. Thorndike, who mentors premedical and medical trainees, has pointed out that burnout begins way before an individual enters the workplace as a doctor. Burnout begins in the earliest stages of medical practice, with the application process to medical school. The admissions process extends over a 12-month period, causing a great deal of “toxic stress.”

One study found that, compared with non-premedical students, premedical students had greater depression severity and emotional exhaustion.

“The current system of medical school admissions ignores the toll that the lengthy and emotionally exhausting process takes on aspiring physicians,” she said. “This is just one example of many in training and health care that requires physicians to set aside their own lives to achieve their goals and to provide the best possible care to others.”

A version of this article first appeared on Medscape.com.

There is a feeling of exhaustion, being unable to shake a lingering cold, suffering from frequent headaches and gastrointestinal disturbances, sleeplessness and shortness of breath ...

That was how burnout was described by clinical psychologist Herbert Freudenberger, PhD, who first used the phrase in a paper back in 1974, after observing the emotional depletion and accompanying psychosomatic symptoms among volunteer staff of a free clinic in New York City. He called it “burnout,” a term borrowed from the slang of substance abusers.

It has now been established beyond a shadow of a doubt that burnout is a serious issue facing physicians across specialties, albeit some more intensely than others. But with the constant barrage of stories published on an almost daily basis, along with studies and surveys, it begs the question: Are physicians getting tired of hearing about burnout? In other words, are they getting “burned out” about burnout?

Some have suggested that the focus should be more on tackling burnout and instituting viable solutions rather than rehashing the problem.

There haven’t been studies or surveys on this question, but several experts have offered their opinion.

Jonathan Fisher, MD, a cardiologist and organizational well-being and resiliency leader at Novant Health, Charlotte, N.C., cautioned that he hesitates to speak about what physicians in general believe. “We are a diverse group of nearly 1 million in the United States alone,” he said.

But he noted that there is a specific phenomenon among burned-out health care providers who are “burned out on burnout.”

“Essentially, the underlying thought is ‘talk is cheap and we want action,’” said Dr. Fisher, who is chair and co-founder of the Ending Physician Burnout Global Summit that was held in 2021. “This reaction is often a reflection of disheartened physicians’ sense of hopelessness and cynicism that systemic change to improve working conditions will happen in our lifetime.”

Dr. Fisher explained that “typically, anyone suffering – physicians or nonphysicians – cares more about ending the suffering as soon as possible than learning its causes, but to alleviate suffering at its core – including the emotional suffering of burnout – we must understand the many causes.”

“To address both the organizational and individual drivers of burnout requires a keen awareness of the thoughts, fears, and dreams of physicians, health care executives, and all other stakeholders in health care,” he added.

Burnout, of course, is a very real problem. The 2022 Medscape Physician Burnout & Depression Report found that nearly half of all respondents (47%) said they are burned out, which was higher than the prior year. Perhaps not surprisingly, burnout among emergency physicians took the biggest leap, jumping from 43% in 2021 to 60% this year. More than half of critical care physicians (56%) also reported that they were burned out.

The World Health Organization’s International Classification of Diseases (ICD-11) – the official compendium of diseases – has categorized burnout as a “syndrome” that results from “chronic workplace stress that has not been successfully managed.” It is considered to be an occupational phenomenon and is not classified as a medical condition.

But whether or not physicians are burned out on hearing about burnout remains unclear. “I am not sure if physicians are tired of hearing about ‘burnout,’ but I do think that they want to hear about solutions that go beyond just telling them to take better care of themselves,” said Anne Thorndike, MD, MPH, an internal medicine physician at Massachusetts General Hospital and associate professor of medicine at Harvard Medical School, Boston. “There are major systematic factors that contribute to physicians burning out.”
 

Why talk about negative outcomes?

Jonathan Ripp, MD, MPH, however, is familiar with this sentiment. “‘Why do we keep identifying a problem without solutions’ is certainly a sentiment that is being expressed,” he said. “It’s a negative outcome, so why do we keep talking about negative outcomes?”

Dr. Ripp, who is a professor of medicine, medical education, and geriatrics and palliative medicine; the senior associate dean for well-being and resilience; and chief wellness officer at Icahn School of Medicine at Mount Sinai, New York, is also a well-known expert and researcher in burnout and physician well-being.

He noted that burnout was one of the first “tools” used as a metric to measure well-being, but it is a negative measurement. “It’s been around a long time, so it has a lot of evidence,” said Dr. Ripp. “But that said, there are other ways of measuring well-being without a negative association, and ways of measuring meaning in work – fulfillment and satisfaction, and so on. It should be balanced.”

But for the average physician not familiar with the long legacy of research, they may be frustrated by this situation. “Then they ask, ‘Why are you just showing me more of this instead of doing something about it?’ but we are actually doing something about it,” said Dr. Ripp.

There are many efforts underway, he explained, but it’s a challenging and complex issue. “There are numerous drivers impacting the well-being of any given segment within the health care workforce,” he said. “It will also vary by discipline and location, and there are also a host of individual factors that may have very little to do with the work environment. There are some very well-established efforts for an organizational approach, but it remains to be seen which is the most effective.”

But in broad strokes, he continued, it’s about tackling the system and not about making an individual more resilient. “Individuals that do engage in activities that improve resilience do better, but that’s not what this is about – it’s not going to solve the problem,” said Dr. Ripp. “Those of us like myself, who are working in this space, are trying to promote a culture of well-being – at the system level.”

The question is how to enable the workforce to do their best work in an efficient way so that the balance of their activities are not the meaningless aspects. “And instead, shoot that balance to the meaningful aspects of work,” he added. “There are enormous challenges, but even though we are working on solutions, I can see how the individual may not see that – they may say, ‘Stop telling me to be resilient, stop telling me there’s a problem,’ but we’re working on it.”
 

Moving medicine forward

James Jerzak, MD, a family physician in Green Bay, Wisc., and physician lead at Bellin Health, noted that “it seems to me that doctors aren’t burned out talking about burnout, but they are burned out hearing that the solution to burnout is simply for them to become more resilient,” he said. “In actuality, the path to dealing with this huge problem is to make meaningful systemic changes in how medicine is practiced.”

He reiterated that medical care has become increasingly complex, with the aging of the population; the increasing incidence of chronic diseases, such as diabetes; the challenges with the increasing cost of care, higher copays, and lack of health insurance for a large portion of the country; and general incivility toward health care workers that was exacerbated by the pandemic.

“This has all led to significantly increased stress levels for medical workers,” he said. “Couple all of that with the increased work involved in meeting the demands of the electronic health record, and it is clear that the current situation is unsustainable.”

In his own health care system, moving medicine forward has meant advancing team-based care, which translates to expanding teams to include adequate support for physicians. This strategy addressed problems in health care delivery, part of which is burnout.

“In many systems practicing advanced team-based care, the ancillary staff – medical assistants, LPNs, and RNs – play an enhanced role in the patient visit and perform functions such as quality care gap closure, medication review and refill pending, pending orders, and helping with documentation,” he said. “Although the current health care workforce shortages has created challenges, there are a lot of innovative approaches being tried [that are] aimed at providing solutions.”

The second key factor is for systems is to develop robust support for their providers with a broad range of team members, such as case managers, clinical pharmacists, diabetic educators, care coordinators, and others. “The day has passed where individual physicians can effectivity manage all of the complexities of care, especially since there are so many nonclinical factors affecting care,” said Dr. Jerzak.

“The recent focus on the social determinants of health and health equity underlies the fact that it truly takes a team of health care professionals working together to provide optimal care for patients,” he said.

Dr. Thorndike, who mentors premedical and medical trainees, has pointed out that burnout begins way before an individual enters the workplace as a doctor. Burnout begins in the earliest stages of medical practice, with the application process to medical school. The admissions process extends over a 12-month period, causing a great deal of “toxic stress.”

One study found that, compared with non-premedical students, premedical students had greater depression severity and emotional exhaustion.

“The current system of medical school admissions ignores the toll that the lengthy and emotionally exhausting process takes on aspiring physicians,” she said. “This is just one example of many in training and health care that requires physicians to set aside their own lives to achieve their goals and to provide the best possible care to others.”

A version of this article first appeared on Medscape.com.

From Sharp Memorial Hospital, San Diego, CA (Drs. Poremba, Dehner, Perreiter, Semma, and Mills), Sharp Rees-Stealy Medical Group, San Diego, CA (Dr. Sakoulas), and Collaborative to Halt Antibiotic-Resistant Microbes (CHARM), Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, CA (Dr. Sakoulas).

Abstract

Objective: To compare the costs of hospitalization of patients with moderate-to-severe COVID-19 who received intravenous immunoglobulin (IVIG) with those of patients of similar comorbidity and illness severity who did not.

Design: Analysis 1 was a case-control study of 10 nonventilated, moderately to severely hypoxic patients with COVID-19 who received IVIG (Privigen [CSL Behring]) matched 1:2 with 20 control patients of similar age, body mass index, degree of hypoxemia, and comorbidities. Analysis 2 consisted of patients enrolled in a previously published, randomized, open-label prospective study of 14 patients with COVID-19 receiving standard of care vs 13 patients who received standard of care plus IVIG (Octagam 10% [Octapharma]).

Setting and participants: Patients with COVID-19 with moderate-to-severe hypoxemia hospitalized at a single site located in San Diego, California.

Measurements: Direct cost of hospitalization.

Results: In the first (case-control) population, mean total direct costs, including IVIG, for the treatment group were $21,982 per IVIG-treated case vs $42,431 per case for matched non-IVIG-receiving controls, representing a net cost reduction of $20,449 (48%) per case. For the second (randomized) group, mean total direct costs, including IVIG, for the treatment group were $28,268 per case vs $62,707 per case for untreated controls, representing a net cost reduction of $34,439 (55%) per case. Of the patients who did not receive IVIG, 24% had hospital costs exceeding $80,000; none of the IVIG-treated patients had costs exceeding this amount (P = .016, Fisher exact test).

Conclusion: If allocated early to the appropriate patient type (moderate-to-severe illness without end-organ comorbidities and age <70 years), IVIG can significantly reduce hospital costs in COVID-19 care. More important, in our study it reduced the demand for scarce critical care resources during the COVID-19 pandemic.

Keywords: IVIG, SARS-CoV-2, cost saving, direct hospital costs.

Intravenous immunoglobulin (IVIG) has been available in most hospitals for 4 decades, with broad therapeutic applications in the treatment of Kawasaki disease and a variety of inflammatory, infectious, autoimmune, and viral diseases, via multifactorial mechanisms of immune modulation.¹ Reports of COVID-19−associated multisystem inflammatory syndrome in adults and children have supported the use of IVIG in treatment.^2,3 Previous studies of IVIG treatment for COVID-19 have produced mixed results. Although retrospective studies have largely been positive,^4-8 prospective clinical trials have been mixed, with some favorable results^9-11 and another, more recent study showing no benefit.¹² However, there is still considerable debate regarding whether some subgroups of patients with COVID-19 may benefit from IVIG; the studies that support this argument, however, have been diluted by broad clinical trials that lack granularity among the heterogeneity of patient characteristics and the timing of IVIG administration.^13,14 One study suggests that patients with COVID-19 who may be particularly poised to benefit from IVIG are those who are younger, have fewer comorbidities, and are treated early.⁸

At our institution, we selectively utilized IVIG to treat patients within 48 hours of rapidly increasing oxygen requirements due to COVID-19, targeting those younger than 70 years, with no previous irreversible end-organ damage, no significant comorbidities (renal failure, heart failure, dementia, active cancer malignancies), and no active treatment for cancer. We analyzed the costs of care of these IVIG (Privigen) recipients and compared them to costs for patients with COVID-19 matched by comorbidities, age, and illness severity who did not receive IVIG. To look for consistency, we examined the cost of care of COVID-19 patients who received IVIG (Octagam) as compared to controls from a previously published pilot trial.¹⁰

Methods

Setting and Treatment

All patients in this study were hospitalized at a single site located in San Diego, California. Treatment patients in both cohorts received IVIG 0.5 g/kg adjusted for body weight daily for 3 consecutive days.

Patient Cohort #1: Retrospective Case-Control Trial

Intravenous immunoglobulin (Privigen 10%, CSL Behring) was utilized off-label to treat moderately to severely ill non-intensive care unit (ICU) patients with COVID-19 requiring ≥3 L of oxygen by nasal cannula who were not mechanically ventilated but were considered at high risk for respiratory failure. Preset exclusion criteria for off-label use of IVIG in the treatment of COVID-19 were age >70 years, active malignancy, organ transplant recipient, renal failure, heart failure, or dementia. Controls were obtained from a list of all admitted patients with COVID-19, matched to cases 2:1 on the basis of age (±10 years), body mass index (±1), gender, comorbidities present at admission (eg, hypertension, diabetes mellitus, lung disease, or history of tobacco use), and maximum oxygen requirements within the first 48 hours of admission. In situations where more than 2 potential matched controls were identified for a patient, the 2 controls closest in age to the treatment patient were selected. One IVIG patient was excluded because only 1 matched-age control could be found. Pregnant patients who otherwise fulfilled the criteria for IVIG administration were also excluded from this analysis.

Patient Cohort #2: Prospective, Randomized, Open-Label Trial

Use of IVIG (Octagam 10%, Octapharma) in COVID-19 was studied in a previously published, prospective, open-label randomized trial.¹⁰ This pilot trial included 16 IVIG-treated patients and 17 control patients, of which 13 and 14 patients, respectively, had hospital cost data available for analysis.¹⁰ Most notably, COVID-19 patients in this study were required to have ≥4 L of oxygen via nasal cannula to maintain arterial oxygen saturationof ≤96%.

Outcomes

Cost data were independently obtained from our finance team, which provided us with the total direct cost and the total pharmaceutical cost associated with each admission. We also compared total length of stay (LOS) and ICU LOS between treatment arms, as these were presumed to be the major drivers of cost difference.

Statistics

Nonparametric comparisons of medians were performed with the Mann-Whitney U test. Comparison of means was done by Student t test. Categorical data were analyzed by Fisher exact test.

This analysis was initiated as an internal quality assessment. It received approval from the Sharp Healthcare Institutional Review Board ([email protected]), and was granted a waiver of subject authorization and consent given the retrospective nature of the study.

Results

Case-Control Analysis

A total of 10 hypoxic patients with COVID-19 received Privigen IVIG outside of clinical trial settings. None of the patients was vaccinated against SARS-CoV-2, as hospitalization occurred prior to vaccine availability. In addition, the original SARS-CoV-2 strain was circulating while these patients were hospitalized, preceding subsequent emerging variants. Oxygen requirements within the first 48 hours ranged from 3 L via nasal cannula to requiring bi-level positive pressure airway therapy with 100% oxygen; median age was 56 years and median Charlson comorbidity index was 1. These 10 patients were each matched to 2 control patients hospitalized during a comparable time period and who, based on oxygen requirements, did not receive IVIG. The 20 control patients had a median age of 58.5 years and a Charlson comorbidity index of 1 (Table 1). Rates of comorbidities, such as hypertension, diabetes mellitus, and obesity, were identical in the 2 groups. None of the patients in either group died during the index hospitalization. Fewer control patients received glucocorticoids, which was reflective of lower illness severity/degree of hypoxia in some controls.

Health care utilization in terms of costs and hospital LOS between the 2 groups are shown in Table 2. The mean total direct hospital cost per case, including IVIG and other drug costs, for the 10 IVIG-treated COVID-19 patients was $21,982 vs $42,431 for the matched controls, a reduction of $20,449 (48%) per case (P = .6187) with IVIG. This difference was heavily driven by 4 control patients (20%) with hospital costs >$80,000, marked by need for ICU transfer, mechanical ventilation during admission, and longer hospital stays. This reduction in progression to mechanical ventilation was consistent with our previously published, open-label, randomized prospective IVIG study, the financial assessment of which is reviewed below. While total direct costs were lower in the treatment arm, the mean drug cost for the treatment arm was $3122 greater than the mean drug cost in the control arm (P = .001622), consistent with the high cost of IVIG therapy (Table 2).

LOS information was obtained, as this was thought to be a primary driver of direct costs. The average LOS in the IVIG arm was 8.4 days, and the average LOS in the control arm was 13.6 days (P = NS). The average ICU LOS in the IVIG arm was 0 days, while the average ICU LOS in the control arm was 5.3 days (P = .04). As with the differences in cost, the differences in LOS were primarily driven by the 4 outlier cases in our control arm, who each had a LOS >25 days, as well as an ICU LOS >20 days.

Randomized, Open-Label, Patient Cohort Analysis

Patient characteristics, LOS, and rates of mechanical ventilation for the IVIG and control patients were previously published and showed a reduction in mechanical ventilation and hospital LOS with IVIG treatment.¹⁰ In this group of patients, 1 patient treated with IVIG (6%) and 3 patients not treated with IVIG (18%) died. To determine the consistency of these results from the case-control patients with a set of patients obtained from clinical trial randomization, we examined the health care costs of patients from the prior study.¹⁰ As with the case-control group, patients in this portion of the analysis were hospitalized before vaccines were available and prior to any identified variants.

Comparing the hospital cost of the IVIG-treated patients to the control patients from this trial revealed results similar to the matched case-control analysis discussed earlier. Average total direct cost per case, including IVIG, for the IVIG treatment group was $28,268, vs $62,707 per case for non-IVIG controls. This represented a net cost reduction of $34,439 (55%) per case, very similar to that of the prior cohort.

IVIG Reduces Costly Outlier Cases

The case-control and randomized trial groups, yielding a combined 23 IVIG and 34 control patients, showed a median cost per case of $22,578 (range $10,115-$70,929) and $22,645 (range $4723-$279,797) for the IVIG and control groups, respectively. Cases with a cost >$80,000 were 0/23 (0%) vs 8/34 (24%) in the IVIG and control groups, respectively (P = .016, Fisher exact test).

