Editorial

Primary care providers play a crucial role in cancer control, including screening and follow-up.^1,2 In particular, they are often responsible for performing the initial screening and, when necessary, discussing appropriate treatment options. However, cancer screening practices in primary care can vary significantly, leading to disparities in access to these services.³

See related article

Arvizo and Mahdi,⁴ in this issue of the Journal, discuss disparities in cervical cancer screening, noting that African American women have a higher risk of developing and dying of cervical cancer than white women, possibly because they are diagnosed at a later stage and have lower stage-specific survival rates. The authors state that equal access to healthcare may help mitigate these factors, and they also discuss how primary care providers can reduce these disparities.

PRIORITIZING CERVICAL CANCER SCREENING

Even in patients who have access to regular primary care, other barriers to cancer screening may exist. A 2014 study used self-reported data from the Behavioral Risk Factor Surveillance System survey to assess barriers to cervical cancer screening in older women (ages 40 to 65) who reported having health insurance and a personal healthcare provider.⁵ Those who were never or rarely screened for cervical cancer were more likely than those who were regularly screened to have a chronic condition, such as heart disease, chronic obstructive pulmonary disease, arthritis, depression, kidney disease, or diabetes.

This finding suggests that cancer screening may be a low priority during an adult primary care visit in which multiple chronic diseases must be addressed. To reduce disparities in cancer screening, primary care systems need to be designed to optimize delivery of preventive care and disease management using a team approach.

SYSTEMATIC FOLLOW-UP

Arvizo and Mahdi also discuss the follow-up of abnormal screening Papanicolaou (Pap) smears. While appropriate follow-up is a key factor in the management of cervical dysplasia, follow-up rates vary among African American women. System-level interventions such as the use of an electronic medical record-based tracking system in primary care settings⁶ with established protocols for follow-up may be effective.

But even with such systems in place, patients may face psychosocial barriers (eg, lack of health literacy, distress after receiving an abnormal cervical cytology test result⁷) that prevent them from seeking additional care. To improve follow-up rates, providers must be aware of these barriers and know how to address them through effective communication.

VACCINATION FOR HPV

Finally, the association between human papilloma virus (HPV) infection and cervical cancer makes HPV vaccination a crucial step in cervical cancer prevention. Continued provider education regarding HPV vaccination can improve knowledge about the HPV vaccine,⁸ as well as improve vaccination rates.⁹ The recent approval of a 2-dose vaccine schedule for younger girls¹⁰ may also help improve vaccine series completion rates.

The authors also suggest that primary care providers counsel all patients about risk factors for cervical cancer, including unsafe sex practices and tobacco use.

OPTIMIZING SCREENING AND PREVENTION

I commend the authors for their discussion of cervical cancer disparities and for raising awareness of the important role primary care providers play in reducing these disparities. Improving cervical cancer screening rates and follow-up will require providers and patients to be aware of cervical cancer risk factors. Further, system-level practice interventions will optimize primary care providers’ ability to engage patients in cancer screening conversations and ensure timely follow-up of screening tests.

Primary care providers play a crucial role in cancer control, including screening and follow-up.^1,2 In particular, they are often responsible for performing the initial screening and, when necessary, discussing appropriate treatment options. However, cancer screening practices in primary care can vary significantly, leading to disparities in access to these services.³

See related article

Arvizo and Mahdi,⁴ in this issue of the Journal, discuss disparities in cervical cancer screening, noting that African American women have a higher risk of developing and dying of cervical cancer than white women, possibly because they are diagnosed at a later stage and have lower stage-specific survival rates. The authors state that equal access to healthcare may help mitigate these factors, and they also discuss how primary care providers can reduce these disparities.

PRIORITIZING CERVICAL CANCER SCREENING

Even in patients who have access to regular primary care, other barriers to cancer screening may exist. A 2014 study used self-reported data from the Behavioral Risk Factor Surveillance System survey to assess barriers to cervical cancer screening in older women (ages 40 to 65) who reported having health insurance and a personal healthcare provider.⁵ Those who were never or rarely screened for cervical cancer were more likely than those who were regularly screened to have a chronic condition, such as heart disease, chronic obstructive pulmonary disease, arthritis, depression, kidney disease, or diabetes.

This finding suggests that cancer screening may be a low priority during an adult primary care visit in which multiple chronic diseases must be addressed. To reduce disparities in cancer screening, primary care systems need to be designed to optimize delivery of preventive care and disease management using a team approach.

SYSTEMATIC FOLLOW-UP

Arvizo and Mahdi also discuss the follow-up of abnormal screening Papanicolaou (Pap) smears. While appropriate follow-up is a key factor in the management of cervical dysplasia, follow-up rates vary among African American women. System-level interventions such as the use of an electronic medical record-based tracking system in primary care settings⁶ with established protocols for follow-up may be effective.

But even with such systems in place, patients may face psychosocial barriers (eg, lack of health literacy, distress after receiving an abnormal cervical cytology test result⁷) that prevent them from seeking additional care. To improve follow-up rates, providers must be aware of these barriers and know how to address them through effective communication.

VACCINATION FOR HPV

Finally, the association between human papilloma virus (HPV) infection and cervical cancer makes HPV vaccination a crucial step in cervical cancer prevention. Continued provider education regarding HPV vaccination can improve knowledge about the HPV vaccine,⁸ as well as improve vaccination rates.⁹ The recent approval of a 2-dose vaccine schedule for younger girls¹⁰ may also help improve vaccine series completion rates.

The authors also suggest that primary care providers counsel all patients about risk factors for cervical cancer, including unsafe sex practices and tobacco use.

OPTIMIZING SCREENING AND PREVENTION

I commend the authors for their discussion of cervical cancer disparities and for raising awareness of the important role primary care providers play in reducing these disparities. Improving cervical cancer screening rates and follow-up will require providers and patients to be aware of cervical cancer risk factors. Further, system-level practice interventions will optimize primary care providers’ ability to engage patients in cancer screening conversations and ensure timely follow-up of screening tests.

Primary care providers play a crucial role in cancer control, including screening and follow-up.^1,2 In particular, they are often responsible for performing the initial screening and, when necessary, discussing appropriate treatment options. However, cancer screening practices in primary care can vary significantly, leading to disparities in access to these services.³

See related article

Arvizo and Mahdi,⁴ in this issue of the Journal, discuss disparities in cervical cancer screening, noting that African American women have a higher risk of developing and dying of cervical cancer than white women, possibly because they are diagnosed at a later stage and have lower stage-specific survival rates. The authors state that equal access to healthcare may help mitigate these factors, and they also discuss how primary care providers can reduce these disparities.

PRIORITIZING CERVICAL CANCER SCREENING

Even in patients who have access to regular primary care, other barriers to cancer screening may exist. A 2014 study used self-reported data from the Behavioral Risk Factor Surveillance System survey to assess barriers to cervical cancer screening in older women (ages 40 to 65) who reported having health insurance and a personal healthcare provider.⁵ Those who were never or rarely screened for cervical cancer were more likely than those who were regularly screened to have a chronic condition, such as heart disease, chronic obstructive pulmonary disease, arthritis, depression, kidney disease, or diabetes.

This finding suggests that cancer screening may be a low priority during an adult primary care visit in which multiple chronic diseases must be addressed. To reduce disparities in cancer screening, primary care systems need to be designed to optimize delivery of preventive care and disease management using a team approach.

SYSTEMATIC FOLLOW-UP

Arvizo and Mahdi also discuss the follow-up of abnormal screening Papanicolaou (Pap) smears. While appropriate follow-up is a key factor in the management of cervical dysplasia, follow-up rates vary among African American women. System-level interventions such as the use of an electronic medical record-based tracking system in primary care settings⁶ with established protocols for follow-up may be effective.

But even with such systems in place, patients may face psychosocial barriers (eg, lack of health literacy, distress after receiving an abnormal cervical cytology test result⁷) that prevent them from seeking additional care. To improve follow-up rates, providers must be aware of these barriers and know how to address them through effective communication.

VACCINATION FOR HPV

Finally, the association between human papilloma virus (HPV) infection and cervical cancer makes HPV vaccination a crucial step in cervical cancer prevention. Continued provider education regarding HPV vaccination can improve knowledge about the HPV vaccine,⁸ as well as improve vaccination rates.⁹ The recent approval of a 2-dose vaccine schedule for younger girls¹⁰ may also help improve vaccine series completion rates.

The authors also suggest that primary care providers counsel all patients about risk factors for cervical cancer, including unsafe sex practices and tobacco use.

OPTIMIZING SCREENING AND PREVENTION

I commend the authors for their discussion of cervical cancer disparities and for raising awareness of the important role primary care providers play in reducing these disparities. Improving cervical cancer screening rates and follow-up will require providers and patients to be aware of cervical cancer risk factors. Further, system-level practice interventions will optimize primary care providers’ ability to engage patients in cancer screening conversations and ensure timely follow-up of screening tests.