Improving care while simultaneously keeping care costs below reimbursement payment levels received from third-party payers is paramount to the financial survival of health care systems. IVIG appears to do this by reducing the number of patients with COVID-19 who progress to ICU care. We compared the costs of care of our combined case-control and randomized trial cohorts to published data on average reimbursements hospitals receive for COVID-19 care from Medicaid, Medicare, and private insurance (Figure).¹⁵ IVIG demonstrated a reduction in cases where costs exceed reimbursement. Indeed, a comparison of net revenue per case of the case-control group showed significantly higher revenue for the IVIG group compared to controls ($52,704 vs $34,712, P = .0338, Table 2).

Discussion

As reflected in at least 1 other study,¹⁶ our hospital had been successfully utilizing IVIG in the treatment of viral acute respiratory distress syndrome (ARDS) prior to COVID-19. Therefore, we moved quickly to perform a randomized, open-label pilot study of IVIG (Octagam 10%) in COVID-19, and noted significant clinical benefit that might translate into hospital cost savings.¹⁰ Over the course of the pandemic, evidence has accumulated that IVIG may play an important role in COVID-19 therapeutics, as summarized in a recent review.¹⁷ However, despite promising but inconsistent results, the relatively high acquisition costs of IVIG raised questions as to its pharmacoeconomic value, particularly with such a high volume of COVID-19 patients with hypoxia, in light of limited clinical data.

COVID-19 therapeutics data can be categorized into either high-quality trials showing marginal benefit for some agents or low-quality trials showing greater benefit for other agents, with IVIG studies falling into the latter category.¹⁸ This phenomenon may speak to the pathophysiological heterogeneity of the COVID-19 patient population. High-quality trials enrolling broad patient types lack the granularity to capture and single out relevant patient subsets who would derive maximal therapeutic benefit, with those subsets diluted by other patient types for which no benefit is seen. Meanwhile, the more granular low-quality trials are criticized as underpowered and lacking in translatability to practice.

Positive results from our pilot trial allowed the use of IVIG (Privigen) off-label in hospitalized COVID-19 patients restricted to specific criteria. Patients had to be moderately to severely ill, requiring >3 L of oxygen via nasal cannula; show high risk of clinical deterioration based on respiratory rate and decline in respiratory status; and have underlying comorbidities (such as hypertension, obesity, or diabetes mellitus). However, older patients (>age 70 years) and those with underlying comorbidities marked by organ failure (such as heart failure, renal failure, dementia, or receipt of organ transplant) and active malignancy were excluded, as their clinical outcome in COVID-19 may be considered less modifiable by therapeutics, while simultaneously carrying potentially a higher risk of adverse events from IVIG (volume overload, renal failure). These exclusions are reflected in the overall low Charlson comorbidity index (mean of 1) of the patients in the case-control study arm. As anticipated, we found a net cost reduction: $20,449 (48%) per case among the 10 IVIG-treated patients compared to the 20 matched controls.

We then went back to the patients from the randomized prospective trial and compared costs for the 13 of 16 IVIG patients and 14 of 17 of the control patients for whom data were available. Among untreated controls, we found a net cost reduction of $34,439 (55%) per case. The higher costs seen in the randomized patient cohort compared to the latter case-control group may be due to a combination of the fact that the treated patients had slightly higher comorbidity indices than the case-control group (median Charlson comorbidity index of 2 in both groups) and the fact that they were treated earlier in the pandemic (May/June 2020), as opposed to the case-control group patients, who were treated in November/December 2020.

It was notable that the cost savings across both groups were derived largely from the reduction in the approximately 20% to 25% of control patients who went on to critical illness, including mechanical ventilation, extracorporeal membrane oxygenation (ECMO), and prolonged ICU stays. Indeed, 8 of 34 of the control patients—but none of the 23 IVIG-treated patients—generated hospital costs in excess of $80,000, a difference that was statistically significant even for such a small sample size. Therefore, reducing these very costly outlier events translated into net savings across the board.

In addition to lowering costs, reducing progression to critical illness is extremely important during heavy waves of COVID-19, when the sheer volume of patients results in severe strain due to the relative scarcity of ICU beds, mechanical ventilators, and ECMO. Therefore, reducing the need for these resources would have a vital role that cannot be measured economically.

The major limitations of this study include the small sample size and the potential lack of generalizability of these results to all hospital centers and treating providers. Our group has considerable experience in IVIG utilization in COVID-19 and, as a result, has identified a “sweet spot,” where benefits were seen clinically and economically. However, it remains to be determined whether IVIG will benefit patients with greater illness severity, such as those in the ICU, on mechanical ventilation, or ECMO. Furthermore, while a significant morbidity and mortality burden of COVID-19 rests in extremely elderly patients and those with end-organ comorbidities such as renal failure and heart failure, it is uncertain whether their COVID-19 adverse outcomes can be improved with IVIG or other therapies. We believe such patients may limit the pharmacoeconomic value of IVIG due to their generally poorer prognosis, regardless of intervention. On the other hand, COVID-19 patients who are not that severely ill, with minimal to no hypoxia, generally will do well regardless of therapy. Therefore, IVIG intervention may be an unnecessary treatment expense. Evidence for this was suggested in our pilot trial¹⁰ and supported in a recent meta-analysis of IVIG therapy in COVID-19.¹⁹

Several other therapeutic options with high acquisition costs have seen an increase in use during the COVID-19 pandemic despite relatively lukewarm data. Remdesivir, the first drug found to have a beneficial effect on hospitalized patients with COVID-19, is priced at $3120 for a complete 5-day treatment course in the United States. This was in line with initial pricing models from the Institute for Clinical and Economic Review (ICER) in May 2020, assuming a mortality benefit with remdesivir use. After the SOLIDARITY trial was published, which showed no mortality benefit associated with remdesivir, ICER updated their pricing models in June 2020 and released a statement that the price of remdesivir was too high to align with demonstrated benefits.^20,21 More recent data demonstrate that remdesivir may be beneficial, but only if administered to patients with fewer than 6 days of symptoms.²² However, only a minority of patients present to the hospital early enough in their illness for remdesivir to be beneficial.²²

Tocilizumab, an interleukin-6 inhibitor, saw an increase in use during the pandemic. An 800-mg treatment course for COVID-19 costs $3584. The efficacy of this treatment option came into question after the COVACTA trial failed to show a difference in clinical status or mortality in COVID-19 patients who received tocilizumab vs placebo.^23,24 A more recent study pointed to a survival benefit of tocilizumab in COVID-19, driven by a very large sample size (>4000), yielding statistically significant, but perhaps clinically less significant, effects on survival.²⁵ This latter study points to the extremely large sample sizes required to capture statistically significant benefits of expensive interventions in COVID-19, which our data demonstrate may benefit only a fraction of patients (20%-25% of patients in the case of IVIG). A more granular clinical assessment of these other interventions is needed to be able to capture the patient subtypes where tocilizumab, remdesivir, and other therapies will be cost effective in the treatment of COVID-19 or other virally mediated cases of ARDS.

Conclusion

While IVIG has a high acquisition cost, the drug’s use in hypoxic COVID-19 patients resulted in reduced costs per COVID-19 case of approximately 50% and use of less critical care resources. The difference was consistent between 2 cohorts (randomized trial vs off-label use in prespecified COVID-19 patient types), IVIG products used (Octagam 10% and Privigen), and time period in the pandemic (waves 1 and 2 in May/June 2020 vs wave 3 in November/December 2020), thereby adjusting for potential differences in circulating viral strains. Furthermore, patients from both groups predated SARS-CoV-2 vaccine availability and major circulating viral variants (eg, delta, omicron), thereby eliminating confounding on outcomes posed by these factors. Control patients’ higher costs of care were driven largely by the approximately 25% of patients who required costly hospital critical care resources, a group mitigated by IVIG. When allocated to the appropriate patient type (patients with moderate-to-severe but not critical illness, <age 70 without preexisting comorbidities of end-organ failure or active cancer), IVIG can reduce hospital costs for COVID-19 care. Identification of specific patient populations where IVIG has the most anticipated benefits in viral illness is needed.

Corresponding author: George Sakoulas, MD, Sharp Rees-Stealy Medical Group, 2020 Genesee Avenue, 2nd Floor, San Diego, CA 92123; [email protected]

Disclosures: Dr Sakoulas has worked as a consultant for Abbvie, Paratek, and Octapharma, has served as a speaker for Abbvie and Paratek, and has received research funding from Octapharma. The other authors did not report any disclosures.

From Sharp Memorial Hospital, San Diego, CA (Drs. Poremba, Dehner, Perreiter, Semma, and Mills), Sharp Rees-Stealy Medical Group, San Diego, CA (Dr. Sakoulas), and Collaborative to Halt Antibiotic-Resistant Microbes (CHARM), Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, CA (Dr. Sakoulas).

Abstract

Objective: To compare the costs of hospitalization of patients with moderate-to-severe COVID-19 who received intravenous immunoglobulin (IVIG) with those of patients of similar comorbidity and illness severity who did not.

Design: Analysis 1 was a case-control study of 10 nonventilated, moderately to severely hypoxic patients with COVID-19 who received IVIG (Privigen [CSL Behring]) matched 1:2 with 20 control patients of similar age, body mass index, degree of hypoxemia, and comorbidities. Analysis 2 consisted of patients enrolled in a previously published, randomized, open-label prospective study of 14 patients with COVID-19 receiving standard of care vs 13 patients who received standard of care plus IVIG (Octagam 10% [Octapharma]).

Setting and participants: Patients with COVID-19 with moderate-to-severe hypoxemia hospitalized at a single site located in San Diego, California.

Measurements: Direct cost of hospitalization.

Results: In the first (case-control) population, mean total direct costs, including IVIG, for the treatment group were $21,982 per IVIG-treated case vs $42,431 per case for matched non-IVIG-receiving controls, representing a net cost reduction of $20,449 (48%) per case. For the second (randomized) group, mean total direct costs, including IVIG, for the treatment group were $28,268 per case vs $62,707 per case for untreated controls, representing a net cost reduction of $34,439 (55%) per case. Of the patients who did not receive IVIG, 24% had hospital costs exceeding $80,000; none of the IVIG-treated patients had costs exceeding this amount (P = .016, Fisher exact test).

Conclusion: If allocated early to the appropriate patient type (moderate-to-severe illness without end-organ comorbidities and age <70 years), IVIG can significantly reduce hospital costs in COVID-19 care. More important, in our study it reduced the demand for scarce critical care resources during the COVID-19 pandemic.

Keywords: IVIG, SARS-CoV-2, cost saving, direct hospital costs.

Intravenous immunoglobulin (IVIG) has been available in most hospitals for 4 decades, with broad therapeutic applications in the treatment of Kawasaki disease and a variety of inflammatory, infectious, autoimmune, and viral diseases, via multifactorial mechanisms of immune modulation.¹ Reports of COVID-19−associated multisystem inflammatory syndrome in adults and children have supported the use of IVIG in treatment.^2,3 Previous studies of IVIG treatment for COVID-19 have produced mixed results. Although retrospective studies have largely been positive,^4-8 prospective clinical trials have been mixed, with some favorable results^9-11 and another, more recent study showing no benefit.¹² However, there is still considerable debate regarding whether some subgroups of patients with COVID-19 may benefit from IVIG; the studies that support this argument, however, have been diluted by broad clinical trials that lack granularity among the heterogeneity of patient characteristics and the timing of IVIG administration.^13,14 One study suggests that patients with COVID-19 who may be particularly poised to benefit from IVIG are those who are younger, have fewer comorbidities, and are treated early.⁸

At our institution, we selectively utilized IVIG to treat patients within 48 hours of rapidly increasing oxygen requirements due to COVID-19, targeting those younger than 70 years, with no previous irreversible end-organ damage, no significant comorbidities (renal failure, heart failure, dementia, active cancer malignancies), and no active treatment for cancer. We analyzed the costs of care of these IVIG (Privigen) recipients and compared them to costs for patients with COVID-19 matched by comorbidities, age, and illness severity who did not receive IVIG. To look for consistency, we examined the cost of care of COVID-19 patients who received IVIG (Octagam) as compared to controls from a previously published pilot trial.¹⁰

Methods

Setting and Treatment

All patients in this study were hospitalized at a single site located in San Diego, California. Treatment patients in both cohorts received IVIG 0.5 g/kg adjusted for body weight daily for 3 consecutive days.

Patient Cohort #1: Retrospective Case-Control Trial

Intravenous immunoglobulin (Privigen 10%, CSL Behring) was utilized off-label to treat moderately to severely ill non-intensive care unit (ICU) patients with COVID-19 requiring ≥3 L of oxygen by nasal cannula who were not mechanically ventilated but were considered at high risk for respiratory failure. Preset exclusion criteria for off-label use of IVIG in the treatment of COVID-19 were age >70 years, active malignancy, organ transplant recipient, renal failure, heart failure, or dementia. Controls were obtained from a list of all admitted patients with COVID-19, matched to cases 2:1 on the basis of age (±10 years), body mass index (±1), gender, comorbidities present at admission (eg, hypertension, diabetes mellitus, lung disease, or history of tobacco use), and maximum oxygen requirements within the first 48 hours of admission. In situations where more than 2 potential matched controls were identified for a patient, the 2 controls closest in age to the treatment patient were selected. One IVIG patient was excluded because only 1 matched-age control could be found. Pregnant patients who otherwise fulfilled the criteria for IVIG administration were also excluded from this analysis.

Patient Cohort #2: Prospective, Randomized, Open-Label Trial

Use of IVIG (Octagam 10%, Octapharma) in COVID-19 was studied in a previously published, prospective, open-label randomized trial.¹⁰ This pilot trial included 16 IVIG-treated patients and 17 control patients, of which 13 and 14 patients, respectively, had hospital cost data available for analysis.¹⁰ Most notably, COVID-19 patients in this study were required to have ≥4 L of oxygen via nasal cannula to maintain arterial oxygen saturationof ≤96%.

Outcomes

Cost data were independently obtained from our finance team, which provided us with the total direct cost and the total pharmaceutical cost associated with each admission. We also compared total length of stay (LOS) and ICU LOS between treatment arms, as these were presumed to be the major drivers of cost difference.

Statistics

Nonparametric comparisons of medians were performed with the Mann-Whitney U test. Comparison of means was done by Student t test. Categorical data were analyzed by Fisher exact test.

This analysis was initiated as an internal quality assessment. It received approval from the Sharp Healthcare Institutional Review Board ([email protected]), and was granted a waiver of subject authorization and consent given the retrospective nature of the study.

Results

Case-Control Analysis

A total of 10 hypoxic patients with COVID-19 received Privigen IVIG outside of clinical trial settings. None of the patients was vaccinated against SARS-CoV-2, as hospitalization occurred prior to vaccine availability. In addition, the original SARS-CoV-2 strain was circulating while these patients were hospitalized, preceding subsequent emerging variants. Oxygen requirements within the first 48 hours ranged from 3 L via nasal cannula to requiring bi-level positive pressure airway therapy with 100% oxygen; median age was 56 years and median Charlson comorbidity index was 1. These 10 patients were each matched to 2 control patients hospitalized during a comparable time period and who, based on oxygen requirements, did not receive IVIG. The 20 control patients had a median age of 58.5 years and a Charlson comorbidity index of 1 (Table 1). Rates of comorbidities, such as hypertension, diabetes mellitus, and obesity, were identical in the 2 groups. None of the patients in either group died during the index hospitalization. Fewer control patients received glucocorticoids, which was reflective of lower illness severity/degree of hypoxia in some controls.

Health care utilization in terms of costs and hospital LOS between the 2 groups are shown in Table 2. The mean total direct hospital cost per case, including IVIG and other drug costs, for the 10 IVIG-treated COVID-19 patients was $21,982 vs $42,431 for the matched controls, a reduction of $20,449 (48%) per case (P = .6187) with IVIG. This difference was heavily driven by 4 control patients (20%) with hospital costs >$80,000, marked by need for ICU transfer, mechanical ventilation during admission, and longer hospital stays. This reduction in progression to mechanical ventilation was consistent with our previously published, open-label, randomized prospective IVIG study, the financial assessment of which is reviewed below. While total direct costs were lower in the treatment arm, the mean drug cost for the treatment arm was $3122 greater than the mean drug cost in the control arm (P = .001622), consistent with the high cost of IVIG therapy (Table 2).

LOS information was obtained, as this was thought to be a primary driver of direct costs. The average LOS in the IVIG arm was 8.4 days, and the average LOS in the control arm was 13.6 days (P = NS). The average ICU LOS in the IVIG arm was 0 days, while the average ICU LOS in the control arm was 5.3 days (P = .04). As with the differences in cost, the differences in LOS were primarily driven by the 4 outlier cases in our control arm, who each had a LOS >25 days, as well as an ICU LOS >20 days.

Randomized, Open-Label, Patient Cohort Analysis

Patient characteristics, LOS, and rates of mechanical ventilation for the IVIG and control patients were previously published and showed a reduction in mechanical ventilation and hospital LOS with IVIG treatment.¹⁰ In this group of patients, 1 patient treated with IVIG (6%) and 3 patients not treated with IVIG (18%) died. To determine the consistency of these results from the case-control patients with a set of patients obtained from clinical trial randomization, we examined the health care costs of patients from the prior study.¹⁰ As with the case-control group, patients in this portion of the analysis were hospitalized before vaccines were available and prior to any identified variants.

Comparing the hospital cost of the IVIG-treated patients to the control patients from this trial revealed results similar to the matched case-control analysis discussed earlier. Average total direct cost per case, including IVIG, for the IVIG treatment group was $28,268, vs $62,707 per case for non-IVIG controls. This represented a net cost reduction of $34,439 (55%) per case, very similar to that of the prior cohort.