In this issue of the Journal of Hospital Medicine, Ellimoottil and colleagues examine characteristics of readmissions identified as planned by the planned readmission algorithm developed for the Center for Medicare & Medicaid Services (CMS) by using Medicare claims data from 131 hospitals in Michigan.¹ They found that a substantial portion of readmissions currently classified as planned by the algorithm appear to be nonelective, as defined by the presence of a charge by an emergency medicine physician or an admission type of emergent or urgent, making those hospitalizations unlikely to be planned. They suggest that the algorithm could be modified to exclude such cases from the planned designation.

To determine whether modifying the algorithm as recommended is a good idea, it is helpful to examine the origins of the existing planned readmission algorithm. The algorithm originated as a consequence of hospital accountability measures for readmissions and was developed by this author in collaboration with colleagues at Yale University and elsewhere.² Readmission measures have been controversial in part because clearly some (undetermined) fraction of readmissions is unavoidable. Many commentators have asked that readmission measures therefore capture only avoidable or related readmissions. Avoidable readmissions are those that could have been prevented by members of the healthcare system through actions taken during or after hospitalization, such as patient counseling, communication among team members, and guideline-concordant medical care. Related readmissions are those directly stemming from the index admission. However, reliably and accurately defining such events has proven elusive. One study, for instance, found the rate of physician-assessed preventability in published studies ranged from 9% to 48%.³ The challenge is even greater in trying to determine preventability using just claims data, without physician review of charts. Imagine, for instance, a patient with heart failure who is readmitted with heart failure exacerbation. The readmission preceded by a large fast-food meal is likely preventable; although even in this case, some would argue the healthcare system should not be held accountable for a readmission if the patient had been properly counseled about avoiding salty food. The one preceded by progressively worsening systolic function in a patient who reliably takes medications, weighs herself daily, and watches her diet is likely not. But both appear identical in claims. Related is also a difficult concept to operationalize. A recently hospitalized patient readmitted with pneumonia might have acquired it in the hospital (related) or from her grandchild 2 weeks later (unrelated). Again, both appear identical in claims.

In the ideal world, clinicians would be held accountable only for preventable readmissions. In practice, that has not proven to be possible.

Instead, the CMS readmission measures omit readmissions that are thought to be planned in advance: necessary and intentional readmissions. Defining a planned readmission is conceptually easier than defining a preventable readmission, yet even this is not always straightforward. The clearest case might be a person with a longstanding plan to have an elective surgery (say, a hip replacement) who is briefly admitted with something minor enough not to delay a subsequent admission for the scheduled surgery. Other patients are admitted with acute problems that require follow-up hospitalization (for instance, an acute myocardial infarction that requires a coronary artery bypass graft 2 weeks later).⁴ More ambiguous are patients who are sent home on a course of treatment with a plan for rehospitalization if it fails; for instance, a patient with gangrene is sent home on intravenous antibiotics but fails to improve and is rehospitalized for an amputation. Is that readmission planned or unplanned? Reasonable people might disagree.

Nonetheless, assuming it is desirable to at least try to identify and remove planned readmissions from measures, there are a number of ways in which one might do so. Perhaps the simplest would be to classify each hospitalization as planned or not on the UB-04 claim form. Such a process would be very feasible but also subject to gaming or coding variability. Given that there is some ambiguity and no standard about what types of readmissions are planned and that current policy provides incentives to reduce unplanned readmission rates, hospitals might vary in the cases to which they would apply such a code. This approach, therefore, has not been favored by payers to date. An alternative is to prospectively flag admissions that are expected to result in planned readmissions. In fiscal year 2014, the CMS implemented this option for newborns and patients with acute myocardial infarction by creating new discharge status codes of “discharged to [location] with a planned acute care hospital inpatient readmission.” Institutions can flag discharges that they know at the time of discharge will be followed by a readmission, such as a newborn who requires a repeat hospitalization for repair of a congenital anomaly.⁵ There is no time span required for the planned readmission to qualify. However, the difficulty in broadening the applicability of this option to all discharges lies in identification and matching; there also remains a possibility for gaming. The code does not specify when the readmission is expected nor for what diagnosis or procedure. How, then, do we know if the subsequent readmission is the one anticipated? Unexpected readmissions may still occur in the interim. Conversely, what if the discharging clinicians don’t know about an anticipated planned procedure? What would stop hospitals from labeling every discharge as expected to be followed by a planned readmission? These considerations have largely prevented the CMS from asking hospitals to apply the new code widely or from applying the code to identify planned readmissions.

Instead, the existing algorithm attempts to identify procedures that might be done on an elective basis and assumes readmissions with these procedures are planned if paired with a nonurgent diagnosis. Ellimoottil and colleagues attempt to verify whether this is accurate using a creative approach of seeking emergency department (ED) charges and admission type of emergent or urgent, and they found that roughly half of planned readmissions are, in fact, likely unplanned. This figure agrees closely with the original chart review validation of the algorithm. In particular, they found that some procedures, such as percutaneous cardiac interventions, appear to be paired regularly with a nonurgent principal diagnosis, such as coronary artery disease, even when done on an urgent basis.

This validation was performed prior to the availability of version 4.0 of the planned readmission algorithm, which removes several high-frequency procedures from the potentially planned readmission list (including cardiac devices and diagnostic cardiac catheterizations) that were very frequently mischaracterized as planned in the original chart validation.⁶ At least 8 such cases were also identified in this validation according to the table. Therefore, the misclassification rate of the current algorithm version is probably less than that reported in this article. Nonetheless, percutaneous transluminal coronary angioplasty remains on the planned procedure list in version 4.0 and appears to account for a substantial error rate, and it is likely that the authors’ approach would improve the accuracy even of the newer version of the algorithm.

The advantages of the suggested modifications are that they do not require chart review and could be readily adopted by the CMS. Although seeking ED charges for Medicare is somewhat cumbersome in that they are recorded in a different data set than the inpatient hospitalizations, there is no absolute barrier to adding this step to the algorithm, and doing so has substantial face validity. That said, identifying ED visits is not straightforward because nonemergency services can be provided in the ED (ie, critical care or observation care) and because facilities and providers have different billing requirements, producing different estimates depending on the data set used.⁷ Including admission type would be easier, but it would be less conservative and likely less accurate, as this field has not been validated and is not typically audited. Nonetheless, adding the presence of ED charges seems likely to improve the accuracy of the algorithm. As the CMS continues to refine the planned readmission algorithm, these proposed changes would be very reasonable to study with chart validation and, if valid, to consider adopting.

Disclosure 

Dr. Horwitz reports grants from Center for Medicare & Medicaid Services, grants from Agency for Healthcare Research and Quality, during the conduct of the study.

In this issue of the Journal of Hospital Medicine, Ellimoottil and colleagues examine characteristics of readmissions identified as planned by the planned readmission algorithm developed for the Center for Medicare & Medicaid Services (CMS) by using Medicare claims data from 131 hospitals in Michigan.¹ They found that a substantial portion of readmissions currently classified as planned by the algorithm appear to be nonelective, as defined by the presence of a charge by an emergency medicine physician or an admission type of emergent or urgent, making those hospitalizations unlikely to be planned. They suggest that the algorithm could be modified to exclude such cases from the planned designation.

To determine whether modifying the algorithm as recommended is a good idea, it is helpful to examine the origins of the existing planned readmission algorithm. The algorithm originated as a consequence of hospital accountability measures for readmissions and was developed by this author in collaboration with colleagues at Yale University and elsewhere.² Readmission measures have been controversial in part because clearly some (undetermined) fraction of readmissions is unavoidable. Many commentators have asked that readmission measures therefore capture only avoidable or related readmissions. Avoidable readmissions are those that could have been prevented by members of the healthcare system through actions taken during or after hospitalization, such as patient counseling, communication among team members, and guideline-concordant medical care. Related readmissions are those directly stemming from the index admission. However, reliably and accurately defining such events has proven elusive. One study, for instance, found the rate of physician-assessed preventability in published studies ranged from 9% to 48%.³ The challenge is even greater in trying to determine preventability using just claims data, without physician review of charts. Imagine, for instance, a patient with heart failure who is readmitted with heart failure exacerbation. The readmission preceded by a large fast-food meal is likely preventable; although even in this case, some would argue the healthcare system should not be held accountable for a readmission if the patient had been properly counseled about avoiding salty food. The one preceded by progressively worsening systolic function in a patient who reliably takes medications, weighs herself daily, and watches her diet is likely not. But both appear identical in claims. Related is also a difficult concept to operationalize. A recently hospitalized patient readmitted with pneumonia might have acquired it in the hospital (related) or from her grandchild 2 weeks later (unrelated). Again, both appear identical in claims.

In the ideal world, clinicians would be held accountable only for preventable readmissions. In practice, that has not proven to be possible.

Instead, the CMS readmission measures omit readmissions that are thought to be planned in advance: necessary and intentional readmissions. Defining a planned readmission is conceptually easier than defining a preventable readmission, yet even this is not always straightforward. The clearest case might be a person with a longstanding plan to have an elective surgery (say, a hip replacement) who is briefly admitted with something minor enough not to delay a subsequent admission for the scheduled surgery. Other patients are admitted with acute problems that require follow-up hospitalization (for instance, an acute myocardial infarction that requires a coronary artery bypass graft 2 weeks later).⁴ More ambiguous are patients who are sent home on a course of treatment with a plan for rehospitalization if it fails; for instance, a patient with gangrene is sent home on intravenous antibiotics but fails to improve and is rehospitalized for an amputation. Is that readmission planned or unplanned? Reasonable people might disagree.

Nonetheless, assuming it is desirable to at least try to identify and remove planned readmissions from measures, there are a number of ways in which one might do so. Perhaps the simplest would be to classify each hospitalization as planned or not on the UB-04 claim form. Such a process would be very feasible but also subject to gaming or coding variability. Given that there is some ambiguity and no standard about what types of readmissions are planned and that current policy provides incentives to reduce unplanned readmission rates, hospitals might vary in the cases to which they would apply such a code. This approach, therefore, has not been favored by payers to date. An alternative is to prospectively flag admissions that are expected to result in planned readmissions. In fiscal year 2014, the CMS implemented this option for newborns and patients with acute myocardial infarction by creating new discharge status codes of “discharged to [location] with a planned acute care hospital inpatient readmission.” Institutions can flag discharges that they know at the time of discharge will be followed by a readmission, such as a newborn who requires a repeat hospitalization for repair of a congenital anomaly.⁵ There is no time span required for the planned readmission to qualify. However, the difficulty in broadening the applicability of this option to all discharges lies in identification and matching; there also remains a possibility for gaming. The code does not specify when the readmission is expected nor for what diagnosis or procedure. How, then, do we know if the subsequent readmission is the one anticipated? Unexpected readmissions may still occur in the interim. Conversely, what if the discharging clinicians don’t know about an anticipated planned procedure? What would stop hospitals from labeling every discharge as expected to be followed by a planned readmission? These considerations have largely prevented the CMS from asking hospitals to apply the new code widely or from applying the code to identify planned readmissions.

Instead, the existing algorithm attempts to identify procedures that might be done on an elective basis and assumes readmissions with these procedures are planned if paired with a nonurgent diagnosis. Ellimoottil and colleagues attempt to verify whether this is accurate using a creative approach of seeking emergency department (ED) charges and admission type of emergent or urgent, and they found that roughly half of planned readmissions are, in fact, likely unplanned. This figure agrees closely with the original chart review validation of the algorithm. In particular, they found that some procedures, such as percutaneous cardiac interventions, appear to be paired regularly with a nonurgent principal diagnosis, such as coronary artery disease, even when done on an urgent basis.

This validation was performed prior to the availability of version 4.0 of the planned readmission algorithm, which removes several high-frequency procedures from the potentially planned readmission list (including cardiac devices and diagnostic cardiac catheterizations) that were very frequently mischaracterized as planned in the original chart validation.⁶ At least 8 such cases were also identified in this validation according to the table. Therefore, the misclassification rate of the current algorithm version is probably less than that reported in this article. Nonetheless, percutaneous transluminal coronary angioplasty remains on the planned procedure list in version 4.0 and appears to account for a substantial error rate, and it is likely that the authors’ approach would improve the accuracy even of the newer version of the algorithm.

The advantages of the suggested modifications are that they do not require chart review and could be readily adopted by the CMS. Although seeking ED charges for Medicare is somewhat cumbersome in that they are recorded in a different data set than the inpatient hospitalizations, there is no absolute barrier to adding this step to the algorithm, and doing so has substantial face validity. That said, identifying ED visits is not straightforward because nonemergency services can be provided in the ED (ie, critical care or observation care) and because facilities and providers have different billing requirements, producing different estimates depending on the data set used.⁷ Including admission type would be easier, but it would be less conservative and likely less accurate, as this field has not been validated and is not typically audited. Nonetheless, adding the presence of ED charges seems likely to improve the accuracy of the algorithm. As the CMS continues to refine the planned readmission algorithm, these proposed changes would be very reasonable to study with chart validation and, if valid, to consider adopting.

Disclosure 

Dr. Horwitz reports grants from Center for Medicare & Medicaid Services, grants from Agency for Healthcare Research and Quality, during the conduct of the study.

In this issue of the Journal of Hospital Medicine, Ellimoottil and colleagues examine characteristics of readmissions identified as planned by the planned readmission algorithm developed for the Center for Medicare & Medicaid Services (CMS) by using Medicare claims data from 131 hospitals in Michigan.¹ They found that a substantial portion of readmissions currently classified as planned by the algorithm appear to be nonelective, as defined by the presence of a charge by an emergency medicine physician or an admission type of emergent or urgent, making those hospitalizations unlikely to be planned. They suggest that the algorithm could be modified to exclude such cases from the planned designation.

To determine whether modifying the algorithm as recommended is a good idea, it is helpful to examine the origins of the existing planned readmission algorithm. The algorithm originated as a consequence of hospital accountability measures for readmissions and was developed by this author in collaboration with colleagues at Yale University and elsewhere.² Readmission measures have been controversial in part because clearly some (undetermined) fraction of readmissions is unavoidable. Many commentators have asked that readmission measures therefore capture only avoidable or related readmissions. Avoidable readmissions are those that could have been prevented by members of the healthcare system through actions taken during or after hospitalization, such as patient counseling, communication among team members, and guideline-concordant medical care. Related readmissions are those directly stemming from the index admission. However, reliably and accurately defining such events has proven elusive. One study, for instance, found the rate of physician-assessed preventability in published studies ranged from 9% to 48%.³ The challenge is even greater in trying to determine preventability using just claims data, without physician review of charts. Imagine, for instance, a patient with heart failure who is readmitted with heart failure exacerbation. The readmission preceded by a large fast-food meal is likely preventable; although even in this case, some would argue the healthcare system should not be held accountable for a readmission if the patient had been properly counseled about avoiding salty food. The one preceded by progressively worsening systolic function in a patient who reliably takes medications, weighs herself daily, and watches her diet is likely not. But both appear identical in claims. Related is also a difficult concept to operationalize. A recently hospitalized patient readmitted with pneumonia might have acquired it in the hospital (related) or from her grandchild 2 weeks later (unrelated). Again, both appear identical in claims.

In the ideal world, clinicians would be held accountable only for preventable readmissions. In practice, that has not proven to be possible.

Instead, the CMS readmission measures omit readmissions that are thought to be planned in advance: necessary and intentional readmissions. Defining a planned readmission is conceptually easier than defining a preventable readmission, yet even this is not always straightforward. The clearest case might be a person with a longstanding plan to have an elective surgery (say, a hip replacement) who is briefly admitted with something minor enough not to delay a subsequent admission for the scheduled surgery. Other patients are admitted with acute problems that require follow-up hospitalization (for instance, an acute myocardial infarction that requires a coronary artery bypass graft 2 weeks later).⁴ More ambiguous are patients who are sent home on a course of treatment with a plan for rehospitalization if it fails; for instance, a patient with gangrene is sent home on intravenous antibiotics but fails to improve and is rehospitalized for an amputation. Is that readmission planned or unplanned? Reasonable people might disagree.

Nonetheless, assuming it is desirable to at least try to identify and remove planned readmissions from measures, there are a number of ways in which one might do so. Perhaps the simplest would be to classify each hospitalization as planned or not on the UB-04 claim form. Such a process would be very feasible but also subject to gaming or coding variability. Given that there is some ambiguity and no standard about what types of readmissions are planned and that current policy provides incentives to reduce unplanned readmission rates, hospitals might vary in the cases to which they would apply such a code. This approach, therefore, has not been favored by payers to date. An alternative is to prospectively flag admissions that are expected to result in planned readmissions. In fiscal year 2014, the CMS implemented this option for newborns and patients with acute myocardial infarction by creating new discharge status codes of “discharged to [location] with a planned acute care hospital inpatient readmission.” Institutions can flag discharges that they know at the time of discharge will be followed by a readmission, such as a newborn who requires a repeat hospitalization for repair of a congenital anomaly.⁵ There is no time span required for the planned readmission to qualify. However, the difficulty in broadening the applicability of this option to all discharges lies in identification and matching; there also remains a possibility for gaming. The code does not specify when the readmission is expected nor for what diagnosis or procedure. How, then, do we know if the subsequent readmission is the one anticipated? Unexpected readmissions may still occur in the interim. Conversely, what if the discharging clinicians don’t know about an anticipated planned procedure? What would stop hospitals from labeling every discharge as expected to be followed by a planned readmission? These considerations have largely prevented the CMS from asking hospitals to apply the new code widely or from applying the code to identify planned readmissions.