IVIG Reduces Costly Outlier Cases

The case-control and randomized trial groups, yielding a combined 23 IVIG and 34 control patients, showed a median cost per case of $22,578 (range $10,115-$70,929) and $22,645 (range $4723-$279,797) for the IVIG and control groups, respectively. Cases with a cost >$80,000 were 0/23 (0%) vs 8/34 (24%) in the IVIG and control groups, respectively (P = .016, Fisher exact test).

Improving care while simultaneously keeping care costs below reimbursement payment levels received from third-party payers is paramount to the financial survival of health care systems. IVIG appears to do this by reducing the number of patients with COVID-19 who progress to ICU care. We compared the costs of care of our combined case-control and randomized trial cohorts to published data on average reimbursements hospitals receive for COVID-19 care from Medicaid, Medicare, and private insurance (Figure).¹⁵ IVIG demonstrated a reduction in cases where costs exceed reimbursement. Indeed, a comparison of net revenue per case of the case-control group showed significantly higher revenue for the IVIG group compared to controls ($52,704 vs $34,712, P = .0338, Table 2).

Discussion

As reflected in at least 1 other study,¹⁶ our hospital had been successfully utilizing IVIG in the treatment of viral acute respiratory distress syndrome (ARDS) prior to COVID-19. Therefore, we moved quickly to perform a randomized, open-label pilot study of IVIG (Octagam 10%) in COVID-19, and noted significant clinical benefit that might translate into hospital cost savings.¹⁰ Over the course of the pandemic, evidence has accumulated that IVIG may play an important role in COVID-19 therapeutics, as summarized in a recent review.¹⁷ However, despite promising but inconsistent results, the relatively high acquisition costs of IVIG raised questions as to its pharmacoeconomic value, particularly with such a high volume of COVID-19 patients with hypoxia, in light of limited clinical data.

COVID-19 therapeutics data can be categorized into either high-quality trials showing marginal benefit for some agents or low-quality trials showing greater benefit for other agents, with IVIG studies falling into the latter category.¹⁸ This phenomenon may speak to the pathophysiological heterogeneity of the COVID-19 patient population. High-quality trials enrolling broad patient types lack the granularity to capture and single out relevant patient subsets who would derive maximal therapeutic benefit, with those subsets diluted by other patient types for which no benefit is seen. Meanwhile, the more granular low-quality trials are criticized as underpowered and lacking in translatability to practice.

Positive results from our pilot trial allowed the use of IVIG (Privigen) off-label in hospitalized COVID-19 patients restricted to specific criteria. Patients had to be moderately to severely ill, requiring >3 L of oxygen via nasal cannula; show high risk of clinical deterioration based on respiratory rate and decline in respiratory status; and have underlying comorbidities (such as hypertension, obesity, or diabetes mellitus). However, older patients (>age 70 years) and those with underlying comorbidities marked by organ failure (such as heart failure, renal failure, dementia, or receipt of organ transplant) and active malignancy were excluded, as their clinical outcome in COVID-19 may be considered less modifiable by therapeutics, while simultaneously carrying potentially a higher risk of adverse events from IVIG (volume overload, renal failure). These exclusions are reflected in the overall low Charlson comorbidity index (mean of 1) of the patients in the case-control study arm. As anticipated, we found a net cost reduction: $20,449 (48%) per case among the 10 IVIG-treated patients compared to the 20 matched controls.

We then went back to the patients from the randomized prospective trial and compared costs for the 13 of 16 IVIG patients and 14 of 17 of the control patients for whom data were available. Among untreated controls, we found a net cost reduction of $34,439 (55%) per case. The higher costs seen in the randomized patient cohort compared to the latter case-control group may be due to a combination of the fact that the treated patients had slightly higher comorbidity indices than the case-control group (median Charlson comorbidity index of 2 in both groups) and the fact that they were treated earlier in the pandemic (May/June 2020), as opposed to the case-control group patients, who were treated in November/December 2020.

It was notable that the cost savings across both groups were derived largely from the reduction in the approximately 20% to 25% of control patients who went on to critical illness, including mechanical ventilation, extracorporeal membrane oxygenation (ECMO), and prolonged ICU stays. Indeed, 8 of 34 of the control patients—but none of the 23 IVIG-treated patients—generated hospital costs in excess of $80,000, a difference that was statistically significant even for such a small sample size. Therefore, reducing these very costly outlier events translated into net savings across the board.

In addition to lowering costs, reducing progression to critical illness is extremely important during heavy waves of COVID-19, when the sheer volume of patients results in severe strain due to the relative scarcity of ICU beds, mechanical ventilators, and ECMO. Therefore, reducing the need for these resources would have a vital role that cannot be measured economically.

The major limitations of this study include the small sample size and the potential lack of generalizability of these results to all hospital centers and treating providers. Our group has considerable experience in IVIG utilization in COVID-19 and, as a result, has identified a “sweet spot,” where benefits were seen clinically and economically. However, it remains to be determined whether IVIG will benefit patients with greater illness severity, such as those in the ICU, on mechanical ventilation, or ECMO. Furthermore, while a significant morbidity and mortality burden of COVID-19 rests in extremely elderly patients and those with end-organ comorbidities such as renal failure and heart failure, it is uncertain whether their COVID-19 adverse outcomes can be improved with IVIG or other therapies. We believe such patients may limit the pharmacoeconomic value of IVIG due to their generally poorer prognosis, regardless of intervention. On the other hand, COVID-19 patients who are not that severely ill, with minimal to no hypoxia, generally will do well regardless of therapy. Therefore, IVIG intervention may be an unnecessary treatment expense. Evidence for this was suggested in our pilot trial¹⁰ and supported in a recent meta-analysis of IVIG therapy in COVID-19.¹⁹

Several other therapeutic options with high acquisition costs have seen an increase in use during the COVID-19 pandemic despite relatively lukewarm data. Remdesivir, the first drug found to have a beneficial effect on hospitalized patients with COVID-19, is priced at $3120 for a complete 5-day treatment course in the United States. This was in line with initial pricing models from the Institute for Clinical and Economic Review (ICER) in May 2020, assuming a mortality benefit with remdesivir use. After the SOLIDARITY trial was published, which showed no mortality benefit associated with remdesivir, ICER updated their pricing models in June 2020 and released a statement that the price of remdesivir was too high to align with demonstrated benefits.^20,21 More recent data demonstrate that remdesivir may be beneficial, but only if administered to patients with fewer than 6 days of symptoms.²² However, only a minority of patients present to the hospital early enough in their illness for remdesivir to be beneficial.²²

Tocilizumab, an interleukin-6 inhibitor, saw an increase in use during the pandemic. An 800-mg treatment course for COVID-19 costs $3584. The efficacy of this treatment option came into question after the COVACTA trial failed to show a difference in clinical status or mortality in COVID-19 patients who received tocilizumab vs placebo.^23,24 A more recent study pointed to a survival benefit of tocilizumab in COVID-19, driven by a very large sample size (>4000), yielding statistically significant, but perhaps clinically less significant, effects on survival.²⁵ This latter study points to the extremely large sample sizes required to capture statistically significant benefits of expensive interventions in COVID-19, which our data demonstrate may benefit only a fraction of patients (20%-25% of patients in the case of IVIG). A more granular clinical assessment of these other interventions is needed to be able to capture the patient subtypes where tocilizumab, remdesivir, and other therapies will be cost effective in the treatment of COVID-19 or other virally mediated cases of ARDS.

Conclusion

While IVIG has a high acquisition cost, the drug’s use in hypoxic COVID-19 patients resulted in reduced costs per COVID-19 case of approximately 50% and use of less critical care resources. The difference was consistent between 2 cohorts (randomized trial vs off-label use in prespecified COVID-19 patient types), IVIG products used (Octagam 10% and Privigen), and time period in the pandemic (waves 1 and 2 in May/June 2020 vs wave 3 in November/December 2020), thereby adjusting for potential differences in circulating viral strains. Furthermore, patients from both groups predated SARS-CoV-2 vaccine availability and major circulating viral variants (eg, delta, omicron), thereby eliminating confounding on outcomes posed by these factors. Control patients’ higher costs of care were driven largely by the approximately 25% of patients who required costly hospital critical care resources, a group mitigated by IVIG. When allocated to the appropriate patient type (patients with moderate-to-severe but not critical illness, <age 70 without preexisting comorbidities of end-organ failure or active cancer), IVIG can reduce hospital costs for COVID-19 care. Identification of specific patient populations where IVIG has the most anticipated benefits in viral illness is needed.

Corresponding author: George Sakoulas, MD, Sharp Rees-Stealy Medical Group, 2020 Genesee Avenue, 2nd Floor, San Diego, CA 92123; [email protected]

Disclosures: Dr Sakoulas has worked as a consultant for Abbvie, Paratek, and Octapharma, has served as a speaker for Abbvie and Paratek, and has received research funding from Octapharma. The other authors did not report any disclosures.

From Sharp Memorial Hospital, San Diego, CA (Drs. Poremba, Dehner, Perreiter, Semma, and Mills), Sharp Rees-Stealy Medical Group, San Diego, CA (Dr. Sakoulas), and Collaborative to Halt Antibiotic-Resistant Microbes (CHARM), Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, CA (Dr. Sakoulas).

Abstract

Objective: To compare the costs of hospitalization of patients with moderate-to-severe COVID-19 who received intravenous immunoglobulin (IVIG) with those of patients of similar comorbidity and illness severity who did not.

Design: Analysis 1 was a case-control study of 10 nonventilated, moderately to severely hypoxic patients with COVID-19 who received IVIG (Privigen [CSL Behring]) matched 1:2 with 20 control patients of similar age, body mass index, degree of hypoxemia, and comorbidities. Analysis 2 consisted of patients enrolled in a previously published, randomized, open-label prospective study of 14 patients with COVID-19 receiving standard of care vs 13 patients who received standard of care plus IVIG (Octagam 10% [Octapharma]).

Setting and participants: Patients with COVID-19 with moderate-to-severe hypoxemia hospitalized at a single site located in San Diego, California.

Measurements: Direct cost of hospitalization.

Results: In the first (case-control) population, mean total direct costs, including IVIG, for the treatment group were $21,982 per IVIG-treated case vs $42,431 per case for matched non-IVIG-receiving controls, representing a net cost reduction of $20,449 (48%) per case. For the second (randomized) group, mean total direct costs, including IVIG, for the treatment group were $28,268 per case vs $62,707 per case for untreated controls, representing a net cost reduction of $34,439 (55%) per case. Of the patients who did not receive IVIG, 24% had hospital costs exceeding $80,000; none of the IVIG-treated patients had costs exceeding this amount (P = .016, Fisher exact test).

Conclusion: If allocated early to the appropriate patient type (moderate-to-severe illness without end-organ comorbidities and age <70 years), IVIG can significantly reduce hospital costs in COVID-19 care. More important, in our study it reduced the demand for scarce critical care resources during the COVID-19 pandemic.

Keywords: IVIG, SARS-CoV-2, cost saving, direct hospital costs.

Intravenous immunoglobulin (IVIG) has been available in most hospitals for 4 decades, with broad therapeutic applications in the treatment of Kawasaki disease and a variety of inflammatory, infectious, autoimmune, and viral diseases, via multifactorial mechanisms of immune modulation.¹ Reports of COVID-19−associated multisystem inflammatory syndrome in adults and children have supported the use of IVIG in treatment.^2,3 Previous studies of IVIG treatment for COVID-19 have produced mixed results. Although retrospective studies have largely been positive,^4-8 prospective clinical trials have been mixed, with some favorable results^9-11 and another, more recent study showing no benefit.¹² However, there is still considerable debate regarding whether some subgroups of patients with COVID-19 may benefit from IVIG; the studies that support this argument, however, have been diluted by broad clinical trials that lack granularity among the heterogeneity of patient characteristics and the timing of IVIG administration.^13,14 One study suggests that patients with COVID-19 who may be particularly poised to benefit from IVIG are those who are younger, have fewer comorbidities, and are treated early.⁸

At our institution, we selectively utilized IVIG to treat patients within 48 hours of rapidly increasing oxygen requirements due to COVID-19, targeting those younger than 70 years, with no previous irreversible end-organ damage, no significant comorbidities (renal failure, heart failure, dementia, active cancer malignancies), and no active treatment for cancer. We analyzed the costs of care of these IVIG (Privigen) recipients and compared them to costs for patients with COVID-19 matched by comorbidities, age, and illness severity who did not receive IVIG. To look for consistency, we examined the cost of care of COVID-19 patients who received IVIG (Octagam) as compared to controls from a previously published pilot trial.¹⁰

Methods

Setting and Treatment

All patients in this study were hospitalized at a single site located in San Diego, California. Treatment patients in both cohorts received IVIG 0.5 g/kg adjusted for body weight daily for 3 consecutive days.

Patient Cohort #1: Retrospective Case-Control Trial

Intravenous immunoglobulin (Privigen 10%, CSL Behring) was utilized off-label to treat moderately to severely ill non-intensive care unit (ICU) patients with COVID-19 requiring ≥3 L of oxygen by nasal cannula who were not mechanically ventilated but were considered at high risk for respiratory failure. Preset exclusion criteria for off-label use of IVIG in the treatment of COVID-19 were age >70 years, active malignancy, organ transplant recipient, renal failure, heart failure, or dementia. Controls were obtained from a list of all admitted patients with COVID-19, matched to cases 2:1 on the basis of age (±10 years), body mass index (±1), gender, comorbidities present at admission (eg, hypertension, diabetes mellitus, lung disease, or history of tobacco use), and maximum oxygen requirements within the first 48 hours of admission. In situations where more than 2 potential matched controls were identified for a patient, the 2 controls closest in age to the treatment patient were selected. One IVIG patient was excluded because only 1 matched-age control could be found. Pregnant patients who otherwise fulfilled the criteria for IVIG administration were also excluded from this analysis.

Patient Cohort #2: Prospective, Randomized, Open-Label Trial

Use of IVIG (Octagam 10%, Octapharma) in COVID-19 was studied in a previously published, prospective, open-label randomized trial.¹⁰ This pilot trial included 16 IVIG-treated patients and 17 control patients, of which 13 and 14 patients, respectively, had hospital cost data available for analysis.¹⁰ Most notably, COVID-19 patients in this study were required to have ≥4 L of oxygen via nasal cannula to maintain arterial oxygen saturationof ≤96%.

Outcomes

Cost data were independently obtained from our finance team, which provided us with the total direct cost and the total pharmaceutical cost associated with each admission. We also compared total length of stay (LOS) and ICU LOS between treatment arms, as these were presumed to be the major drivers of cost difference.

Statistics

Nonparametric comparisons of medians were performed with the Mann-Whitney U test. Comparison of means was done by Student t test. Categorical data were analyzed by Fisher exact test.

This analysis was initiated as an internal quality assessment. It received approval from the Sharp Healthcare Institutional Review Board ([email protected]), and was granted a waiver of subject authorization and consent given the retrospective nature of the study.

Results

Case-Control Analysis

A total of 10 hypoxic patients with COVID-19 received Privigen IVIG outside of clinical trial settings. None of the patients was vaccinated against SARS-CoV-2, as hospitalization occurred prior to vaccine availability. In addition, the original SARS-CoV-2 strain was circulating while these patients were hospitalized, preceding subsequent emerging variants. Oxygen requirements within the first 48 hours ranged from 3 L via nasal cannula to requiring bi-level positive pressure airway therapy with 100% oxygen; median age was 56 years and median Charlson comorbidity index was 1. These 10 patients were each matched to 2 control patients hospitalized during a comparable time period and who, based on oxygen requirements, did not receive IVIG. The 20 control patients had a median age of 58.5 years and a Charlson comorbidity index of 1 (Table 1). Rates of comorbidities, such as hypertension, diabetes mellitus, and obesity, were identical in the 2 groups. None of the patients in either group died during the index hospitalization. Fewer control patients received glucocorticoids, which was reflective of lower illness severity/degree of hypoxia in some controls.

Health care utilization in terms of costs and hospital LOS between the 2 groups are shown in Table 2. The mean total direct hospital cost per case, including IVIG and other drug costs, for the 10 IVIG-treated COVID-19 patients was $21,982 vs $42,431 for the matched controls, a reduction of $20,449 (48%) per case (P = .6187) with IVIG. This difference was heavily driven by 4 control patients (20%) with hospital costs >$80,000, marked by need for ICU transfer, mechanical ventilation during admission, and longer hospital stays. This reduction in progression to mechanical ventilation was consistent with our previously published, open-label, randomized prospective IVIG study, the financial assessment of which is reviewed below. While total direct costs were lower in the treatment arm, the mean drug cost for the treatment arm was $3122 greater than the mean drug cost in the control arm (P = .001622), consistent with the high cost of IVIG therapy (Table 2).

LOS information was obtained, as this was thought to be a primary driver of direct costs. The average LOS in the IVIG arm was 8.4 days, and the average LOS in the control arm was 13.6 days (P = NS). The average ICU LOS in the IVIG arm was 0 days, while the average ICU LOS in the control arm was 5.3 days (P = .04). As with the differences in cost, the differences in LOS were primarily driven by the 4 outlier cases in our control arm, who each had a LOS >25 days, as well as an ICU LOS >20 days.

Randomized, Open-Label, Patient Cohort Analysis

Patient characteristics, LOS, and rates of mechanical ventilation for the IVIG and control patients were previously published and showed a reduction in mechanical ventilation and hospital LOS with IVIG treatment.¹⁰ In this group of patients, 1 patient treated with IVIG (6%) and 3 patients not treated with IVIG (18%) died. To determine the consistency of these results from the case-control patients with a set of patients obtained from clinical trial randomization, we examined the health care costs of patients from the prior study.¹⁰ As with the case-control group, patients in this portion of the analysis were hospitalized before vaccines were available and prior to any identified variants.

Comparing the hospital cost of the IVIG-treated patients to the control patients from this trial revealed results similar to the matched case-control analysis discussed earlier. Average total direct cost per case, including IVIG, for the IVIG treatment group was $28,268, vs $62,707 per case for non-IVIG controls. This represented a net cost reduction of $34,439 (55%) per case, very similar to that of the prior cohort.

IVIG Reduces Costly Outlier Cases

The case-control and randomized trial groups, yielding a combined 23 IVIG and 34 control patients, showed a median cost per case of $22,578 (range $10,115-$70,929) and $22,645 (range $4723-$279,797) for the IVIG and control groups, respectively. Cases with a cost >$80,000 were 0/23 (0%) vs 8/34 (24%) in the IVIG and control groups, respectively (P = .016, Fisher exact test).

Improving care while simultaneously keeping care costs below reimbursement payment levels received from third-party payers is paramount to the financial survival of health care systems. IVIG appears to do this by reducing the number of patients with COVID-19 who progress to ICU care. We compared the costs of care of our combined case-control and randomized trial cohorts to published data on average reimbursements hospitals receive for COVID-19 care from Medicaid, Medicare, and private insurance (Figure).¹⁵ IVIG demonstrated a reduction in cases where costs exceed reimbursement. Indeed, a comparison of net revenue per case of the case-control group showed significantly higher revenue for the IVIG group compared to controls ($52,704 vs $34,712, P = .0338, Table 2).

Discussion

As reflected in at least 1 other study,¹⁶ our hospital had been successfully utilizing IVIG in the treatment of viral acute respiratory distress syndrome (ARDS) prior to COVID-19. Therefore, we moved quickly to perform a randomized, open-label pilot study of IVIG (Octagam 10%) in COVID-19, and noted significant clinical benefit that might translate into hospital cost savings.¹⁰ Over the course of the pandemic, evidence has accumulated that IVIG may play an important role in COVID-19 therapeutics, as summarized in a recent review.¹⁷ However, despite promising but inconsistent results, the relatively high acquisition costs of IVIG raised questions as to its pharmacoeconomic value, particularly with such a high volume of COVID-19 patients with hypoxia, in light of limited clinical data.

COVID-19 therapeutics data can be categorized into either high-quality trials showing marginal benefit for some agents or low-quality trials showing greater benefit for other agents, with IVIG studies falling into the latter category.¹⁸ This phenomenon may speak to the pathophysiological heterogeneity of the COVID-19 patient population. High-quality trials enrolling broad patient types lack the granularity to capture and single out relevant patient subsets who would derive maximal therapeutic benefit, with those subsets diluted by other patient types for which no benefit is seen. Meanwhile, the more granular low-quality trials are criticized as underpowered and lacking in translatability to practice.

Positive results from our pilot trial allowed the use of IVIG (Privigen) off-label in hospitalized COVID-19 patients restricted to specific criteria. Patients had to be moderately to severely ill, requiring >3 L of oxygen via nasal cannula; show high risk of clinical deterioration based on respiratory rate and decline in respiratory status; and have underlying comorbidities (such as hypertension, obesity, or diabetes mellitus). However, older patients (>age 70 years) and those with underlying comorbidities marked by organ failure (such as heart failure, renal failure, dementia, or receipt of organ transplant) and active malignancy were excluded, as their clinical outcome in COVID-19 may be considered less modifiable by therapeutics, while simultaneously carrying potentially a higher risk of adverse events from IVIG (volume overload, renal failure). These exclusions are reflected in the overall low Charlson comorbidity index (mean of 1) of the patients in the case-control study arm. As anticipated, we found a net cost reduction: $20,449 (48%) per case among the 10 IVIG-treated patients compared to the 20 matched controls.

We then went back to the patients from the randomized prospective trial and compared costs for the 13 of 16 IVIG patients and 14 of 17 of the control patients for whom data were available. Among untreated controls, we found a net cost reduction of $34,439 (55%) per case. The higher costs seen in the randomized patient cohort compared to the latter case-control group may be due to a combination of the fact that the treated patients had slightly higher comorbidity indices than the case-control group (median Charlson comorbidity index of 2 in both groups) and the fact that they were treated earlier in the pandemic (May/June 2020), as opposed to the case-control group patients, who were treated in November/December 2020.

It was notable that the cost savings across both groups were derived largely from the reduction in the approximately 20% to 25% of control patients who went on to critical illness, including mechanical ventilation, extracorporeal membrane oxygenation (ECMO), and prolonged ICU stays. Indeed, 8 of 34 of the control patients—but none of the 23 IVIG-treated patients—generated hospital costs in excess of $80,000, a difference that was statistically significant even for such a small sample size. Therefore, reducing these very costly outlier events translated into net savings across the board.

In addition to lowering costs, reducing progression to critical illness is extremely important during heavy waves of COVID-19, when the sheer volume of patients results in severe strain due to the relative scarcity of ICU beds, mechanical ventilators, and ECMO. Therefore, reducing the need for these resources would have a vital role that cannot be measured economically.

The major limitations of this study include the small sample size and the potential lack of generalizability of these results to all hospital centers and treating providers. Our group has considerable experience in IVIG utilization in COVID-19 and, as a result, has identified a “sweet spot,” where benefits were seen clinically and economically. However, it remains to be determined whether IVIG will benefit patients with greater illness severity, such as those in the ICU, on mechanical ventilation, or ECMO. Furthermore, while a significant morbidity and mortality burden of COVID-19 rests in extremely elderly patients and those with end-organ comorbidities such as renal failure and heart failure, it is uncertain whether their COVID-19 adverse outcomes can be improved with IVIG or other therapies. We believe such patients may limit the pharmacoeconomic value of IVIG due to their generally poorer prognosis, regardless of intervention. On the other hand, COVID-19 patients who are not that severely ill, with minimal to no hypoxia, generally will do well regardless of therapy. Therefore, IVIG intervention may be an unnecessary treatment expense. Evidence for this was suggested in our pilot trial¹⁰ and supported in a recent meta-analysis of IVIG therapy in COVID-19.¹⁹

Several other therapeutic options with high acquisition costs have seen an increase in use during the COVID-19 pandemic despite relatively lukewarm data. Remdesivir, the first drug found to have a beneficial effect on hospitalized patients with COVID-19, is priced at $3120 for a complete 5-day treatment course in the United States. This was in line with initial pricing models from the Institute for Clinical and Economic Review (ICER) in May 2020, assuming a mortality benefit with remdesivir use. After the SOLIDARITY trial was published, which showed no mortality benefit associated with remdesivir, ICER updated their pricing models in June 2020 and released a statement that the price of remdesivir was too high to align with demonstrated benefits.^20,21 More recent data demonstrate that remdesivir may be beneficial, but only if administered to patients with fewer than 6 days of symptoms.²² However, only a minority of patients present to the hospital early enough in their illness for remdesivir to be beneficial.²²

Tocilizumab, an interleukin-6 inhibitor, saw an increase in use during the pandemic. An 800-mg treatment course for COVID-19 costs $3584. The efficacy of this treatment option came into question after the COVACTA trial failed to show a difference in clinical status or mortality in COVID-19 patients who received tocilizumab vs placebo.^23,24 A more recent study pointed to a survival benefit of tocilizumab in COVID-19, driven by a very large sample size (>4000), yielding statistically significant, but perhaps clinically less significant, effects on survival.²⁵ This latter study points to the extremely large sample sizes required to capture statistically significant benefits of expensive interventions in COVID-19, which our data demonstrate may benefit only a fraction of patients (20%-25% of patients in the case of IVIG). A more granular clinical assessment of these other interventions is needed to be able to capture the patient subtypes where tocilizumab, remdesivir, and other therapies will be cost effective in the treatment of COVID-19 or other virally mediated cases of ARDS.

Conclusion

While IVIG has a high acquisition cost, the drug’s use in hypoxic COVID-19 patients resulted in reduced costs per COVID-19 case of approximately 50% and use of less critical care resources. The difference was consistent between 2 cohorts (randomized trial vs off-label use in prespecified COVID-19 patient types), IVIG products used (Octagam 10% and Privigen), and time period in the pandemic (waves 1 and 2 in May/June 2020 vs wave 3 in November/December 2020), thereby adjusting for potential differences in circulating viral strains. Furthermore, patients from both groups predated SARS-CoV-2 vaccine availability and major circulating viral variants (eg, delta, omicron), thereby eliminating confounding on outcomes posed by these factors. Control patients’ higher costs of care were driven largely by the approximately 25% of patients who required costly hospital critical care resources, a group mitigated by IVIG. When allocated to the appropriate patient type (patients with moderate-to-severe but not critical illness, <age 70 without preexisting comorbidities of end-organ failure or active cancer), IVIG can reduce hospital costs for COVID-19 care. Identification of specific patient populations where IVIG has the most anticipated benefits in viral illness is needed.

Corresponding author: George Sakoulas, MD, Sharp Rees-Stealy Medical Group, 2020 Genesee Avenue, 2nd Floor, San Diego, CA 92123; [email protected]

Disclosures: Dr Sakoulas has worked as a consultant for Abbvie, Paratek, and Octapharma, has served as a speaker for Abbvie and Paratek, and has received research funding from Octapharma. The other authors did not report any disclosures.

Study 1 Overview (SCOT-HEART Investigators)

Objective: To assess cardiovascular mortality and nonfatal myocardial infarction at 5 years in patients with stable chest pain referred to cardiology clinic for management with either standard care plus computed tomography angiography (CTA) or standard care alone.

Design: Multicenter, randomized, open-label prospective study.

Setting and participants: A total of 4146 patients with stable chest pain were randomized to standard care or standard care plus CTA at 12 centers across Scotland and were followed for 5 years.

Main outcome measures: The primary end point was a composite of death from coronary heart disease or nonfatal myocardial infarction. Main secondary end points were nonfatal myocardial infarction, nonfatal stroke, and frequency of invasive coronary angiography (ICA) and coronary revascularization with percutaneous coronary intervention or coronary artery bypass grafting.

Main results: The primary outcome including the composite of cardiovascular death or nonfatal myocardial infarction was lower in the CTA group than in the standard-care group at 2.3% (48 of 2073 patients) vs 3.9% (81 of 2073 patients), respectively (hazard ratio, 0.59; 95% CI, 0.41-0.84; P = .004). Although there was a higher rate of ICA and coronary revascularization in the CTA group than in the standard-care group in the first few months of follow-up, the overall rates were similar at 5 years, with ICA performed in 491 patients and 502 patients in the CTA vs standard-care groups, respectively (hazard ratio, 1.00; 95% CI, 0.88-1.13). Similarly, coronary revascularization was performed in 279 patients in the CTA group and in 267 patients in the standard-care group (hazard ratio, 1.07; 95% CI, 0.91-1.27). There were, however, more preventive therapies initiated in patients in the CTA group than in the standard-care group (odds ratio, 1.40; 95% CI, 1.19-1.65).

Conclusion: In patients with stable chest pain, the use of CTA in addition to standard care resulted in a significantly lower rate of death from coronary heart disease or nonfatal myocardial infarction at 5 years; the main contributor to this outcome was a reduced nonfatal myocardial infarction rate. There was no difference in the rate of coronary angiography or coronary revascularization between the 2 groups at 5 years.

Study 2 Overview (DISCHARGE Trial Group)

Objective: To compare the effectiveness of computed tomography (CT) with ICA as a diagnostic tool in patients with stable chest pain and intermediate pretest probability of coronary artery disease (CAD).

Design: Multicenter, randomized, assessor-blinded pragmatic prospective study.

Setting and participants: A total of 3667 patients with stable chest pain and intermediate pretest probability of CAD were enrolled at 26 centers and randomized into CT or ICA groups. Only 3561 patients were included in the modified intention-to-treat analysis, with 1808 patients and 1753 patients in the CT and ICA groups, respectively.

Main outcome measures: The primary outcome was a composite of cardiovascular death, nonfatal myocardial infarction, and nonfatal stroke over 3.5 years. The main secondary outcomes were major procedure-related complications and patient-reported angina pectoris during the last 4 weeks of follow up.

Main results: The primary outcome occurred in 38 of 1808 patients (2.1%) in the CT group and in 52 of 1753 patients (3.0%) in the ICA group (hazard ratio, 0.70; 95% CI, 0.46-1.07; P = .10). The secondary outcomes showed that major procedure-related complications occurred in 9 patients (0.5%) in the CT group and in 33 patients (1.9%) in the ICA group (hazard ratio, 0.26; 95% CI, 0.13-0.55). Rates of patient-reported angina in the final 4 weeks of follow-up were 8.8% in the CT group and 7.5% in the ICA group (odds ratio, 1.17; 95% CI, 0.92-1.48).

Conclusion: Risk of major adverse cardiovascular events from the primary outcome were similar in both the CT and ICA groups among patients with stable chest pain and intermediate pretest probability of CAD. Patients referred for CT had a lower rate of coronary angiography leading to fewer major procedure-related complications in these patients than in those referred for ICA.

Evaluation and treatment of obstructive atherosclerosis is an important part of clinical care in patients presenting with angina symptoms.¹ Thus, the initial investigation for patients with suspected obstructive CAD includes ruling out acute coronary syndrome and assessing quality of life.¹ The diagnostic test should be tailored to the pretest probability for the diagnosis of obstructive CAD.²

In the United States, stress testing traditionally has been used for the initial assessment in patients with suspected CAD,³ but recently CTA has been utilized more frequently for this purpose. Compared to a stress test, which often helps identify and assess ischemia, CTA can provide anatomical assessment, with higher sensitivity to identify CAD.⁴ Furthermore, it can distinguish nonobstructive plaques that can be challenging to identify with stress test alone.

Whether CTA is superior to stress testing as the initial assessment for CAD has been debated. The randomized PROMISE trial compared patients with stable angina who underwent functional stress testing or CTA as an initial strategy.⁵ They reported a similar outcome between the 2 groups at a median follow-up of 2 years. However, in the original SCOT-HEART trial (CT coronary angiography in patients with suspected angina due to coronary heart disease), which was published in the same year as the PROMISE trial, the patients who underwent initial assessment with CTA had a numerically lower composite end point of cardiac death and myocardial infarction at a median follow-up of 1.7 years (1.3% vs 2.0%, P = .053).⁶

Given this result, the SCOT-HEART investigators extended the follow-up to evaluate the composite end point of death from coronary heart disease or nonfatal myocardial infarction at 5 years.⁷ This trial enrolled patients who were initially referred to a cardiology clinic for evaluation of chest pain, and they were randomized to standard care plus CTA or standard care alone. At a median duration of 4.8 years, the primary outcome was lower in the CTA group (2.3%, 48 patients) than in the standard-care group (3.9%, 81 patients) (hazard ratio, 0.58; 95% CI, 0.41-0.84; P = .004). Both groups had similar rates of invasive coronary angiography and had similar coronary revascularization rates.

It is hypothesized that this lower rate of nonfatal myocardial infarction in patients with CTA plus standard care is associated with a higher rate of preventive therapies initiated in patients in the CTA-plus-standard-care group compared to standard care alone. However, the difference in the standard-care group should be noted when compared to the PROMISE trial. In the PROMISE trial, the comparator group had predominantly stress imaging (either nuclear stress test or echocardiography), while in the SCOT-HEART trial, the group had predominantly stress electrocardiogram (ECG), and only 10% of the patients underwent stress imaging. It is possible the difference seen in the rate of nonfatal myocardial infarction was due to suboptimal diagnosis of CAD with stress ECG, which has lower sensitivity compared to stress imaging.

The DISCHARGE trial investigated the effectiveness of CTA vs ICA as the initial diagnostic test in the management of patients with stable chest pain and an intermediate pretest probability of obstructive CAD.⁸ At 3.5 years of follow-up, the primary composite of cardiovascular death, myocardial infarction, or stroke was similar in both groups (2.1% vs 3.0; hazard ratio, 0.70; 95% CI, 0.46-1.07; P = .10). Importantly, as fewer patients underwent ICA, the risk of procedure-related complication was lower in the CTA group than in the ICA group. However, it is important to note that only 25% of the patients diagnosed with obstructive CAD had greater than 50% vessel stenosis, which raises the question of whether an initial invasive strategy is appropriate for this population.

The strengths of these 2 studies include the large number of patients enrolled along with adequate follow-up, 5 years in the SCOT-HEART trial and 3.5 years in the DISCHARGE trial. The 2 studies overall suggest the usefulness of CTA for assessment of CAD. However, the control groups were very different in these 2 trials. In the SCOT-HEART study, the comparator group was primarily assessed by stress ECG, while in the DISCHARGE study, the comparator group was primary assessed by ICA. In the PROMISE trial, the composite end point of death, myocardial infarction, hospitalization for unstable angina, or major procedural complication was similar when the strategy of initial CTA was compared to functional testing with imaging (exercise ECG, nuclear stress testing, or echocardiography).⁵ Thus, clinical assessment is still needed when clinicians are selecting the appropriate diagnostic test for patients with suspected CAD. The most recent guidelines give similar recommendations for CTA compared to stress imaging.⁹ Whether further improvement in CTA acquisition or the addition of CT fractional flow reserve can further improve outcomes requires additional study.

Applications for Clinical Practice and System Implementation

In patients with stable chest pain and intermediate pretest probability of CAD, CTA is useful in diagnosis compared to stress ECG and in reducing utilization of low-yield ICA. Whether CTA is more useful compared to the other noninvasive stress imaging modalities in this population requires further study.

Practice Points

• In patients with stable chest pain and intermediate pretest probability of CAD, CTA is useful compared to stress ECG.
• Use of CTA can potentially reduce the use of low-yield coronary angiography.