Instead, the existing algorithm attempts to identify procedures that might be done on an elective basis and assumes readmissions with these procedures are planned if paired with a nonurgent diagnosis. Ellimoottil and colleagues attempt to verify whether this is accurate using a creative approach of seeking emergency department (ED) charges and admission type of emergent or urgent, and they found that roughly half of planned readmissions are, in fact, likely unplanned. This figure agrees closely with the original chart review validation of the algorithm. In particular, they found that some procedures, such as percutaneous cardiac interventions, appear to be paired regularly with a nonurgent principal diagnosis, such as coronary artery disease, even when done on an urgent basis.

This validation was performed prior to the availability of version 4.0 of the planned readmission algorithm, which removes several high-frequency procedures from the potentially planned readmission list (including cardiac devices and diagnostic cardiac catheterizations) that were very frequently mischaracterized as planned in the original chart validation.⁶ At least 8 such cases were also identified in this validation according to the table. Therefore, the misclassification rate of the current algorithm version is probably less than that reported in this article. Nonetheless, percutaneous transluminal coronary angioplasty remains on the planned procedure list in version 4.0 and appears to account for a substantial error rate, and it is likely that the authors’ approach would improve the accuracy even of the newer version of the algorithm.

The advantages of the suggested modifications are that they do not require chart review and could be readily adopted by the CMS. Although seeking ED charges for Medicare is somewhat cumbersome in that they are recorded in a different data set than the inpatient hospitalizations, there is no absolute barrier to adding this step to the algorithm, and doing so has substantial face validity. That said, identifying ED visits is not straightforward because nonemergency services can be provided in the ED (ie, critical care or observation care) and because facilities and providers have different billing requirements, producing different estimates depending on the data set used.⁷ Including admission type would be easier, but it would be less conservative and likely less accurate, as this field has not been validated and is not typically audited. Nonetheless, adding the presence of ED charges seems likely to improve the accuracy of the algorithm. As the CMS continues to refine the planned readmission algorithm, these proposed changes would be very reasonable to study with chart validation and, if valid, to consider adopting.

Disclosure 

Dr. Horwitz reports grants from Center for Medicare & Medicaid Services, grants from Agency for Healthcare Research and Quality, during the conduct of the study.

“Unnecessary noise is the most cruel abuse of care which can be inflicted on either the sick or the well.”

–Florence Nightingale¹

Motivated by the “unsustainable” rise in noise pollution and its “direct, as well as cumulative, adverse health effects,” an expert World Health Organization (WHO) task force composed the Guidelines for Community Noise, outlining specific noise recommendations for public settings, including hospitals.² In ward settings, these guidelines mandate that background noise (which is defined as unwanted sound) levels average <35 decibels (dB; ie, a typical library) during the day, average <30 dB at night, and peak no higher than 40 dB (ie, a normal conversation), a level sufficient to awaken someone from sleep.

Since the publication of these guidelines in 1999, substantial new research has added to our understanding of hospital noise levels. Recent research has demonstrated that few, if any, hospitals comply with WHO noise recommendations.³ Moreover, since 1960, hospital sound levels have risen ~4 dB per decade; based on the logarithmic decibel scale, if this trend continues, this translates to a 528% increase in loudness by 2020.³

The overwhelming majority of research on hospital noise has focused on the intensive care unit (ICU), where beeping machines and busy staff often push peak nighttime noise levels over 80 dB (ie, a kitchen blender).⁴ When evaluated during sleep, noise in the ICU causes frequent arousals and awakenings. When noise is combined with other factors, such as bright light and patient care interactions, poor sleep quality invariably results.⁴

While it has been known for years that critically ill patients experience markedly fragmented and nonrestorative sleep,⁵ poor sleep has recently gained attention due to its potential role as a modifiable risk factor for delirium and its associated consequences, including prolonged length of stay and long-lasting neuropsychological and physical impairments.⁶ Due to this interest, numerous interventions have been attempted,⁷ including multicomponent bundles to promote sleep,⁸ which have been shown to reduce delirium in the ICU.^9-12 Therefore, efforts to promote sleep in the ICU, including interventions to minimize nighttime noise, are recommended in Society of Critical Care Medicine clinical practice guidelines¹³ and are listed as a top 5 research priority by an expert panel of ICU delirium researchers.¹⁴

In contrast to the ICU, there has been little attention paid to noise in other patient care areas. Existing studies in non-ICU ward settings suggest that excessive noise is common,³ similar to the ICU, and that patients experience poor sleep, with noise being a significant disruptor of sleep.^5,15,16 Such poor sleep is thought to contribute to uncontrolled pain, labile blood pressure, and dissatisfaction with care.^16,17

In this issue of the Journal of Hospital Medicine, Jaiswal and colleagues¹⁸ report on an important study evaluating sound and light levels in both non-ICU and ICU settings within a busy tertiary-care hospital. In 8 general ward, 8 telemetry, and 8 ICU patient rooms, the investigators used meters to record sound and light levels for 24 to 72 hours. In each of these locations, they detected average hourly sound levels ranging from 45 to 54 dB, 47 to 55 dB, and 56 to 60 dB, respectively, with ICUs consistently registering the highest hourly sound levels. Notably, all locations exceeded WHO noise limits at all hours of the day. As a novel measure, the investigators evaluated sound level changes (SLCs), or the difference between peak and background sound levels, based on research suggesting that dramatic SLCs (≥17.5 dB) are more disruptive than constant loud noise.¹⁹ The authors observed that SLCs ≥17.5 dB occur predominantly during daytime hours and, interestingly, at a similar rate in the wards versus the ICU.

Importantly, the authors do not link their findings with patient sleep or other patient outcomes but instead focus on employing rigorous methods to gather continuous recordings. By measuring light levels, the authors bring attention to an issue often considered less disruptive to sleep than noise.^6,10,20 Similar to prior research,²¹ Jaiswal and colleagues demonstrate low levels of light at night, with no substantial difference between non-ICU and ICU settings. As a key finding, the authors bring attention to low levels of light during daytime hours, particularly in the morning, when levels range from 22 to 101 lux in the wards and 16 to 39 lux in the ICU. While the optimal timing and brightness of light exposure remains unknown, it is well established that ambient light is the most potent cue for circadian rhythms, with levels >100 lux necessary to suppress melatonin, the key hormone involved in circadian entrainment. Hence, the levels of morning light observed in this study were likely insufficient to maintain healthy circadian rhythms. When exposed to abnormal light levels and factors such as noise, stress, and medications, hospitalized patients are at risk for circadian rhythm misalignment, which can disrupt sleep and trigger a complex molecular cascade, leading to end-organ dysfunction including depressed immunity, glucose dysregulation, arrhythmias, and delirium.^22-24

What are the major takeaway messages from this study? First, it confirms that sound levels are not only high in the ICU but also in non-ICU wards. As hospital ratings and reimbursements now rely on favorable patient ratings, future noise-reduction efforts will surely expand more vigorously across patient care areas.²⁵ Second, SLCs and daytime recordings must be included in efforts to understand and improve sleep and circadian rhythms in hospitalized patients. Finally, this study provides a sobering reminder of the challenge of meeting WHO guidelines and facilitating an optimal healing environment for patients. Sadly, hospital sound levels continue to rise, and quiet-time interventions consistently fail to lower noise to levels anywhere near WHO limits.²⁶ Hence, to make any progress, hospitals of the future must entertain novel design modifications (eg, sound-absorbing walls and alternative room layouts), fix common sources of noise pollution (eg, ventilation systems and alarms), and critically evaluate and update interventions aimed at improving sleep and aligning circadian rhythms for hospitalized patients.²⁷

Acknowledgments

B.B.K. is currently supported by a grant through the University of California, Los Angeles Clinical Translational Research Institute and the National Institutes of Health’s National Center for Advancing Translational Sciences (UL1TR000124).

Disclosure

The authors have nothing to disclose.

“Unnecessary noise is the most cruel abuse of care which can be inflicted on either the sick or the well.”

–Florence Nightingale¹

Motivated by the “unsustainable” rise in noise pollution and its “direct, as well as cumulative, adverse health effects,” an expert World Health Organization (WHO) task force composed the Guidelines for Community Noise, outlining specific noise recommendations for public settings, including hospitals.² In ward settings, these guidelines mandate that background noise (which is defined as unwanted sound) levels average <35 decibels (dB; ie, a typical library) during the day, average <30 dB at night, and peak no higher than 40 dB (ie, a normal conversation), a level sufficient to awaken someone from sleep.