–Thai Nguyen, MD, Albert Chan, MD, Taishi Hirai, MD
University of Missouri, Columbia, MO

Study 1 Overview (SCOT-HEART Investigators)

Objective: To assess cardiovascular mortality and nonfatal myocardial infarction at 5 years in patients with stable chest pain referred to cardiology clinic for management with either standard care plus computed tomography angiography (CTA) or standard care alone.

Design: Multicenter, randomized, open-label prospective study.

Setting and participants: A total of 4146 patients with stable chest pain were randomized to standard care or standard care plus CTA at 12 centers across Scotland and were followed for 5 years.

Main outcome measures: The primary end point was a composite of death from coronary heart disease or nonfatal myocardial infarction. Main secondary end points were nonfatal myocardial infarction, nonfatal stroke, and frequency of invasive coronary angiography (ICA) and coronary revascularization with percutaneous coronary intervention or coronary artery bypass grafting.

Main results: The primary outcome including the composite of cardiovascular death or nonfatal myocardial infarction was lower in the CTA group than in the standard-care group at 2.3% (48 of 2073 patients) vs 3.9% (81 of 2073 patients), respectively (hazard ratio, 0.59; 95% CI, 0.41-0.84; P = .004). Although there was a higher rate of ICA and coronary revascularization in the CTA group than in the standard-care group in the first few months of follow-up, the overall rates were similar at 5 years, with ICA performed in 491 patients and 502 patients in the CTA vs standard-care groups, respectively (hazard ratio, 1.00; 95% CI, 0.88-1.13). Similarly, coronary revascularization was performed in 279 patients in the CTA group and in 267 patients in the standard-care group (hazard ratio, 1.07; 95% CI, 0.91-1.27). There were, however, more preventive therapies initiated in patients in the CTA group than in the standard-care group (odds ratio, 1.40; 95% CI, 1.19-1.65).

Conclusion: In patients with stable chest pain, the use of CTA in addition to standard care resulted in a significantly lower rate of death from coronary heart disease or nonfatal myocardial infarction at 5 years; the main contributor to this outcome was a reduced nonfatal myocardial infarction rate. There was no difference in the rate of coronary angiography or coronary revascularization between the 2 groups at 5 years.

Study 2 Overview (DISCHARGE Trial Group)

Objective: To compare the effectiveness of computed tomography (CT) with ICA as a diagnostic tool in patients with stable chest pain and intermediate pretest probability of coronary artery disease (CAD).

Design: Multicenter, randomized, assessor-blinded pragmatic prospective study.

Setting and participants: A total of 3667 patients with stable chest pain and intermediate pretest probability of CAD were enrolled at 26 centers and randomized into CT or ICA groups. Only 3561 patients were included in the modified intention-to-treat analysis, with 1808 patients and 1753 patients in the CT and ICA groups, respectively.

Main outcome measures: The primary outcome was a composite of cardiovascular death, nonfatal myocardial infarction, and nonfatal stroke over 3.5 years. The main secondary outcomes were major procedure-related complications and patient-reported angina pectoris during the last 4 weeks of follow up.

Main results: The primary outcome occurred in 38 of 1808 patients (2.1%) in the CT group and in 52 of 1753 patients (3.0%) in the ICA group (hazard ratio, 0.70; 95% CI, 0.46-1.07; P = .10). The secondary outcomes showed that major procedure-related complications occurred in 9 patients (0.5%) in the CT group and in 33 patients (1.9%) in the ICA group (hazard ratio, 0.26; 95% CI, 0.13-0.55). Rates of patient-reported angina in the final 4 weeks of follow-up were 8.8% in the CT group and 7.5% in the ICA group (odds ratio, 1.17; 95% CI, 0.92-1.48).

Conclusion: Risk of major adverse cardiovascular events from the primary outcome were similar in both the CT and ICA groups among patients with stable chest pain and intermediate pretest probability of CAD. Patients referred for CT had a lower rate of coronary angiography leading to fewer major procedure-related complications in these patients than in those referred for ICA.

Evaluation and treatment of obstructive atherosclerosis is an important part of clinical care in patients presenting with angina symptoms.¹ Thus, the initial investigation for patients with suspected obstructive CAD includes ruling out acute coronary syndrome and assessing quality of life.¹ The diagnostic test should be tailored to the pretest probability for the diagnosis of obstructive CAD.²

In the United States, stress testing traditionally has been used for the initial assessment in patients with suspected CAD,³ but recently CTA has been utilized more frequently for this purpose. Compared to a stress test, which often helps identify and assess ischemia, CTA can provide anatomical assessment, with higher sensitivity to identify CAD.⁴ Furthermore, it can distinguish nonobstructive plaques that can be challenging to identify with stress test alone.

Whether CTA is superior to stress testing as the initial assessment for CAD has been debated. The randomized PROMISE trial compared patients with stable angina who underwent functional stress testing or CTA as an initial strategy.⁵ They reported a similar outcome between the 2 groups at a median follow-up of 2 years. However, in the original SCOT-HEART trial (CT coronary angiography in patients with suspected angina due to coronary heart disease), which was published in the same year as the PROMISE trial, the patients who underwent initial assessment with CTA had a numerically lower composite end point of cardiac death and myocardial infarction at a median follow-up of 1.7 years (1.3% vs 2.0%, P = .053).⁶

Given this result, the SCOT-HEART investigators extended the follow-up to evaluate the composite end point of death from coronary heart disease or nonfatal myocardial infarction at 5 years.⁷ This trial enrolled patients who were initially referred to a cardiology clinic for evaluation of chest pain, and they were randomized to standard care plus CTA or standard care alone. At a median duration of 4.8 years, the primary outcome was lower in the CTA group (2.3%, 48 patients) than in the standard-care group (3.9%, 81 patients) (hazard ratio, 0.58; 95% CI, 0.41-0.84; P = .004). Both groups had similar rates of invasive coronary angiography and had similar coronary revascularization rates.

It is hypothesized that this lower rate of nonfatal myocardial infarction in patients with CTA plus standard care is associated with a higher rate of preventive therapies initiated in patients in the CTA-plus-standard-care group compared to standard care alone. However, the difference in the standard-care group should be noted when compared to the PROMISE trial. In the PROMISE trial, the comparator group had predominantly stress imaging (either nuclear stress test or echocardiography), while in the SCOT-HEART trial, the group had predominantly stress electrocardiogram (ECG), and only 10% of the patients underwent stress imaging. It is possible the difference seen in the rate of nonfatal myocardial infarction was due to suboptimal diagnosis of CAD with stress ECG, which has lower sensitivity compared to stress imaging.

The DISCHARGE trial investigated the effectiveness of CTA vs ICA as the initial diagnostic test in the management of patients with stable chest pain and an intermediate pretest probability of obstructive CAD.⁸ At 3.5 years of follow-up, the primary composite of cardiovascular death, myocardial infarction, or stroke was similar in both groups (2.1% vs 3.0; hazard ratio, 0.70; 95% CI, 0.46-1.07; P = .10). Importantly, as fewer patients underwent ICA, the risk of procedure-related complication was lower in the CTA group than in the ICA group. However, it is important to note that only 25% of the patients diagnosed with obstructive CAD had greater than 50% vessel stenosis, which raises the question of whether an initial invasive strategy is appropriate for this population.

The strengths of these 2 studies include the large number of patients enrolled along with adequate follow-up, 5 years in the SCOT-HEART trial and 3.5 years in the DISCHARGE trial. The 2 studies overall suggest the usefulness of CTA for assessment of CAD. However, the control groups were very different in these 2 trials. In the SCOT-HEART study, the comparator group was primarily assessed by stress ECG, while in the DISCHARGE study, the comparator group was primary assessed by ICA. In the PROMISE trial, the composite end point of death, myocardial infarction, hospitalization for unstable angina, or major procedural complication was similar when the strategy of initial CTA was compared to functional testing with imaging (exercise ECG, nuclear stress testing, or echocardiography).⁵ Thus, clinical assessment is still needed when clinicians are selecting the appropriate diagnostic test for patients with suspected CAD. The most recent guidelines give similar recommendations for CTA compared to stress imaging.⁹ Whether further improvement in CTA acquisition or the addition of CT fractional flow reserve can further improve outcomes requires additional study.

Applications for Clinical Practice and System Implementation

In patients with stable chest pain and intermediate pretest probability of CAD, CTA is useful in diagnosis compared to stress ECG and in reducing utilization of low-yield ICA. Whether CTA is more useful compared to the other noninvasive stress imaging modalities in this population requires further study.

Practice Points

• In patients with stable chest pain and intermediate pretest probability of CAD, CTA is useful compared to stress ECG.
• Use of CTA can potentially reduce the use of low-yield coronary angiography.

–Thai Nguyen, MD, Albert Chan, MD, Taishi Hirai, MD
University of Missouri, Columbia, MO

Study 1 Overview (SCOT-HEART Investigators)

Objective: To assess cardiovascular mortality and nonfatal myocardial infarction at 5 years in patients with stable chest pain referred to cardiology clinic for management with either standard care plus computed tomography angiography (CTA) or standard care alone.

Design: Multicenter, randomized, open-label prospective study.

Setting and participants: A total of 4146 patients with stable chest pain were randomized to standard care or standard care plus CTA at 12 centers across Scotland and were followed for 5 years.

Main outcome measures: The primary end point was a composite of death from coronary heart disease or nonfatal myocardial infarction. Main secondary end points were nonfatal myocardial infarction, nonfatal stroke, and frequency of invasive coronary angiography (ICA) and coronary revascularization with percutaneous coronary intervention or coronary artery bypass grafting.

Main results: The primary outcome including the composite of cardiovascular death or nonfatal myocardial infarction was lower in the CTA group than in the standard-care group at 2.3% (48 of 2073 patients) vs 3.9% (81 of 2073 patients), respectively (hazard ratio, 0.59; 95% CI, 0.41-0.84; P = .004). Although there was a higher rate of ICA and coronary revascularization in the CTA group than in the standard-care group in the first few months of follow-up, the overall rates were similar at 5 years, with ICA performed in 491 patients and 502 patients in the CTA vs standard-care groups, respectively (hazard ratio, 1.00; 95% CI, 0.88-1.13). Similarly, coronary revascularization was performed in 279 patients in the CTA group and in 267 patients in the standard-care group (hazard ratio, 1.07; 95% CI, 0.91-1.27). There were, however, more preventive therapies initiated in patients in the CTA group than in the standard-care group (odds ratio, 1.40; 95% CI, 1.19-1.65).

Conclusion: In patients with stable chest pain, the use of CTA in addition to standard care resulted in a significantly lower rate of death from coronary heart disease or nonfatal myocardial infarction at 5 years; the main contributor to this outcome was a reduced nonfatal myocardial infarction rate. There was no difference in the rate of coronary angiography or coronary revascularization between the 2 groups at 5 years.

Study 2 Overview (DISCHARGE Trial Group)

Objective: To compare the effectiveness of computed tomography (CT) with ICA as a diagnostic tool in patients with stable chest pain and intermediate pretest probability of coronary artery disease (CAD).

Design: Multicenter, randomized, assessor-blinded pragmatic prospective study.

Setting and participants: A total of 3667 patients with stable chest pain and intermediate pretest probability of CAD were enrolled at 26 centers and randomized into CT or ICA groups. Only 3561 patients were included in the modified intention-to-treat analysis, with 1808 patients and 1753 patients in the CT and ICA groups, respectively.

Main outcome measures: The primary outcome was a composite of cardiovascular death, nonfatal myocardial infarction, and nonfatal stroke over 3.5 years. The main secondary outcomes were major procedure-related complications and patient-reported angina pectoris during the last 4 weeks of follow up.

Main results: The primary outcome occurred in 38 of 1808 patients (2.1%) in the CT group and in 52 of 1753 patients (3.0%) in the ICA group (hazard ratio, 0.70; 95% CI, 0.46-1.07; P = .10). The secondary outcomes showed that major procedure-related complications occurred in 9 patients (0.5%) in the CT group and in 33 patients (1.9%) in the ICA group (hazard ratio, 0.26; 95% CI, 0.13-0.55). Rates of patient-reported angina in the final 4 weeks of follow-up were 8.8% in the CT group and 7.5% in the ICA group (odds ratio, 1.17; 95% CI, 0.92-1.48).

Conclusion: Risk of major adverse cardiovascular events from the primary outcome were similar in both the CT and ICA groups among patients with stable chest pain and intermediate pretest probability of CAD. Patients referred for CT had a lower rate of coronary angiography leading to fewer major procedure-related complications in these patients than in those referred for ICA.

Evaluation and treatment of obstructive atherosclerosis is an important part of clinical care in patients presenting with angina symptoms.¹ Thus, the initial investigation for patients with suspected obstructive CAD includes ruling out acute coronary syndrome and assessing quality of life.¹ The diagnostic test should be tailored to the pretest probability for the diagnosis of obstructive CAD.²

In the United States, stress testing traditionally has been used for the initial assessment in patients with suspected CAD,³ but recently CTA has been utilized more frequently for this purpose. Compared to a stress test, which often helps identify and assess ischemia, CTA can provide anatomical assessment, with higher sensitivity to identify CAD.⁴ Furthermore, it can distinguish nonobstructive plaques that can be challenging to identify with stress test alone.

Whether CTA is superior to stress testing as the initial assessment for CAD has been debated. The randomized PROMISE trial compared patients with stable angina who underwent functional stress testing or CTA as an initial strategy.⁵ They reported a similar outcome between the 2 groups at a median follow-up of 2 years. However, in the original SCOT-HEART trial (CT coronary angiography in patients with suspected angina due to coronary heart disease), which was published in the same year as the PROMISE trial, the patients who underwent initial assessment with CTA had a numerically lower composite end point of cardiac death and myocardial infarction at a median follow-up of 1.7 years (1.3% vs 2.0%, P = .053).⁶

Given this result, the SCOT-HEART investigators extended the follow-up to evaluate the composite end point of death from coronary heart disease or nonfatal myocardial infarction at 5 years.⁷ This trial enrolled patients who were initially referred to a cardiology clinic for evaluation of chest pain, and they were randomized to standard care plus CTA or standard care alone. At a median duration of 4.8 years, the primary outcome was lower in the CTA group (2.3%, 48 patients) than in the standard-care group (3.9%, 81 patients) (hazard ratio, 0.58; 95% CI, 0.41-0.84; P = .004). Both groups had similar rates of invasive coronary angiography and had similar coronary revascularization rates.

It is hypothesized that this lower rate of nonfatal myocardial infarction in patients with CTA plus standard care is associated with a higher rate of preventive therapies initiated in patients in the CTA-plus-standard-care group compared to standard care alone. However, the difference in the standard-care group should be noted when compared to the PROMISE trial. In the PROMISE trial, the comparator group had predominantly stress imaging (either nuclear stress test or echocardiography), while in the SCOT-HEART trial, the group had predominantly stress electrocardiogram (ECG), and only 10% of the patients underwent stress imaging. It is possible the difference seen in the rate of nonfatal myocardial infarction was due to suboptimal diagnosis of CAD with stress ECG, which has lower sensitivity compared to stress imaging.

The DISCHARGE trial investigated the effectiveness of CTA vs ICA as the initial diagnostic test in the management of patients with stable chest pain and an intermediate pretest probability of obstructive CAD.⁸ At 3.5 years of follow-up, the primary composite of cardiovascular death, myocardial infarction, or stroke was similar in both groups (2.1% vs 3.0; hazard ratio, 0.70; 95% CI, 0.46-1.07; P = .10). Importantly, as fewer patients underwent ICA, the risk of procedure-related complication was lower in the CTA group than in the ICA group. However, it is important to note that only 25% of the patients diagnosed with obstructive CAD had greater than 50% vessel stenosis, which raises the question of whether an initial invasive strategy is appropriate for this population.

The strengths of these 2 studies include the large number of patients enrolled along with adequate follow-up, 5 years in the SCOT-HEART trial and 3.5 years in the DISCHARGE trial. The 2 studies overall suggest the usefulness of CTA for assessment of CAD. However, the control groups were very different in these 2 trials. In the SCOT-HEART study, the comparator group was primarily assessed by stress ECG, while in the DISCHARGE study, the comparator group was primary assessed by ICA. In the PROMISE trial, the composite end point of death, myocardial infarction, hospitalization for unstable angina, or major procedural complication was similar when the strategy of initial CTA was compared to functional testing with imaging (exercise ECG, nuclear stress testing, or echocardiography).⁵ Thus, clinical assessment is still needed when clinicians are selecting the appropriate diagnostic test for patients with suspected CAD. The most recent guidelines give similar recommendations for CTA compared to stress imaging.⁹ Whether further improvement in CTA acquisition or the addition of CT fractional flow reserve can further improve outcomes requires additional study.

Applications for Clinical Practice and System Implementation

In patients with stable chest pain and intermediate pretest probability of CAD, CTA is useful in diagnosis compared to stress ECG and in reducing utilization of low-yield ICA. Whether CTA is more useful compared to the other noninvasive stress imaging modalities in this population requires further study.

Practice Points

• In patients with stable chest pain and intermediate pretest probability of CAD, CTA is useful compared to stress ECG.
• Use of CTA can potentially reduce the use of low-yield coronary angiography.

–Thai Nguyen, MD, Albert Chan, MD, Taishi Hirai, MD
University of Missouri, Columbia, MO

INDIANAPOLIS – Recent legislative sessions in state legislative houses across the country have yielded progress toward codifying optimal team practice (OTP) into state law. That’s according to Phil Bongiorno, BA, senior vice president of advocacy and government relations at the American Academy of Physician Associates (AAPA), who spoke at the group’s annual meeting.

OTP refers to the AAPA’s goal of improving patient access to care and lessening administrative obligations by eliminating the legal requirement that there be a specific relationship between a PA, physician, or any other health care provider. This would allow a PA to practice to the full extent of their education, training, and experience, Mr. Bongiorno said.

The second tenet of OTP is to persuade states to create a separate majority PA board to regulate PAs. An alternative to this would be for states to add PAs and physicians who work with PAs to their medical or healing arts boards, he said.

Third, in an OTP environment, each state would authorize PAs to be eligible for direct payment by all public and private insurers. “We have seen that development at the federal level, as far as Medicare is concerned,” Mr. Bongiorno said. “Now, we’re focusing on making that happen in the individual states as well.”

According to Mr. Bongiorno, this year’s state advocacy priorities are to pursue new legislation in additional states, even as efforts continue to persuade state legislatures to act on carryover bills from the previous legislative session.

Mr. Bongiorno briefly summarized what he called “OTP successes” from 2021:

• Federal government: Authorized direct payment to PAs under Medicare
• Arkansas, Delaware, Illinois, Pennsylvania: Added one or more PAs to their medical boards
• Florida, Utah: Approved direct payment to PAs
• Tennessee, Wisconsin: Created a separate PA review board
• Utah, Wisconsin: Removed the relationship/agreement requirement (Wisconsin now requires 10,000 hours of practice to remove the relationship requirement)

North Central region

In Colorado, House Bill 1095 (HB1095) would have removed requirements for a legal relationship between a PA and a physician. Initially that would have happened after 3,000 hours of practice, although changing that to 5,000 hours has been a compromise measure. PAs changing specialties must collaborate for 2,000 hours, now negotiated to 3,000 hours.

HB1095 ultimately was not successful last year or this year, said Erika Miller, director of state advocacy and outreach for the AAPA. “But we do see it as a success, because in the 2022 session, we managed to get it passed in committee by a 10-to-1 vote,” she said. “It then moved to the full house and was not successful there.”

Ms. Miller said that South Dakota Senate Bill 134 would have removed the requirement for a legal PA/physician relationship after 1,040 hours, which is the requirement for nurse practitioners. “South Dakota had introduced similar legislation the year before, but also like Colorado, they went from not getting out of committee last year to making it to the senate floor this time,” she said.

In Wisconsin, the new PA-affiliated credentialing board began on April 1. It gives PAs the authority to license, discipline, and write regulations, Ms. Miller said.
 

South Central region

Arizona Senate Bill 1367 included direct pay, removed the relationship tether with a physician, and made each PA fully responsible for the care they provide. “The bill passed out of committee successfully but did not make it to a vote due to unexpected struggles between the Arizona medical society and PA chapter,” said Shannon Morey, senior director of state advocacy and outreach at the AAPA. “They are ready to go again next year.”

In Louisiana, Senate Bill 158 is a “strong” bill that addressed all the desired aspects of OTP, Ms. Morey said; “The legislation stands subject to call on the Senate floor, but it has been killed by the sponsor.”
 

Northeast region

Massachusetts Senate Bill 740 (S740) would remove the legal tether between PA and physician, said Carson Walker, senior director of state advocacy and outreach at the AAPA. “The committee decided to extend its time in committee until June,” he said. “By next month, we expect that the committee will schedule a hearing that includes S740, and we fully plan on submitting testimony.”

In New York, Senate Bill 9233 (S9233) would remove physician supervision after 3,600 hours of practice.

“Just about 10 days ago, sponsors were able to have S9233 introduced, which is the most succinct and, I think, the most effective OTP bill I have ever seen,” Mr. Walker said.

“S9233 says that after 3,600 hours a PA can practice without the supervision of a physician, and that’s all. There’s not a lot of time left in this session, but we are hopeful that it lays the groundwork for success next year.”

New Hampshire Senate Bill 228 has passed the legislature and is awaiting the governor’s signature. It will allow direct payment, make PAs responsible for the care they provide, and shift the physician-PA relationship from supervision to collaboration, Mr. Walker said.
 

Southeast region

Stephanie Radix, senior director of state advocacy and outreach at the AAPA, discussed North Carolina’s Senate Bill 345, which passed the Senate unanimously in 2021 and has been carried over to this year’s session. The bill defines team-based settings, eliminates the relationship tether, and establishes a supervised career entry interval of 4,000 clinical hours in the state.

The legislature is slated to adjourn June 30, Ms. Radix said: “We are very hopeful that we will get it across the finish line.”

In an interview, Mr. Bongiorno said that the AAPA’s overall advocacy progress is as expected.

“Optimal team practice is about allowing each practice to make that determination on how the team should work as a true collaboration,” he said. “The bottom line is that OTP would allow us to reach more patients, serve the community, and ensure that people are able to get healthcare, especially in underserved areas.”

A version of this article first appeared on Medscape.com.

INDIANAPOLIS – Recent legislative sessions in state legislative houses across the country have yielded progress toward codifying optimal team practice (OTP) into state law. That’s according to Phil Bongiorno, BA, senior vice president of advocacy and government relations at the American Academy of Physician Associates (AAPA), who spoke at the group’s annual meeting.

OTP refers to the AAPA’s goal of improving patient access to care and lessening administrative obligations by eliminating the legal requirement that there be a specific relationship between a PA, physician, or any other health care provider. This would allow a PA to practice to the full extent of their education, training, and experience, Mr. Bongiorno said.

The second tenet of OTP is to persuade states to create a separate majority PA board to regulate PAs. An alternative to this would be for states to add PAs and physicians who work with PAs to their medical or healing arts boards, he said.

Third, in an OTP environment, each state would authorize PAs to be eligible for direct payment by all public and private insurers. “We have seen that development at the federal level, as far as Medicare is concerned,” Mr. Bongiorno said. “Now, we’re focusing on making that happen in the individual states as well.”

According to Mr. Bongiorno, this year’s state advocacy priorities are to pursue new legislation in additional states, even as efforts continue to persuade state legislatures to act on carryover bills from the previous legislative session.

Mr. Bongiorno briefly summarized what he called “OTP successes” from 2021:

• Federal government: Authorized direct payment to PAs under Medicare
• Arkansas, Delaware, Illinois, Pennsylvania: Added one or more PAs to their medical boards
• Florida, Utah: Approved direct payment to PAs
• Tennessee, Wisconsin: Created a separate PA review board
• Utah, Wisconsin: Removed the relationship/agreement requirement (Wisconsin now requires 10,000 hours of practice to remove the relationship requirement)

North Central region

In Colorado, House Bill 1095 (HB1095) would have removed requirements for a legal relationship between a PA and a physician. Initially that would have happened after 3,000 hours of practice, although changing that to 5,000 hours has been a compromise measure. PAs changing specialties must collaborate for 2,000 hours, now negotiated to 3,000 hours.

HB1095 ultimately was not successful last year or this year, said Erika Miller, director of state advocacy and outreach for the AAPA. “But we do see it as a success, because in the 2022 session, we managed to get it passed in committee by a 10-to-1 vote,” she said. “It then moved to the full house and was not successful there.”

Ms. Miller said that South Dakota Senate Bill 134 would have removed the requirement for a legal PA/physician relationship after 1,040 hours, which is the requirement for nurse practitioners. “South Dakota had introduced similar legislation the year before, but also like Colorado, they went from not getting out of committee last year to making it to the senate floor this time,” she said.

In Wisconsin, the new PA-affiliated credentialing board began on April 1. It gives PAs the authority to license, discipline, and write regulations, Ms. Miller said.
 

South Central region

Arizona Senate Bill 1367 included direct pay, removed the relationship tether with a physician, and made each PA fully responsible for the care they provide. “The bill passed out of committee successfully but did not make it to a vote due to unexpected struggles between the Arizona medical society and PA chapter,” said Shannon Morey, senior director of state advocacy and outreach at the AAPA. “They are ready to go again next year.”

In Louisiana, Senate Bill 158 is a “strong” bill that addressed all the desired aspects of OTP, Ms. Morey said; “The legislation stands subject to call on the Senate floor, but it has been killed by the sponsor.”
 

Northeast region

Massachusetts Senate Bill 740 (S740) would remove the legal tether between PA and physician, said Carson Walker, senior director of state advocacy and outreach at the AAPA. “The committee decided to extend its time in committee until June,” he said. “By next month, we expect that the committee will schedule a hearing that includes S740, and we fully plan on submitting testimony.”

In New York, Senate Bill 9233 (S9233) would remove physician supervision after 3,600 hours of practice.

“Just about 10 days ago, sponsors were able to have S9233 introduced, which is the most succinct and, I think, the most effective OTP bill I have ever seen,” Mr. Walker said.

“S9233 says that after 3,600 hours a PA can practice without the supervision of a physician, and that’s all. There’s not a lot of time left in this session, but we are hopeful that it lays the groundwork for success next year.”

New Hampshire Senate Bill 228 has passed the legislature and is awaiting the governor’s signature. It will allow direct payment, make PAs responsible for the care they provide, and shift the physician-PA relationship from supervision to collaboration, Mr. Walker said.
 

Southeast region

Stephanie Radix, senior director of state advocacy and outreach at the AAPA, discussed North Carolina’s Senate Bill 345, which passed the Senate unanimously in 2021 and has been carried over to this year’s session. The bill defines team-based settings, eliminates the relationship tether, and establishes a supervised career entry interval of 4,000 clinical hours in the state.

The legislature is slated to adjourn June 30, Ms. Radix said: “We are very hopeful that we will get it across the finish line.”

In an interview, Mr. Bongiorno said that the AAPA’s overall advocacy progress is as expected.

“Optimal team practice is about allowing each practice to make that determination on how the team should work as a true collaboration,” he said. “The bottom line is that OTP would allow us to reach more patients, serve the community, and ensure that people are able to get healthcare, especially in underserved areas.”

A version of this article first appeared on Medscape.com.

INDIANAPOLIS – Recent legislative sessions in state legislative houses across the country have yielded progress toward codifying optimal team practice (OTP) into state law. That’s according to Phil Bongiorno, BA, senior vice president of advocacy and government relations at the American Academy of Physician Associates (AAPA), who spoke at the group’s annual meeting.

OTP refers to the AAPA’s goal of improving patient access to care and lessening administrative obligations by eliminating the legal requirement that there be a specific relationship between a PA, physician, or any other health care provider. This would allow a PA to practice to the full extent of their education, training, and experience, Mr. Bongiorno said.

The second tenet of OTP is to persuade states to create a separate majority PA board to regulate PAs. An alternative to this would be for states to add PAs and physicians who work with PAs to their medical or healing arts boards, he said.

Third, in an OTP environment, each state would authorize PAs to be eligible for direct payment by all public and private insurers. “We have seen that development at the federal level, as far as Medicare is concerned,” Mr. Bongiorno said. “Now, we’re focusing on making that happen in the individual states as well.”

According to Mr. Bongiorno, this year’s state advocacy priorities are to pursue new legislation in additional states, even as efforts continue to persuade state legislatures to act on carryover bills from the previous legislative session.

Mr. Bongiorno briefly summarized what he called “OTP successes” from 2021:

• Federal government: Authorized direct payment to PAs under Medicare
• Arkansas, Delaware, Illinois, Pennsylvania: Added one or more PAs to their medical boards
• Florida, Utah: Approved direct payment to PAs
• Tennessee, Wisconsin: Created a separate PA review board
• Utah, Wisconsin: Removed the relationship/agreement requirement (Wisconsin now requires 10,000 hours of practice to remove the relationship requirement)

North Central region

In Colorado, House Bill 1095 (HB1095) would have removed requirements for a legal relationship between a PA and a physician. Initially that would have happened after 3,000 hours of practice, although changing that to 5,000 hours has been a compromise measure. PAs changing specialties must collaborate for 2,000 hours, now negotiated to 3,000 hours.

HB1095 ultimately was not successful last year or this year, said Erika Miller, director of state advocacy and outreach for the AAPA. “But we do see it as a success, because in the 2022 session, we managed to get it passed in committee by a 10-to-1 vote,” she said. “It then moved to the full house and was not successful there.”

Ms. Miller said that South Dakota Senate Bill 134 would have removed the requirement for a legal PA/physician relationship after 1,040 hours, which is the requirement for nurse practitioners. “South Dakota had introduced similar legislation the year before, but also like Colorado, they went from not getting out of committee last year to making it to the senate floor this time,” she said.

In Wisconsin, the new PA-affiliated credentialing board began on April 1. It gives PAs the authority to license, discipline, and write regulations, Ms. Miller said.
 

South Central region

Arizona Senate Bill 1367 included direct pay, removed the relationship tether with a physician, and made each PA fully responsible for the care they provide. “The bill passed out of committee successfully but did not make it to a vote due to unexpected struggles between the Arizona medical society and PA chapter,” said Shannon Morey, senior director of state advocacy and outreach at the AAPA. “They are ready to go again next year.”

In Louisiana, Senate Bill 158 is a “strong” bill that addressed all the desired aspects of OTP, Ms. Morey said; “The legislation stands subject to call on the Senate floor, but it has been killed by the sponsor.”
 

Northeast region

Massachusetts Senate Bill 740 (S740) would remove the legal tether between PA and physician, said Carson Walker, senior director of state advocacy and outreach at the AAPA. “The committee decided to extend its time in committee until June,” he said. “By next month, we expect that the committee will schedule a hearing that includes S740, and we fully plan on submitting testimony.”

In New York, Senate Bill 9233 (S9233) would remove physician supervision after 3,600 hours of practice.

“Just about 10 days ago, sponsors were able to have S9233 introduced, which is the most succinct and, I think, the most effective OTP bill I have ever seen,” Mr. Walker said.

“S9233 says that after 3,600 hours a PA can practice without the supervision of a physician, and that’s all. There’s not a lot of time left in this session, but we are hopeful that it lays the groundwork for success next year.”

New Hampshire Senate Bill 228 has passed the legislature and is awaiting the governor’s signature. It will allow direct payment, make PAs responsible for the care they provide, and shift the physician-PA relationship from supervision to collaboration, Mr. Walker said.
 

Southeast region

Stephanie Radix, senior director of state advocacy and outreach at the AAPA, discussed North Carolina’s Senate Bill 345, which passed the Senate unanimously in 2021 and has been carried over to this year’s session. The bill defines team-based settings, eliminates the relationship tether, and establishes a supervised career entry interval of 4,000 clinical hours in the state.

The legislature is slated to adjourn June 30, Ms. Radix said: “We are very hopeful that we will get it across the finish line.”

In an interview, Mr. Bongiorno said that the AAPA’s overall advocacy progress is as expected.

“Optimal team practice is about allowing each practice to make that determination on how the team should work as a true collaboration,” he said. “The bottom line is that OTP would allow us to reach more patients, serve the community, and ensure that people are able to get healthcare, especially in underserved areas.”

A version of this article first appeared on Medscape.com.

Motherhood and dermatology residency are both full-time jobs. The thought that a woman must either be superhuman to succeed at both or that success at one must come at the expense of the other is antiquated. With careful navigation and sufficient support, these two roles can complement and heighten one another. The most recent Accreditation Council for Graduate Medical Education (ACGME) report showed that nearly 60% of dermatology residents are women,¹ with most women in training being of childbearing age. One study showed that female dermatologists were most likely to have children during residency (51% of those surveyed), despite residents reporting more barriers to childbearing at this career stage.² Trainees thinking of starting a family have many considerations to navigate: timing of pregnancy, maternity leave scheduling, breastfeeding while working, and planning for childcare. For the first time in the history of the specialty, most active dermatologists in practice are women.³ Thus, the future of dermatology requires supportive policies and resources for the successful navigation of these issues by today’s trainees.

Timing of Pregnancy

Timing of pregnancy can be a source of stress to the female dermatology resident. Barriers to childbearing during residency include the perception that women who have children during residency training are less committed to their jobs; concerns of overburdening fellow residents; and fear that residency may need to be extended, thereby delaying the ability to sit for the board examination.² However, the potential increased risk for infertility in delaying pregnancy adds to the stress of pregnancy planning. A 2016 survey of female physicians (N=327) showed that 24.1% of respondents who had attempted conception were diagnosed with infertility, with an average age at diagnosis of 33.7 years.⁴ This is higher than the national average, with the Centers for Disease Control and Prevention reporting that approximately 19% of women aged 15 to 49 years with no prior births experience infertility.⁵ In a 1992 survey of female physician residents (N=373) who gave birth during residency, 32% indicated that they would not recommend the experience to others; of the 68% who would recommend the experience, one-third encouraged timing delivery to occur in the last 2 months of residency due to benefits of continued insurance coverage, a decrease in clinic responsibilities, and the potential for extended maternity leave during hiatus between jobs.⁶ Although this may be a good strategy, studying and sitting for board examinations while caring for a newborn right after graduation may be overly difficult for some. The first year of residency was perceived as the most stressful time to be pregnant, with each subsequent year being less problematic.⁶ Planning pregnancy for delivery near the end of the second year and beginning of the third year of dermatology residency may be a reasonable choice.

Maternity Leave

The Family and Medical Leave Act entitles eligible employees of covered employers to take unpaid, job-protected leave, with 12 workweeks of leave in a 12-month period for the birth of a child and to care for the newborn child within 1 year of birth.⁷ The actual length of maternity leave taken by most surveyed female dermatologists (n=96) is shorter: 25% (24/96) took less than 4 weeks, 42.7% (41/96) took 4 to 8 weeks, 25% (24/96) took 9 to 12 weeks, and 7.3% (7/96) were able to take more than 12 weeks of maternity leave.²

The American Board of Dermatology implemented a new Resident Leave policy that went into effect July 1, 2021, stipulating that, within certain parameters, time spent away from training for family and parental leave would not exhaust vacation time or require an extension in training. Under this policy, absence from training exceeding 8 weeks (6 weeks leave, plus 2 weeks of vacation) in a given year should be approved only under exceptional circumstances and may necessitate additional training time to ensure that competency requirements are met.⁸ Although this policy is a step in the right direction, institutional policies still may vary. Dermatology residents planning to start a family during training should consider their plans for fellowship, as taking an extended maternity leave beyond 8 weeks may jeopardize a July fellowship start date.