Since the publication of these guidelines in 1999, substantial new research has added to our understanding of hospital noise levels. Recent research has demonstrated that few, if any, hospitals comply with WHO noise recommendations.³ Moreover, since 1960, hospital sound levels have risen ~4 dB per decade; based on the logarithmic decibel scale, if this trend continues, this translates to a 528% increase in loudness by 2020.³

The overwhelming majority of research on hospital noise has focused on the intensive care unit (ICU), where beeping machines and busy staff often push peak nighttime noise levels over 80 dB (ie, a kitchen blender).⁴ When evaluated during sleep, noise in the ICU causes frequent arousals and awakenings. When noise is combined with other factors, such as bright light and patient care interactions, poor sleep quality invariably results.⁴

While it has been known for years that critically ill patients experience markedly fragmented and nonrestorative sleep,⁵ poor sleep has recently gained attention due to its potential role as a modifiable risk factor for delirium and its associated consequences, including prolonged length of stay and long-lasting neuropsychological and physical impairments.⁶ Due to this interest, numerous interventions have been attempted,⁷ including multicomponent bundles to promote sleep,⁸ which have been shown to reduce delirium in the ICU.^9-12 Therefore, efforts to promote sleep in the ICU, including interventions to minimize nighttime noise, are recommended in Society of Critical Care Medicine clinical practice guidelines¹³ and are listed as a top 5 research priority by an expert panel of ICU delirium researchers.¹⁴

In contrast to the ICU, there has been little attention paid to noise in other patient care areas. Existing studies in non-ICU ward settings suggest that excessive noise is common,³ similar to the ICU, and that patients experience poor sleep, with noise being a significant disruptor of sleep.^5,15,16 Such poor sleep is thought to contribute to uncontrolled pain, labile blood pressure, and dissatisfaction with care.^16,17

In this issue of the Journal of Hospital Medicine, Jaiswal and colleagues¹⁸ report on an important study evaluating sound and light levels in both non-ICU and ICU settings within a busy tertiary-care hospital. In 8 general ward, 8 telemetry, and 8 ICU patient rooms, the investigators used meters to record sound and light levels for 24 to 72 hours. In each of these locations, they detected average hourly sound levels ranging from 45 to 54 dB, 47 to 55 dB, and 56 to 60 dB, respectively, with ICUs consistently registering the highest hourly sound levels. Notably, all locations exceeded WHO noise limits at all hours of the day. As a novel measure, the investigators evaluated sound level changes (SLCs), or the difference between peak and background sound levels, based on research suggesting that dramatic SLCs (≥17.5 dB) are more disruptive than constant loud noise.¹⁹ The authors observed that SLCs ≥17.5 dB occur predominantly during daytime hours and, interestingly, at a similar rate in the wards versus the ICU.

Importantly, the authors do not link their findings with patient sleep or other patient outcomes but instead focus on employing rigorous methods to gather continuous recordings. By measuring light levels, the authors bring attention to an issue often considered less disruptive to sleep than noise.^6,10,20 Similar to prior research,²¹ Jaiswal and colleagues demonstrate low levels of light at night, with no substantial difference between non-ICU and ICU settings. As a key finding, the authors bring attention to low levels of light during daytime hours, particularly in the morning, when levels range from 22 to 101 lux in the wards and 16 to 39 lux in the ICU. While the optimal timing and brightness of light exposure remains unknown, it is well established that ambient light is the most potent cue for circadian rhythms, with levels >100 lux necessary to suppress melatonin, the key hormone involved in circadian entrainment. Hence, the levels of morning light observed in this study were likely insufficient to maintain healthy circadian rhythms. When exposed to abnormal light levels and factors such as noise, stress, and medications, hospitalized patients are at risk for circadian rhythm misalignment, which can disrupt sleep and trigger a complex molecular cascade, leading to end-organ dysfunction including depressed immunity, glucose dysregulation, arrhythmias, and delirium.^22-24

What are the major takeaway messages from this study? First, it confirms that sound levels are not only high in the ICU but also in non-ICU wards. As hospital ratings and reimbursements now rely on favorable patient ratings, future noise-reduction efforts will surely expand more vigorously across patient care areas.²⁵ Second, SLCs and daytime recordings must be included in efforts to understand and improve sleep and circadian rhythms in hospitalized patients. Finally, this study provides a sobering reminder of the challenge of meeting WHO guidelines and facilitating an optimal healing environment for patients. Sadly, hospital sound levels continue to rise, and quiet-time interventions consistently fail to lower noise to levels anywhere near WHO limits.²⁶ Hence, to make any progress, hospitals of the future must entertain novel design modifications (eg, sound-absorbing walls and alternative room layouts), fix common sources of noise pollution (eg, ventilation systems and alarms), and critically evaluate and update interventions aimed at improving sleep and aligning circadian rhythms for hospitalized patients.²⁷

Acknowledgments

B.B.K. is currently supported by a grant through the University of California, Los Angeles Clinical Translational Research Institute and the National Institutes of Health’s National Center for Advancing Translational Sciences (UL1TR000124).

Disclosure

The authors have nothing to disclose.

“Unnecessary noise is the most cruel abuse of care which can be inflicted on either the sick or the well.”

–Florence Nightingale¹

Motivated by the “unsustainable” rise in noise pollution and its “direct, as well as cumulative, adverse health effects,” an expert World Health Organization (WHO) task force composed the Guidelines for Community Noise, outlining specific noise recommendations for public settings, including hospitals.² In ward settings, these guidelines mandate that background noise (which is defined as unwanted sound) levels average <35 decibels (dB; ie, a typical library) during the day, average <30 dB at night, and peak no higher than 40 dB (ie, a normal conversation), a level sufficient to awaken someone from sleep.

Since the publication of these guidelines in 1999, substantial new research has added to our understanding of hospital noise levels. Recent research has demonstrated that few, if any, hospitals comply with WHO noise recommendations.³ Moreover, since 1960, hospital sound levels have risen ~4 dB per decade; based on the logarithmic decibel scale, if this trend continues, this translates to a 528% increase in loudness by 2020.³

The overwhelming majority of research on hospital noise has focused on the intensive care unit (ICU), where beeping machines and busy staff often push peak nighttime noise levels over 80 dB (ie, a kitchen blender).⁴ When evaluated during sleep, noise in the ICU causes frequent arousals and awakenings. When noise is combined with other factors, such as bright light and patient care interactions, poor sleep quality invariably results.⁴

While it has been known for years that critically ill patients experience markedly fragmented and nonrestorative sleep,⁵ poor sleep has recently gained attention due to its potential role as a modifiable risk factor for delirium and its associated consequences, including prolonged length of stay and long-lasting neuropsychological and physical impairments.⁶ Due to this interest, numerous interventions have been attempted,⁷ including multicomponent bundles to promote sleep,⁸ which have been shown to reduce delirium in the ICU.^9-12 Therefore, efforts to promote sleep in the ICU, including interventions to minimize nighttime noise, are recommended in Society of Critical Care Medicine clinical practice guidelines¹³ and are listed as a top 5 research priority by an expert panel of ICU delirium researchers.¹⁴

In contrast to the ICU, there has been little attention paid to noise in other patient care areas. Existing studies in non-ICU ward settings suggest that excessive noise is common,³ similar to the ICU, and that patients experience poor sleep, with noise being a significant disruptor of sleep.^5,15,16 Such poor sleep is thought to contribute to uncontrolled pain, labile blood pressure, and dissatisfaction with care.^16,17

In this issue of the Journal of Hospital Medicine, Jaiswal and colleagues¹⁸ report on an important study evaluating sound and light levels in both non-ICU and ICU settings within a busy tertiary-care hospital. In 8 general ward, 8 telemetry, and 8 ICU patient rooms, the investigators used meters to record sound and light levels for 24 to 72 hours. In each of these locations, they detected average hourly sound levels ranging from 45 to 54 dB, 47 to 55 dB, and 56 to 60 dB, respectively, with ICUs consistently registering the highest hourly sound levels. Notably, all locations exceeded WHO noise limits at all hours of the day. As a novel measure, the investigators evaluated sound level changes (SLCs), or the difference between peak and background sound levels, based on research suggesting that dramatic SLCs (≥17.5 dB) are more disruptive than constant loud noise.¹⁹ The authors observed that SLCs ≥17.5 dB occur predominantly during daytime hours and, interestingly, at a similar rate in the wards versus the ICU.

Importantly, the authors do not link their findings with patient sleep or other patient outcomes but instead focus on employing rigorous methods to gather continuous recordings. By measuring light levels, the authors bring attention to an issue often considered less disruptive to sleep than noise.^6,10,20 Similar to prior research,²¹ Jaiswal and colleagues demonstrate low levels of light at night, with no substantial difference between non-ICU and ICU settings. As a key finding, the authors bring attention to low levels of light during daytime hours, particularly in the morning, when levels range from 22 to 101 lux in the wards and 16 to 39 lux in the ICU. While the optimal timing and brightness of light exposure remains unknown, it is well established that ambient light is the most potent cue for circadian rhythms, with levels >100 lux necessary to suppress melatonin, the key hormone involved in circadian entrainment. Hence, the levels of morning light observed in this study were likely insufficient to maintain healthy circadian rhythms. When exposed to abnormal light levels and factors such as noise, stress, and medications, hospitalized patients are at risk for circadian rhythm misalignment, which can disrupt sleep and trigger a complex molecular cascade, leading to end-organ dysfunction including depressed immunity, glucose dysregulation, arrhythmias, and delirium.^22-24

What are the major takeaway messages from this study? First, it confirms that sound levels are not only high in the ICU but also in non-ICU wards. As hospital ratings and reimbursements now rely on favorable patient ratings, future noise-reduction efforts will surely expand more vigorously across patient care areas.²⁵ Second, SLCs and daytime recordings must be included in efforts to understand and improve sleep and circadian rhythms in hospitalized patients. Finally, this study provides a sobering reminder of the challenge of meeting WHO guidelines and facilitating an optimal healing environment for patients. Sadly, hospital sound levels continue to rise, and quiet-time interventions consistently fail to lower noise to levels anywhere near WHO limits.²⁶ Hence, to make any progress, hospitals of the future must entertain novel design modifications (eg, sound-absorbing walls and alternative room layouts), fix common sources of noise pollution (eg, ventilation systems and alarms), and critically evaluate and update interventions aimed at improving sleep and aligning circadian rhythms for hospitalized patients.²⁷

Acknowledgments

B.B.K. is currently supported by a grant through the University of California, Los Angeles Clinical Translational Research Institute and the National Institutes of Health’s National Center for Advancing Translational Sciences (UL1TR000124).

Disclosure

The authors have nothing to disclose.

Peripheral intravenous catheters (PIVCs) are the most frequently used vascular access devices (VADs) in all patient populations and practice settings. Because of its invasive nature and the fact that PIVCs are placed and medications are administered directly into the bloodstream, vascular access is risky. There are multiple factors to consider when placing a PIVC, the least of which is determining the most appropriate device for the patient based on the prescribed therapy.

VAD planning and assessment needs to occur at the first patient encounter so that the most appropriate device is selected and it aligns with the duration of the treatment, minimizes the number of unnecessary VADs placed, and preserves veins for any future needs. The level of the clinician’s expertise, coupled with challenging environments of care, add to the complexity of what most perceive to be a “simple” procedure—placing a PIVC. For these reasons, it’s imperative that clinicians are competent in the use and placement of VADs to ensure safe patient care.

Carr and colleagues¹ performed a notable scoping review to determine the existence of tools, clinical prediction rules, and algorithms (TRAs) that would support decision-making for the use of PIVCs and promote first-time insertion success (FTIS). They refined their search strategy to studies that described the use or development of any TRA regarding PIVC insertion in hospitalized adult patients.

The team identified 36 references for screening and based on their inclusion and exclusion criteria, were left with 13 studies in the final review. Inclusion criteria included TRAs for PIVC insertion in hospitalized adult patients using a traditional insertion approach, which was defined as “an assessment and/or insertion with touch and feel, therefore, without vessel locating technology such as ultrasound and/or near infrared technology.” ¹ Of note is that some of the exclusion criteria included pediatric studies, TRAs focused on postinsertion assessment, studies that examined VADs other than PIVCs, and studies in which vascular visualization techniques were used.

In general, the authors were unable to find reported evidence that the study recommendations were adopted in clinical practice or to what degree any TRA had on the success of a PIVC insertion. As a result, they were unable to determine what, if any, clinical value the TRAs had.

The review of the studies, however, identified 3 variables that had an impact on PIVC insertion success: patient, clinician, and product characteristics. Vein characteristics, such as the number, size, and location of veins, and patients’ clinical conditions, such as diabetes, sickle cell anemia, and intravenous drug abuse, were noted as predictors of PIVC insertion success. In 7 papers, the primary focus was on patients with a history of difficult intravenous access (DIVA). The definition of DIVA varied from time to insertion of the PIVC to the number of failed attempts, ranging from 1 to 3 or more attempts.

Clinician variables, such as specialty nurse certification, years of experience, and self-reporting skill level, were associated with successful insertions, and clinicians who predicted FTIS were likely to have FTIS. Product variables included PIVC gauge size and the number of vein options and the relationship with successful first attempts.

Limitations noted by the researchers were a lack of sufficient published evidence for TRAs for PIVC insertion and standardized definitions for DIVA and expert inserters. The number of variables and the dearth of standardized terms may also influence the ability to adopt any TRAs.

While the purpose of the research was to identify TRAs that could guide clinical practice for the use of PIVCs and successful insertions, the authors make an important point that dwell time was not considered. While a TRA may lead to a successful insertion, it may not transcend the intended life of the PIVC or the duration of the therapy. Therefore, TRAs should embed steps that ensure the appropriate device is selected at the start of the patient’s treatment.

The authors identified a need for undertaking and providing research in a critical area of patient care and safety. This article increases awareness of issues related to PIVCs and the impact they have on patient care. FTIS rates vary and the implications of their use are many. Patient satisfaction, no delay in treatment, vein preservation, a decreased risk of complications, and the cost of labor and products are factors to consider. Tools to improve patient outcomes related to device insertion, care, and management need to be developed and validated. The authors also note that future TRAs should integrate the use of ultrasound and vascular visualization technologies.

In a complex, challenging healthcare environment, tools and guidance that enhance practice do not only help clinicians; they have a positive impact on patient care. The need for research, so that gaps in knowledge and science can be bridged, is clear. Gaps must be identified, research conducted, and TRAs developed and adopted to enhance patient outcomes.

Disclosure

The author reports no conflicts of interest.

Peripheral intravenous catheters (PIVCs) are the most frequently used vascular access devices (VADs) in all patient populations and practice settings. Because of its invasive nature and the fact that PIVCs are placed and medications are administered directly into the bloodstream, vascular access is risky. There are multiple factors to consider when placing a PIVC, the least of which is determining the most appropriate device for the patient based on the prescribed therapy.

VAD planning and assessment needs to occur at the first patient encounter so that the most appropriate device is selected and it aligns with the duration of the treatment, minimizes the number of unnecessary VADs placed, and preserves veins for any future needs. The level of the clinician’s expertise, coupled with challenging environments of care, add to the complexity of what most perceive to be a “simple” procedure—placing a PIVC. For these reasons, it’s imperative that clinicians are competent in the use and placement of VADs to ensure safe patient care.

Carr and colleagues¹ performed a notable scoping review to determine the existence of tools, clinical prediction rules, and algorithms (TRAs) that would support decision-making for the use of PIVCs and promote first-time insertion success (FTIS). They refined their search strategy to studies that described the use or development of any TRA regarding PIVC insertion in hospitalized adult patients.

The team identified 36 references for screening and based on their inclusion and exclusion criteria, were left with 13 studies in the final review. Inclusion criteria included TRAs for PIVC insertion in hospitalized adult patients using a traditional insertion approach, which was defined as “an assessment and/or insertion with touch and feel, therefore, without vessel locating technology such as ultrasound and/or near infrared technology.” ¹ Of note is that some of the exclusion criteria included pediatric studies, TRAs focused on postinsertion assessment, studies that examined VADs other than PIVCs, and studies in which vascular visualization techniques were used.

In general, the authors were unable to find reported evidence that the study recommendations were adopted in clinical practice or to what degree any TRA had on the success of a PIVC insertion. As a result, they were unable to determine what, if any, clinical value the TRAs had.

The review of the studies, however, identified 3 variables that had an impact on PIVC insertion success: patient, clinician, and product characteristics. Vein characteristics, such as the number, size, and location of veins, and patients’ clinical conditions, such as diabetes, sickle cell anemia, and intravenous drug abuse, were noted as predictors of PIVC insertion success. In 7 papers, the primary focus was on patients with a history of difficult intravenous access (DIVA). The definition of DIVA varied from time to insertion of the PIVC to the number of failed attempts, ranging from 1 to 3 or more attempts.

Clinician variables, such as specialty nurse certification, years of experience, and self-reporting skill level, were associated with successful insertions, and clinicians who predicted FTIS were likely to have FTIS. Product variables included PIVC gauge size and the number of vein options and the relationship with successful first attempts.

Limitations noted by the researchers were a lack of sufficient published evidence for TRAs for PIVC insertion and standardized definitions for DIVA and expert inserters. The number of variables and the dearth of standardized terms may also influence the ability to adopt any TRAs.