Lactation and Residency

The American Academy of Pediatrics recommends exclusive breastfeeding for approximately 6 months, with continuation of breastfeeding for 1 year or longer as mutually desired by the mother and infant.⁹ Successful lactation and achieving breastfeeding goals can be difficult during medical training. A national cross-sectional survey of female residents (N=312) showed that the median total time of breastfeeding and pumping was 9 months, with 74% continuing after 6 months and 13% continuing past 12 months. Of those surveyed, 73% reported residency limited their ability to lactate, and 37% stopped prior to their desired goal.¹⁰ As of July 1, 2020, the ACGME requires that residency programs and sponsoring institutions provide clean and private facilities for lactation that have refrigeration capabilities, with proximity appropriate for safe patient care.¹¹ There has been a call to dermatology program leadership to support breastfeeding residents by providing sufficient time and space to pump; a breastfeeding resident will need a 20- to 30-minute break to express milk approximately every 3 hours during the work day.¹² One innovative initiative to meet the ACGME lactation requirement reported by the Kansas University Medical Center Graduate Medical Education program (Kansas City, Kansas) was the purchase of wearable breast pumps to loan to residents. The benefits of wearable breast pumps are that they are discreet and can allow mothers to express milk inconspicuously while working, can increase milk supply, require less set up and expression time than traditional pumps, and can allow the mother to manage time more efficiently.¹³ Breastfeeding plans and goals should be discussed with program leadership before return from leave to strategize and anticipate gaps in clinic scheduling to accommodate the lactating resident.

Planning for Childcare

Resident hours can be long and erratic, making choices for childcare difficult. In one survey of female residents, 61% of married or partnered respondents (n=447) were delaying childbearing, and 46% cited lack of access to childcare as a reason.¹⁴ Not all dermatology residents are fortunate enough to match to a program near family, but close family support can be an undeniable asset during childrearing and should be weighed heavily when ranking programs. Options for childcare include relying on a stay-at-home spouse or other family member, a live-in or live-out nanny, part-time babysitters, and daycare. It is crucial to have multiple layers and back-up options for childcare available at any given time when working as a resident. Even with a child enrolled in a full-time daycare and a live-in nanny, a daycare closure due to a COVID-19 exposure or sudden medical emergency in the nanny can still leave unpredicted holes in your childcare plan, leaving the resident to potentially miss work to fill the gap. A survey of residents at one institution showed that the most common backup childcare plan for situations in which either the child or the regular caregiver is ill is for the nontrainee parent or spouse to stay home (45%; n=101), with 25% of respondents staying home to care for a sick child themselves, which clearly has an impact on the hospital. The article proposed implementation of on-site or near-site childcare for residents with extended hours or a 24-hour emergency drop-in availability.¹⁵ One institution reported success with the development of a departmentally funded childcare supplementation stipend offered to residents to support daycare costs during the first 6 months of a baby’s life.¹⁶

Final Thoughts

Due to the competitiveness of the field, dermatology residents are by nature high performing and academically successful. For a high achiever, the idea of potentially disappointing faculty and colleagues by starting a family during residency can be guilt inducing. Concerns about one’s ability to adequately study the breadth of dermatology while simultaneously raising a child can be distressing; however, there are many ways in which motherhood can hone skills to become a better dermatology resident. Through motherhood one can enhance time management skills, increase efficiency, and improve rapport with pediatric patients and trust with their parents/guardians. A dermatology resident may be her own harshest critic, but it is time that the future generation of dermatologists become their own greatest advocates for establishing supportive policies and resources for the successful navigation of motherhood and dermatology residency.

Motherhood and dermatology residency are both full-time jobs. The thought that a woman must either be superhuman to succeed at both or that success at one must come at the expense of the other is antiquated. With careful navigation and sufficient support, these two roles can complement and heighten one another. The most recent Accreditation Council for Graduate Medical Education (ACGME) report showed that nearly 60% of dermatology residents are women,¹ with most women in training being of childbearing age. One study showed that female dermatologists were most likely to have children during residency (51% of those surveyed), despite residents reporting more barriers to childbearing at this career stage.² Trainees thinking of starting a family have many considerations to navigate: timing of pregnancy, maternity leave scheduling, breastfeeding while working, and planning for childcare. For the first time in the history of the specialty, most active dermatologists in practice are women.³ Thus, the future of dermatology requires supportive policies and resources for the successful navigation of these issues by today’s trainees.

Timing of Pregnancy

Timing of pregnancy can be a source of stress to the female dermatology resident. Barriers to childbearing during residency include the perception that women who have children during residency training are less committed to their jobs; concerns of overburdening fellow residents; and fear that residency may need to be extended, thereby delaying the ability to sit for the board examination.² However, the potential increased risk for infertility in delaying pregnancy adds to the stress of pregnancy planning. A 2016 survey of female physicians (N=327) showed that 24.1% of respondents who had attempted conception were diagnosed with infertility, with an average age at diagnosis of 33.7 years.⁴ This is higher than the national average, with the Centers for Disease Control and Prevention reporting that approximately 19% of women aged 15 to 49 years with no prior births experience infertility.⁵ In a 1992 survey of female physician residents (N=373) who gave birth during residency, 32% indicated that they would not recommend the experience to others; of the 68% who would recommend the experience, one-third encouraged timing delivery to occur in the last 2 months of residency due to benefits of continued insurance coverage, a decrease in clinic responsibilities, and the potential for extended maternity leave during hiatus between jobs.⁶ Although this may be a good strategy, studying and sitting for board examinations while caring for a newborn right after graduation may be overly difficult for some. The first year of residency was perceived as the most stressful time to be pregnant, with each subsequent year being less problematic.⁶ Planning pregnancy for delivery near the end of the second year and beginning of the third year of dermatology residency may be a reasonable choice.

Maternity Leave

The Family and Medical Leave Act entitles eligible employees of covered employers to take unpaid, job-protected leave, with 12 workweeks of leave in a 12-month period for the birth of a child and to care for the newborn child within 1 year of birth.⁷ The actual length of maternity leave taken by most surveyed female dermatologists (n=96) is shorter: 25% (24/96) took less than 4 weeks, 42.7% (41/96) took 4 to 8 weeks, 25% (24/96) took 9 to 12 weeks, and 7.3% (7/96) were able to take more than 12 weeks of maternity leave.²

The American Board of Dermatology implemented a new Resident Leave policy that went into effect July 1, 2021, stipulating that, within certain parameters, time spent away from training for family and parental leave would not exhaust vacation time or require an extension in training. Under this policy, absence from training exceeding 8 weeks (6 weeks leave, plus 2 weeks of vacation) in a given year should be approved only under exceptional circumstances and may necessitate additional training time to ensure that competency requirements are met.⁸ Although this policy is a step in the right direction, institutional policies still may vary. Dermatology residents planning to start a family during training should consider their plans for fellowship, as taking an extended maternity leave beyond 8 weeks may jeopardize a July fellowship start date.

Lactation and Residency

The American Academy of Pediatrics recommends exclusive breastfeeding for approximately 6 months, with continuation of breastfeeding for 1 year or longer as mutually desired by the mother and infant.⁹ Successful lactation and achieving breastfeeding goals can be difficult during medical training. A national cross-sectional survey of female residents (N=312) showed that the median total time of breastfeeding and pumping was 9 months, with 74% continuing after 6 months and 13% continuing past 12 months. Of those surveyed, 73% reported residency limited their ability to lactate, and 37% stopped prior to their desired goal.¹⁰ As of July 1, 2020, the ACGME requires that residency programs and sponsoring institutions provide clean and private facilities for lactation that have refrigeration capabilities, with proximity appropriate for safe patient care.¹¹ There has been a call to dermatology program leadership to support breastfeeding residents by providing sufficient time and space to pump; a breastfeeding resident will need a 20- to 30-minute break to express milk approximately every 3 hours during the work day.¹² One innovative initiative to meet the ACGME lactation requirement reported by the Kansas University Medical Center Graduate Medical Education program (Kansas City, Kansas) was the purchase of wearable breast pumps to loan to residents. The benefits of wearable breast pumps are that they are discreet and can allow mothers to express milk inconspicuously while working, can increase milk supply, require less set up and expression time than traditional pumps, and can allow the mother to manage time more efficiently.¹³ Breastfeeding plans and goals should be discussed with program leadership before return from leave to strategize and anticipate gaps in clinic scheduling to accommodate the lactating resident.

Planning for Childcare

Resident hours can be long and erratic, making choices for childcare difficult. In one survey of female residents, 61% of married or partnered respondents (n=447) were delaying childbearing, and 46% cited lack of access to childcare as a reason.¹⁴ Not all dermatology residents are fortunate enough to match to a program near family, but close family support can be an undeniable asset during childrearing and should be weighed heavily when ranking programs. Options for childcare include relying on a stay-at-home spouse or other family member, a live-in or live-out nanny, part-time babysitters, and daycare. It is crucial to have multiple layers and back-up options for childcare available at any given time when working as a resident. Even with a child enrolled in a full-time daycare and a live-in nanny, a daycare closure due to a COVID-19 exposure or sudden medical emergency in the nanny can still leave unpredicted holes in your childcare plan, leaving the resident to potentially miss work to fill the gap. A survey of residents at one institution showed that the most common backup childcare plan for situations in which either the child or the regular caregiver is ill is for the nontrainee parent or spouse to stay home (45%; n=101), with 25% of respondents staying home to care for a sick child themselves, which clearly has an impact on the hospital. The article proposed implementation of on-site or near-site childcare for residents with extended hours or a 24-hour emergency drop-in availability.¹⁵ One institution reported success with the development of a departmentally funded childcare supplementation stipend offered to residents to support daycare costs during the first 6 months of a baby’s life.¹⁶

Final Thoughts

Due to the competitiveness of the field, dermatology residents are by nature high performing and academically successful. For a high achiever, the idea of potentially disappointing faculty and colleagues by starting a family during residency can be guilt inducing. Concerns about one’s ability to adequately study the breadth of dermatology while simultaneously raising a child can be distressing; however, there are many ways in which motherhood can hone skills to become a better dermatology resident. Through motherhood one can enhance time management skills, increase efficiency, and improve rapport with pediatric patients and trust with their parents/guardians. A dermatology resident may be her own harshest critic, but it is time that the future generation of dermatologists become their own greatest advocates for establishing supportive policies and resources for the successful navigation of motherhood and dermatology residency.

Motherhood and dermatology residency are both full-time jobs. The thought that a woman must either be superhuman to succeed at both or that success at one must come at the expense of the other is antiquated. With careful navigation and sufficient support, these two roles can complement and heighten one another. The most recent Accreditation Council for Graduate Medical Education (ACGME) report showed that nearly 60% of dermatology residents are women,¹ with most women in training being of childbearing age. One study showed that female dermatologists were most likely to have children during residency (51% of those surveyed), despite residents reporting more barriers to childbearing at this career stage.² Trainees thinking of starting a family have many considerations to navigate: timing of pregnancy, maternity leave scheduling, breastfeeding while working, and planning for childcare. For the first time in the history of the specialty, most active dermatologists in practice are women.³ Thus, the future of dermatology requires supportive policies and resources for the successful navigation of these issues by today’s trainees.

Timing of Pregnancy

Timing of pregnancy can be a source of stress to the female dermatology resident. Barriers to childbearing during residency include the perception that women who have children during residency training are less committed to their jobs; concerns of overburdening fellow residents; and fear that residency may need to be extended, thereby delaying the ability to sit for the board examination.² However, the potential increased risk for infertility in delaying pregnancy adds to the stress of pregnancy planning. A 2016 survey of female physicians (N=327) showed that 24.1% of respondents who had attempted conception were diagnosed with infertility, with an average age at diagnosis of 33.7 years.⁴ This is higher than the national average, with the Centers for Disease Control and Prevention reporting that approximately 19% of women aged 15 to 49 years with no prior births experience infertility.⁵ In a 1992 survey of female physician residents (N=373) who gave birth during residency, 32% indicated that they would not recommend the experience to others; of the 68% who would recommend the experience, one-third encouraged timing delivery to occur in the last 2 months of residency due to benefits of continued insurance coverage, a decrease in clinic responsibilities, and the potential for extended maternity leave during hiatus between jobs.⁶ Although this may be a good strategy, studying and sitting for board examinations while caring for a newborn right after graduation may be overly difficult for some. The first year of residency was perceived as the most stressful time to be pregnant, with each subsequent year being less problematic.⁶ Planning pregnancy for delivery near the end of the second year and beginning of the third year of dermatology residency may be a reasonable choice.

Maternity Leave

The Family and Medical Leave Act entitles eligible employees of covered employers to take unpaid, job-protected leave, with 12 workweeks of leave in a 12-month period for the birth of a child and to care for the newborn child within 1 year of birth.⁷ The actual length of maternity leave taken by most surveyed female dermatologists (n=96) is shorter: 25% (24/96) took less than 4 weeks, 42.7% (41/96) took 4 to 8 weeks, 25% (24/96) took 9 to 12 weeks, and 7.3% (7/96) were able to take more than 12 weeks of maternity leave.²

The American Board of Dermatology implemented a new Resident Leave policy that went into effect July 1, 2021, stipulating that, within certain parameters, time spent away from training for family and parental leave would not exhaust vacation time or require an extension in training. Under this policy, absence from training exceeding 8 weeks (6 weeks leave, plus 2 weeks of vacation) in a given year should be approved only under exceptional circumstances and may necessitate additional training time to ensure that competency requirements are met.⁸ Although this policy is a step in the right direction, institutional policies still may vary. Dermatology residents planning to start a family during training should consider their plans for fellowship, as taking an extended maternity leave beyond 8 weeks may jeopardize a July fellowship start date.

Lactation and Residency

The American Academy of Pediatrics recommends exclusive breastfeeding for approximately 6 months, with continuation of breastfeeding for 1 year or longer as mutually desired by the mother and infant.⁹ Successful lactation and achieving breastfeeding goals can be difficult during medical training. A national cross-sectional survey of female residents (N=312) showed that the median total time of breastfeeding and pumping was 9 months, with 74% continuing after 6 months and 13% continuing past 12 months. Of those surveyed, 73% reported residency limited their ability to lactate, and 37% stopped prior to their desired goal.¹⁰ As of July 1, 2020, the ACGME requires that residency programs and sponsoring institutions provide clean and private facilities for lactation that have refrigeration capabilities, with proximity appropriate for safe patient care.¹¹ There has been a call to dermatology program leadership to support breastfeeding residents by providing sufficient time and space to pump; a breastfeeding resident will need a 20- to 30-minute break to express milk approximately every 3 hours during the work day.¹² One innovative initiative to meet the ACGME lactation requirement reported by the Kansas University Medical Center Graduate Medical Education program (Kansas City, Kansas) was the purchase of wearable breast pumps to loan to residents. The benefits of wearable breast pumps are that they are discreet and can allow mothers to express milk inconspicuously while working, can increase milk supply, require less set up and expression time than traditional pumps, and can allow the mother to manage time more efficiently.¹³ Breastfeeding plans and goals should be discussed with program leadership before return from leave to strategize and anticipate gaps in clinic scheduling to accommodate the lactating resident.

Planning for Childcare

Resident hours can be long and erratic, making choices for childcare difficult. In one survey of female residents, 61% of married or partnered respondents (n=447) were delaying childbearing, and 46% cited lack of access to childcare as a reason.¹⁴ Not all dermatology residents are fortunate enough to match to a program near family, but close family support can be an undeniable asset during childrearing and should be weighed heavily when ranking programs. Options for childcare include relying on a stay-at-home spouse or other family member, a live-in or live-out nanny, part-time babysitters, and daycare. It is crucial to have multiple layers and back-up options for childcare available at any given time when working as a resident. Even with a child enrolled in a full-time daycare and a live-in nanny, a daycare closure due to a COVID-19 exposure or sudden medical emergency in the nanny can still leave unpredicted holes in your childcare plan, leaving the resident to potentially miss work to fill the gap. A survey of residents at one institution showed that the most common backup childcare plan for situations in which either the child or the regular caregiver is ill is for the nontrainee parent or spouse to stay home (45%; n=101), with 25% of respondents staying home to care for a sick child themselves, which clearly has an impact on the hospital. The article proposed implementation of on-site or near-site childcare for residents with extended hours or a 24-hour emergency drop-in availability.¹⁵ One institution reported success with the development of a departmentally funded childcare supplementation stipend offered to residents to support daycare costs during the first 6 months of a baby’s life.¹⁶

Final Thoughts

Due to the competitiveness of the field, dermatology residents are by nature high performing and academically successful. For a high achiever, the idea of potentially disappointing faculty and colleagues by starting a family during residency can be guilt inducing. Concerns about one’s ability to adequately study the breadth of dermatology while simultaneously raising a child can be distressing; however, there are many ways in which motherhood can hone skills to become a better dermatology resident. Through motherhood one can enhance time management skills, increase efficiency, and improve rapport with pediatric patients and trust with their parents/guardians. A dermatology resident may be her own harshest critic, but it is time that the future generation of dermatologists become their own greatest advocates for establishing supportive policies and resources for the successful navigation of motherhood and dermatology residency.

In states that adopted Medicaid expansion following the implementation of the Affordable Care Act (ACA), patients with cancer have improved 2-year overall survival rates, compared with patients in states that did not adopt the expansion.

The finding comes from an American Cancer Society study of more than 2 million patients with newly diagnosed cancer, published online in the Journal of the National Cancer Institute.

The analysis also showed that the evidence was strongest for malignancies with poor prognosis such as lung, pancreatic, and liver cancer, and also for colorectal cancer.