While the purpose of the research was to identify TRAs that could guide clinical practice for the use of PIVCs and successful insertions, the authors make an important point that dwell time was not considered. While a TRA may lead to a successful insertion, it may not transcend the intended life of the PIVC or the duration of the therapy. Therefore, TRAs should embed steps that ensure the appropriate device is selected at the start of the patient’s treatment.

The authors identified a need for undertaking and providing research in a critical area of patient care and safety. This article increases awareness of issues related to PIVCs and the impact they have on patient care. FTIS rates vary and the implications of their use are many. Patient satisfaction, no delay in treatment, vein preservation, a decreased risk of complications, and the cost of labor and products are factors to consider. Tools to improve patient outcomes related to device insertion, care, and management need to be developed and validated. The authors also note that future TRAs should integrate the use of ultrasound and vascular visualization technologies.

In a complex, challenging healthcare environment, tools and guidance that enhance practice do not only help clinicians; they have a positive impact on patient care. The need for research, so that gaps in knowledge and science can be bridged, is clear. Gaps must be identified, research conducted, and TRAs developed and adopted to enhance patient outcomes.

Disclosure

The author reports no conflicts of interest.

Peripheral intravenous catheters (PIVCs) are the most frequently used vascular access devices (VADs) in all patient populations and practice settings. Because of its invasive nature and the fact that PIVCs are placed and medications are administered directly into the bloodstream, vascular access is risky. There are multiple factors to consider when placing a PIVC, the least of which is determining the most appropriate device for the patient based on the prescribed therapy.

VAD planning and assessment needs to occur at the first patient encounter so that the most appropriate device is selected and it aligns with the duration of the treatment, minimizes the number of unnecessary VADs placed, and preserves veins for any future needs. The level of the clinician’s expertise, coupled with challenging environments of care, add to the complexity of what most perceive to be a “simple” procedure—placing a PIVC. For these reasons, it’s imperative that clinicians are competent in the use and placement of VADs to ensure safe patient care.

Carr and colleagues¹ performed a notable scoping review to determine the existence of tools, clinical prediction rules, and algorithms (TRAs) that would support decision-making for the use of PIVCs and promote first-time insertion success (FTIS). They refined their search strategy to studies that described the use or development of any TRA regarding PIVC insertion in hospitalized adult patients.

The team identified 36 references for screening and based on their inclusion and exclusion criteria, were left with 13 studies in the final review. Inclusion criteria included TRAs for PIVC insertion in hospitalized adult patients using a traditional insertion approach, which was defined as “an assessment and/or insertion with touch and feel, therefore, without vessel locating technology such as ultrasound and/or near infrared technology.” ¹ Of note is that some of the exclusion criteria included pediatric studies, TRAs focused on postinsertion assessment, studies that examined VADs other than PIVCs, and studies in which vascular visualization techniques were used.

In general, the authors were unable to find reported evidence that the study recommendations were adopted in clinical practice or to what degree any TRA had on the success of a PIVC insertion. As a result, they were unable to determine what, if any, clinical value the TRAs had.

The review of the studies, however, identified 3 variables that had an impact on PIVC insertion success: patient, clinician, and product characteristics. Vein characteristics, such as the number, size, and location of veins, and patients’ clinical conditions, such as diabetes, sickle cell anemia, and intravenous drug abuse, were noted as predictors of PIVC insertion success. In 7 papers, the primary focus was on patients with a history of difficult intravenous access (DIVA). The definition of DIVA varied from time to insertion of the PIVC to the number of failed attempts, ranging from 1 to 3 or more attempts.

Clinician variables, such as specialty nurse certification, years of experience, and self-reporting skill level, were associated with successful insertions, and clinicians who predicted FTIS were likely to have FTIS. Product variables included PIVC gauge size and the number of vein options and the relationship with successful first attempts.

Limitations noted by the researchers were a lack of sufficient published evidence for TRAs for PIVC insertion and standardized definitions for DIVA and expert inserters. The number of variables and the dearth of standardized terms may also influence the ability to adopt any TRAs.

While the purpose of the research was to identify TRAs that could guide clinical practice for the use of PIVCs and successful insertions, the authors make an important point that dwell time was not considered. While a TRA may lead to a successful insertion, it may not transcend the intended life of the PIVC or the duration of the therapy. Therefore, TRAs should embed steps that ensure the appropriate device is selected at the start of the patient’s treatment.

The authors identified a need for undertaking and providing research in a critical area of patient care and safety. This article increases awareness of issues related to PIVCs and the impact they have on patient care. FTIS rates vary and the implications of their use are many. Patient satisfaction, no delay in treatment, vein preservation, a decreased risk of complications, and the cost of labor and products are factors to consider. Tools to improve patient outcomes related to device insertion, care, and management need to be developed and validated. The authors also note that future TRAs should integrate the use of ultrasound and vascular visualization technologies.

In a complex, challenging healthcare environment, tools and guidance that enhance practice do not only help clinicians; they have a positive impact on patient care. The need for research, so that gaps in knowledge and science can be bridged, is clear. Gaps must be identified, research conducted, and TRAs developed and adopted to enhance patient outcomes.

Disclosure

The author reports no conflicts of interest.

During my training in Leiden, Netherlands, I was infused with the lessons of Herman Boerhaave (1668–1738), the professor who is considered the pioneer of bedside teaching.¹ This practice had begun in Padua and was then brought to Leiden, where Boerhaave transformed it into an art form. At the Caecilia hospital, the municipal clerics provided Boerhaave with 2 wards for teaching; 1 with 6 beds for men and the other with 6 beds for women. Medical historian Henry Sigerist² has commented that half the physicians of Europe were trained on these 12 beds.

See related article

Boerhaave made daily rounds with his students, examining the patients, reviewing their histories, and inspecting their urine. He considered postmortem examinations essential and made his students attend the autopsies of patients who died: “In spite of the most detailed description of all disease phenomena one does not know anything of the cause until one has opened the body.”²

What was once the basis of clinical medicine is now fading, with both clinical rounds and autopsies being replaced by imaging techniques of body parts and automated analysis of Vacutainer samples. These novelties provide us with far more diagnostic accuracy than Boer­haave had, and randomized controlled trials provide us with an evidence base. But bedside observation and case reports are still relevant,³ and autopsies still reveal important, clinically missed diagnoses.⁴

In this issue of the Journal, Imm et al⁵ describe a case of presumed postoperative delirium in a 64-year-old hospitalized patient. They remind us that crucial signs and symptoms can guide how to use our modern diagnostic tools.

DELIRIUM IS OFTEN OVERLOOKED

Delirium is often overlooked by physicians. But why? The characteristic disturbances in attention and cognition are easy to interpret, while the various observation scales have high sensitivity and should signal the need for further interrogation. Perhaps the reason we often overlook the signs and symptoms is that we assume that delirium is just normal sickness behavior.

Another reason we may fail to recognize the syndrome is more fundamental and closely related to how we practice medicine. These days, we place such trust in high-tech diagnostics that we feel the modern procedures supersede the classic examination of patients. But mental disturbances can only be detected by history-taking and clinical observation.

Moreover, the actual mental state is less important than the subtle changes in it. A continuously disturbed mind does not pose a problem, but a casual remark by a family member or informal caregiver that “his mood has changed” should seize our attention.⁶

Here, the fragmented and disconnected practice of modern medicine takes its toll. Shorter working hours have helped to preserve our own mental performance, but at the cost of being less able to follow the patient’s mental status over time and to recognize a change of behavior. Applying repeated, standardized assessments of these vital signs may help solve the problem, but repeated observations are easily neglected, as are body temperature, blood pressure, and others.

DELIRIUM IS SERIOUS

Imm et al also remind us that delirium is serious. The case-fatality rate in delirium equals that in acute cardiovascular events or metastatic cancer, even though its impact is often not thought to be as severe. Far too often the mental symptoms are dismissed and judged to be something to be handled in the outpatient clinic after the acute problems are addressed.

In part, this may be because no professional society or advocacy group is promoting the recognition, diagnosis, and treatment of delirium or pushing for incentives to do so. We have cardiologists and oncologists but not deliriologists. But in a way, it may be a good thing that no specialist group “owns” delirium, as the syndrome is elicited by various underlying disease mechanisms, and every physician should be vigilant to recognize it.

DELIRIUM REQUIRES PROMPT MANAGEMENT

If delirium is a life-threatening condition, it necessitates a prompt and coordinated series of diagnostic actions, judgments, and decisions.⁷ Although most delirious patients are not admitted to an intensive care unit, they should be considered critically ill and must be provided a corresponding level of care. Here, the old clinical aphorism holds: action should be taken before the sun sets or rises. Attention should be on worsening of the underlying disease, unexpected comorbid conditions, and side effects of our interventions.