Importantly, improvements in survival were larger in non-Hispanic Black patients and individuals residing in rural areas, suggesting there was a narrowing of disparities in cancer survival by race and rurality.

“Our findings provide further evidence of the importance of expanding Medicaid eligibility in all states, particularly considering the economic crisis and health care disruptions caused by the COVID-19 pandemic,” said lead author Xuesong Han, PhD, scientific director of health services research at the American Cancer Society, in a statement. “What’s encouraging is the American Rescue Plan Act of 2021 provides new incentives for Medicaid expansion in states that have yet to increase eligibility.”

The ACA provided states with incentives to expand Medicaid eligibility to all low-income adults under 138% federal poverty level, regardless of parental status.

As of last month, just 12 states have not yet opted for Medicaid expansion, even though the American Rescue Plan Act of 2021 provides new incentives for those remaining jurisdictions. But to date, none of the remaining states have taken advantage of these new incentives.

An interactive map showing the status of Medicare expansion by state is available here. The 12 states that have not adopted Medicare expansion (as of April) are Alabama, Florida, Georgia, Kansas, Mississippi, North Carolina, South Carolina, South Dakota, Tennessee, Texas, Wisconsin, and Wyoming.  

The benefit of Medicaid expansion on cancer outcomes has already been observed in other studies. The first study to show a survival benefit was presented at the 2020 American Society of Clinical Oncology annual meeting. That analysis showed that cancer mortality declined by 29% in states that expanded Medicaid and by 25% in those that did not. The authors also noted that the greatest mortality benefit was observed in Hispanic patients.
 

Improved survival with expansion

In the current paper, Dr. Han and colleagues used population-based cancer registries from 42 states and compared data on patients aged 18-62 years who were diagnosed with cancer in a period of 2 years before (2010-2012) and after (2014-2016) ACA Medicaid expansion. They were followed through Sept. 30, 2013, and Dec. 31, 2017, respectively.

The analysis involved a total of 2.5 million patients, of whom 1.52 million lived in states that adopted Medicaid expansion and compared with 1 million patients were in states that did not.

Patients with grouped by sex, race and ethnicity, census tract-level poverty, and rurality. The authors note that non-Hispanic Black patients and those from high poverty areas and nonmetropolitan areas were disproportionately represented in nonexpansion states. 

During the 2-year follow-up period, a total of 453,487 deaths occurred (257,950 in expansion states and 195,537 in nonexpansion states).

Overall, patients in expansion states generally had better survival versus those in nonexpansion states, the authors comment. However, for most cancer types, overall survival improved after the ACA for both groups of states.

The 2-year overall survival increased from 80.6% before the ACA to 82.2% post ACA in expansion states and from 78.7% to 80% in nonexpansion states.

This extrapolated to net increase of 0.44 percentage points in expansion states after adjusting for sociodemographic factors. By cancer site, the net increase was greater for colorectal cancer, lung cancer, non-Hodgkin’s lymphoma, pancreatic cancer, and liver cancer.

For Hispanic patients, 2-year survival also increased but was similar in expansion and nonexpansion states, and little net change was associated with Medicaid expansion.

“Our study shows that the increase was largely driven by improvements in survival for cancer types with poor prognosis, suggesting improved access to timely and effective treatments,” said Dr. Han. “It adds to accumulating evidence of the multiple benefits of Medicaid expansion.”

A version of this article first appeared on Medscape.com.

In states that adopted Medicaid expansion following the implementation of the Affordable Care Act (ACA), patients with cancer have improved 2-year overall survival rates, compared with patients in states that did not adopt the expansion.

The finding comes from an American Cancer Society study of more than 2 million patients with newly diagnosed cancer, published online in the Journal of the National Cancer Institute.

The analysis also showed that the evidence was strongest for malignancies with poor prognosis such as lung, pancreatic, and liver cancer, and also for colorectal cancer.

Importantly, improvements in survival were larger in non-Hispanic Black patients and individuals residing in rural areas, suggesting there was a narrowing of disparities in cancer survival by race and rurality.

“Our findings provide further evidence of the importance of expanding Medicaid eligibility in all states, particularly considering the economic crisis and health care disruptions caused by the COVID-19 pandemic,” said lead author Xuesong Han, PhD, scientific director of health services research at the American Cancer Society, in a statement. “What’s encouraging is the American Rescue Plan Act of 2021 provides new incentives for Medicaid expansion in states that have yet to increase eligibility.”

The ACA provided states with incentives to expand Medicaid eligibility to all low-income adults under 138% federal poverty level, regardless of parental status.

As of last month, just 12 states have not yet opted for Medicaid expansion, even though the American Rescue Plan Act of 2021 provides new incentives for those remaining jurisdictions. But to date, none of the remaining states have taken advantage of these new incentives.

An interactive map showing the status of Medicare expansion by state is available here. The 12 states that have not adopted Medicare expansion (as of April) are Alabama, Florida, Georgia, Kansas, Mississippi, North Carolina, South Carolina, South Dakota, Tennessee, Texas, Wisconsin, and Wyoming.  

The benefit of Medicaid expansion on cancer outcomes has already been observed in other studies. The first study to show a survival benefit was presented at the 2020 American Society of Clinical Oncology annual meeting. That analysis showed that cancer mortality declined by 29% in states that expanded Medicaid and by 25% in those that did not. The authors also noted that the greatest mortality benefit was observed in Hispanic patients.
 

Improved survival with expansion

In the current paper, Dr. Han and colleagues used population-based cancer registries from 42 states and compared data on patients aged 18-62 years who were diagnosed with cancer in a period of 2 years before (2010-2012) and after (2014-2016) ACA Medicaid expansion. They were followed through Sept. 30, 2013, and Dec. 31, 2017, respectively.

The analysis involved a total of 2.5 million patients, of whom 1.52 million lived in states that adopted Medicaid expansion and compared with 1 million patients were in states that did not.

Patients with grouped by sex, race and ethnicity, census tract-level poverty, and rurality. The authors note that non-Hispanic Black patients and those from high poverty areas and nonmetropolitan areas were disproportionately represented in nonexpansion states. 

During the 2-year follow-up period, a total of 453,487 deaths occurred (257,950 in expansion states and 195,537 in nonexpansion states).

Overall, patients in expansion states generally had better survival versus those in nonexpansion states, the authors comment. However, for most cancer types, overall survival improved after the ACA for both groups of states.

The 2-year overall survival increased from 80.6% before the ACA to 82.2% post ACA in expansion states and from 78.7% to 80% in nonexpansion states.

This extrapolated to net increase of 0.44 percentage points in expansion states after adjusting for sociodemographic factors. By cancer site, the net increase was greater for colorectal cancer, lung cancer, non-Hodgkin’s lymphoma, pancreatic cancer, and liver cancer.

For Hispanic patients, 2-year survival also increased but was similar in expansion and nonexpansion states, and little net change was associated with Medicaid expansion.

“Our study shows that the increase was largely driven by improvements in survival for cancer types with poor prognosis, suggesting improved access to timely and effective treatments,” said Dr. Han. “It adds to accumulating evidence of the multiple benefits of Medicaid expansion.”

A version of this article first appeared on Medscape.com.

In states that adopted Medicaid expansion following the implementation of the Affordable Care Act (ACA), patients with cancer have improved 2-year overall survival rates, compared with patients in states that did not adopt the expansion.

The finding comes from an American Cancer Society study of more than 2 million patients with newly diagnosed cancer, published online in the Journal of the National Cancer Institute.

The analysis also showed that the evidence was strongest for malignancies with poor prognosis such as lung, pancreatic, and liver cancer, and also for colorectal cancer.

Importantly, improvements in survival were larger in non-Hispanic Black patients and individuals residing in rural areas, suggesting there was a narrowing of disparities in cancer survival by race and rurality.

“Our findings provide further evidence of the importance of expanding Medicaid eligibility in all states, particularly considering the economic crisis and health care disruptions caused by the COVID-19 pandemic,” said lead author Xuesong Han, PhD, scientific director of health services research at the American Cancer Society, in a statement. “What’s encouraging is the American Rescue Plan Act of 2021 provides new incentives for Medicaid expansion in states that have yet to increase eligibility.”

The ACA provided states with incentives to expand Medicaid eligibility to all low-income adults under 138% federal poverty level, regardless of parental status.

As of last month, just 12 states have not yet opted for Medicaid expansion, even though the American Rescue Plan Act of 2021 provides new incentives for those remaining jurisdictions. But to date, none of the remaining states have taken advantage of these new incentives.

An interactive map showing the status of Medicare expansion by state is available here. The 12 states that have not adopted Medicare expansion (as of April) are Alabama, Florida, Georgia, Kansas, Mississippi, North Carolina, South Carolina, South Dakota, Tennessee, Texas, Wisconsin, and Wyoming.  

The benefit of Medicaid expansion on cancer outcomes has already been observed in other studies. The first study to show a survival benefit was presented at the 2020 American Society of Clinical Oncology annual meeting. That analysis showed that cancer mortality declined by 29% in states that expanded Medicaid and by 25% in those that did not. The authors also noted that the greatest mortality benefit was observed in Hispanic patients.
 

Improved survival with expansion

In the current paper, Dr. Han and colleagues used population-based cancer registries from 42 states and compared data on patients aged 18-62 years who were diagnosed with cancer in a period of 2 years before (2010-2012) and after (2014-2016) ACA Medicaid expansion. They were followed through Sept. 30, 2013, and Dec. 31, 2017, respectively.

The analysis involved a total of 2.5 million patients, of whom 1.52 million lived in states that adopted Medicaid expansion and compared with 1 million patients were in states that did not.

Patients with grouped by sex, race and ethnicity, census tract-level poverty, and rurality. The authors note that non-Hispanic Black patients and those from high poverty areas and nonmetropolitan areas were disproportionately represented in nonexpansion states. 

During the 2-year follow-up period, a total of 453,487 deaths occurred (257,950 in expansion states and 195,537 in nonexpansion states).

Overall, patients in expansion states generally had better survival versus those in nonexpansion states, the authors comment. However, for most cancer types, overall survival improved after the ACA for both groups of states.

The 2-year overall survival increased from 80.6% before the ACA to 82.2% post ACA in expansion states and from 78.7% to 80% in nonexpansion states.

This extrapolated to net increase of 0.44 percentage points in expansion states after adjusting for sociodemographic factors. By cancer site, the net increase was greater for colorectal cancer, lung cancer, non-Hodgkin’s lymphoma, pancreatic cancer, and liver cancer.

For Hispanic patients, 2-year survival also increased but was similar in expansion and nonexpansion states, and little net change was associated with Medicaid expansion.

“Our study shows that the increase was largely driven by improvements in survival for cancer types with poor prognosis, suggesting improved access to timely and effective treatments,” said Dr. Han. “It adds to accumulating evidence of the multiple benefits of Medicaid expansion.”

A version of this article first appeared on Medscape.com.

In April, the Iowa Supreme Court dismissed a knotty claim against a local doctor and hospital accused of concealing a woman’s renal cancer, according to a story in the Iowa Capital Dispatch, among other news outlets.

In 2004, Linda Berry visited Mercy Medical Center in Cedar Rapids for an unspecified ailment. At the hospital, Ms. Berry underwent a CT scan, which revealed a benign cyst on her right kidney. According to the suit later filed by her family, she was not informed about the growth during this visit — nor during four successive visits to the same hospital over the next decade.

The first of these four visits occurred in 2006, when Ms. Berry was again seen at Mercy, this time for a urinary tract infection. Despite undergoing a second renal scan, Ms. Berry was not informed of the mass on her right kidney.

Three years later, in October 2009, she arrived with her daughter at the Mercy emergency department (ED) complaining of abdominal pain. She was examined by Paul Grossmann, MD, a general surgeon. Ms. Berry underwent an abdominal scan that showed her renal abnormality. Dr. Grossmann diagnosed her as having constipation and released her from the ED. According to the family, he made no mention of the mass on her right kidney.

En route home, however, Ms. Berry and her daughter received a call from a resident under Dr. Grossmann’s supervision. Returning to the hospital, Ms. Berry learned that her constipation was actually colitis. She was prescribed an antibiotic and was again released from the ED. Her post-release instructions made no mention of the now larger mass on her kidney.

Two days later, still complaining of abdominal pain, Ms. Berry returned to the Mercy ED. Examined by another ED doctor, she underwent a fourth CT scan, which also showed the kidney mass. A radiology report urged Dr. Grossmann, her previous physician, to pursue the matter in order to rule out renal cancer. Dr. Grossmann followed up with Berry’s primary care doctor. In doing so, though, he mentioned only the patient’s ongoing colitis, not her kidney mass, according to the plaintiffs’ claim.

In 2016, following a fall, Ms. Berry returned yet again to the Mercy ED, this time with a broken arm. During her treatment, she underwent a fifth CT scan, which revealed the same kidney mass. This time, though, a discharge nurse mentioned the abnormality to Ms. Berry — allegedly the first time in more than a decade that a medical professional had alerted her to the potential problem.

The alert may have been too late, however. Ms. Berry was diagnosed shortly thereafter with metastatic renal cell carcinoma. She died on May 22, 2019.

A version of this article first appeared on Medscape.com.

In April, the Iowa Supreme Court dismissed a knotty claim against a local doctor and hospital accused of concealing a woman’s renal cancer, according to a story in the Iowa Capital Dispatch, among other news outlets.

In 2004, Linda Berry visited Mercy Medical Center in Cedar Rapids for an unspecified ailment. At the hospital, Ms. Berry underwent a CT scan, which revealed a benign cyst on her right kidney. According to the suit later filed by her family, she was not informed about the growth during this visit — nor during four successive visits to the same hospital over the next decade.

The first of these four visits occurred in 2006, when Ms. Berry was again seen at Mercy, this time for a urinary tract infection. Despite undergoing a second renal scan, Ms. Berry was not informed of the mass on her right kidney.

Three years later, in October 2009, she arrived with her daughter at the Mercy emergency department (ED) complaining of abdominal pain. She was examined by Paul Grossmann, MD, a general surgeon. Ms. Berry underwent an abdominal scan that showed her renal abnormality. Dr. Grossmann diagnosed her as having constipation and released her from the ED. According to the family, he made no mention of the mass on her right kidney.

En route home, however, Ms. Berry and her daughter received a call from a resident under Dr. Grossmann’s supervision. Returning to the hospital, Ms. Berry learned that her constipation was actually colitis. She was prescribed an antibiotic and was again released from the ED. Her post-release instructions made no mention of the now larger mass on her kidney.

Two days later, still complaining of abdominal pain, Ms. Berry returned to the Mercy ED. Examined by another ED doctor, she underwent a fourth CT scan, which also showed the kidney mass. A radiology report urged Dr. Grossmann, her previous physician, to pursue the matter in order to rule out renal cancer. Dr. Grossmann followed up with Berry’s primary care doctor. In doing so, though, he mentioned only the patient’s ongoing colitis, not her kidney mass, according to the plaintiffs’ claim.

In 2016, following a fall, Ms. Berry returned yet again to the Mercy ED, this time with a broken arm. During her treatment, she underwent a fifth CT scan, which revealed the same kidney mass. This time, though, a discharge nurse mentioned the abnormality to Ms. Berry — allegedly the first time in more than a decade that a medical professional had alerted her to the potential problem.

The alert may have been too late, however. Ms. Berry was diagnosed shortly thereafter with metastatic renal cell carcinoma. She died on May 22, 2019.

A version of this article first appeared on Medscape.com.

In April, the Iowa Supreme Court dismissed a knotty claim against a local doctor and hospital accused of concealing a woman’s renal cancer, according to a story in the Iowa Capital Dispatch, among other news outlets.

In 2004, Linda Berry visited Mercy Medical Center in Cedar Rapids for an unspecified ailment. At the hospital, Ms. Berry underwent a CT scan, which revealed a benign cyst on her right kidney. According to the suit later filed by her family, she was not informed about the growth during this visit — nor during four successive visits to the same hospital over the next decade.

The first of these four visits occurred in 2006, when Ms. Berry was again seen at Mercy, this time for a urinary tract infection. Despite undergoing a second renal scan, Ms. Berry was not informed of the mass on her right kidney.

Three years later, in October 2009, she arrived with her daughter at the Mercy emergency department (ED) complaining of abdominal pain. She was examined by Paul Grossmann, MD, a general surgeon. Ms. Berry underwent an abdominal scan that showed her renal abnormality. Dr. Grossmann diagnosed her as having constipation and released her from the ED. According to the family, he made no mention of the mass on her right kidney.

En route home, however, Ms. Berry and her daughter received a call from a resident under Dr. Grossmann’s supervision. Returning to the hospital, Ms. Berry learned that her constipation was actually colitis. She was prescribed an antibiotic and was again released from the ED. Her post-release instructions made no mention of the now larger mass on her kidney.

Two days later, still complaining of abdominal pain, Ms. Berry returned to the Mercy ED. Examined by another ED doctor, she underwent a fourth CT scan, which also showed the kidney mass. A radiology report urged Dr. Grossmann, her previous physician, to pursue the matter in order to rule out renal cancer. Dr. Grossmann followed up with Berry’s primary care doctor. In doing so, though, he mentioned only the patient’s ongoing colitis, not her kidney mass, according to the plaintiffs’ claim.

In 2016, following a fall, Ms. Berry returned yet again to the Mercy ED, this time with a broken arm. During her treatment, she underwent a fifth CT scan, which revealed the same kidney mass. This time, though, a discharge nurse mentioned the abnormality to Ms. Berry — allegedly the first time in more than a decade that a medical professional had alerted her to the potential problem.

The alert may have been too late, however. Ms. Berry was diagnosed shortly thereafter with metastatic renal cell carcinoma. She died on May 22, 2019.

A version of this article first appeared on Medscape.com.