As the case reported by Imm et al shows, the causative factors may be recognized only after in-depth examination.⁴ The pathogenesis of delirium is poorly understood, and there is no specific therapy for it. There is not even conclusive evidence that the standard use of antipsychotics is beneficial, whereas their side effects cannot be overestimated.⁷ Our interventions are aimed at eliminating the underlying pathologies that have triggered the delirious state, as well as on preventing complications of the mental disturbance.

Many of us have had the experience of watching one of our children develop fever and confusion. When our older patients become delirious, it should raise the same level of alarm and activity as when it happens in a child.

During my training in Leiden, Netherlands, I was infused with the lessons of Herman Boerhaave (1668–1738), the professor who is considered the pioneer of bedside teaching.¹ This practice had begun in Padua and was then brought to Leiden, where Boerhaave transformed it into an art form. At the Caecilia hospital, the municipal clerics provided Boerhaave with 2 wards for teaching; 1 with 6 beds for men and the other with 6 beds for women. Medical historian Henry Sigerist² has commented that half the physicians of Europe were trained on these 12 beds.

See related article

Boerhaave made daily rounds with his students, examining the patients, reviewing their histories, and inspecting their urine. He considered postmortem examinations essential and made his students attend the autopsies of patients who died: “In spite of the most detailed description of all disease phenomena one does not know anything of the cause until one has opened the body.”²

What was once the basis of clinical medicine is now fading, with both clinical rounds and autopsies being replaced by imaging techniques of body parts and automated analysis of Vacutainer samples. These novelties provide us with far more diagnostic accuracy than Boer­haave had, and randomized controlled trials provide us with an evidence base. But bedside observation and case reports are still relevant,³ and autopsies still reveal important, clinically missed diagnoses.⁴

In this issue of the Journal, Imm et al⁵ describe a case of presumed postoperative delirium in a 64-year-old hospitalized patient. They remind us that crucial signs and symptoms can guide how to use our modern diagnostic tools.

DELIRIUM IS OFTEN OVERLOOKED

Delirium is often overlooked by physicians. But why? The characteristic disturbances in attention and cognition are easy to interpret, while the various observation scales have high sensitivity and should signal the need for further interrogation. Perhaps the reason we often overlook the signs and symptoms is that we assume that delirium is just normal sickness behavior.

Another reason we may fail to recognize the syndrome is more fundamental and closely related to how we practice medicine. These days, we place such trust in high-tech diagnostics that we feel the modern procedures supersede the classic examination of patients. But mental disturbances can only be detected by history-taking and clinical observation.

Moreover, the actual mental state is less important than the subtle changes in it. A continuously disturbed mind does not pose a problem, but a casual remark by a family member or informal caregiver that “his mood has changed” should seize our attention.⁶

Here, the fragmented and disconnected practice of modern medicine takes its toll. Shorter working hours have helped to preserve our own mental performance, but at the cost of being less able to follow the patient’s mental status over time and to recognize a change of behavior. Applying repeated, standardized assessments of these vital signs may help solve the problem, but repeated observations are easily neglected, as are body temperature, blood pressure, and others.

DELIRIUM IS SERIOUS

Imm et al also remind us that delirium is serious. The case-fatality rate in delirium equals that in acute cardiovascular events or metastatic cancer, even though its impact is often not thought to be as severe. Far too often the mental symptoms are dismissed and judged to be something to be handled in the outpatient clinic after the acute problems are addressed.

In part, this may be because no professional society or advocacy group is promoting the recognition, diagnosis, and treatment of delirium or pushing for incentives to do so. We have cardiologists and oncologists but not deliriologists. But in a way, it may be a good thing that no specialist group “owns” delirium, as the syndrome is elicited by various underlying disease mechanisms, and every physician should be vigilant to recognize it.

DELIRIUM REQUIRES PROMPT MANAGEMENT

If delirium is a life-threatening condition, it necessitates a prompt and coordinated series of diagnostic actions, judgments, and decisions.⁷ Although most delirious patients are not admitted to an intensive care unit, they should be considered critically ill and must be provided a corresponding level of care. Here, the old clinical aphorism holds: action should be taken before the sun sets or rises. Attention should be on worsening of the underlying disease, unexpected comorbid conditions, and side effects of our interventions.

As the case reported by Imm et al shows, the causative factors may be recognized only after in-depth examination.⁴ The pathogenesis of delirium is poorly understood, and there is no specific therapy for it. There is not even conclusive evidence that the standard use of antipsychotics is beneficial, whereas their side effects cannot be overestimated.⁷ Our interventions are aimed at eliminating the underlying pathologies that have triggered the delirious state, as well as on preventing complications of the mental disturbance.

Many of us have had the experience of watching one of our children develop fever and confusion. When our older patients become delirious, it should raise the same level of alarm and activity as when it happens in a child.

During my training in Leiden, Netherlands, I was infused with the lessons of Herman Boerhaave (1668–1738), the professor who is considered the pioneer of bedside teaching.¹ This practice had begun in Padua and was then brought to Leiden, where Boerhaave transformed it into an art form. At the Caecilia hospital, the municipal clerics provided Boerhaave with 2 wards for teaching; 1 with 6 beds for men and the other with 6 beds for women. Medical historian Henry Sigerist² has commented that half the physicians of Europe were trained on these 12 beds.

See related article

Boerhaave made daily rounds with his students, examining the patients, reviewing their histories, and inspecting their urine. He considered postmortem examinations essential and made his students attend the autopsies of patients who died: “In spite of the most detailed description of all disease phenomena one does not know anything of the cause until one has opened the body.”²

What was once the basis of clinical medicine is now fading, with both clinical rounds and autopsies being replaced by imaging techniques of body parts and automated analysis of Vacutainer samples. These novelties provide us with far more diagnostic accuracy than Boer­haave had, and randomized controlled trials provide us with an evidence base. But bedside observation and case reports are still relevant,³ and autopsies still reveal important, clinically missed diagnoses.⁴

In this issue of the Journal, Imm et al⁵ describe a case of presumed postoperative delirium in a 64-year-old hospitalized patient. They remind us that crucial signs and symptoms can guide how to use our modern diagnostic tools.

DELIRIUM IS OFTEN OVERLOOKED

Delirium is often overlooked by physicians. But why? The characteristic disturbances in attention and cognition are easy to interpret, while the various observation scales have high sensitivity and should signal the need for further interrogation. Perhaps the reason we often overlook the signs and symptoms is that we assume that delirium is just normal sickness behavior.

Another reason we may fail to recognize the syndrome is more fundamental and closely related to how we practice medicine. These days, we place such trust in high-tech diagnostics that we feel the modern procedures supersede the classic examination of patients. But mental disturbances can only be detected by history-taking and clinical observation.

Moreover, the actual mental state is less important than the subtle changes in it. A continuously disturbed mind does not pose a problem, but a casual remark by a family member or informal caregiver that “his mood has changed” should seize our attention.⁶

Here, the fragmented and disconnected practice of modern medicine takes its toll. Shorter working hours have helped to preserve our own mental performance, but at the cost of being less able to follow the patient’s mental status over time and to recognize a change of behavior. Applying repeated, standardized assessments of these vital signs may help solve the problem, but repeated observations are easily neglected, as are body temperature, blood pressure, and others.

DELIRIUM IS SERIOUS

Imm et al also remind us that delirium is serious. The case-fatality rate in delirium equals that in acute cardiovascular events or metastatic cancer, even though its impact is often not thought to be as severe. Far too often the mental symptoms are dismissed and judged to be something to be handled in the outpatient clinic after the acute problems are addressed.

In part, this may be because no professional society or advocacy group is promoting the recognition, diagnosis, and treatment of delirium or pushing for incentives to do so. We have cardiologists and oncologists but not deliriologists. But in a way, it may be a good thing that no specialist group “owns” delirium, as the syndrome is elicited by various underlying disease mechanisms, and every physician should be vigilant to recognize it.

DELIRIUM REQUIRES PROMPT MANAGEMENT

If delirium is a life-threatening condition, it necessitates a prompt and coordinated series of diagnostic actions, judgments, and decisions.⁷ Although most delirious patients are not admitted to an intensive care unit, they should be considered critically ill and must be provided a corresponding level of care. Here, the old clinical aphorism holds: action should be taken before the sun sets or rises. Attention should be on worsening of the underlying disease, unexpected comorbid conditions, and side effects of our interventions.

As the case reported by Imm et al shows, the causative factors may be recognized only after in-depth examination.⁴ The pathogenesis of delirium is poorly understood, and there is no specific therapy for it. There is not even conclusive evidence that the standard use of antipsychotics is beneficial, whereas their side effects cannot be overestimated.⁷ Our interventions are aimed at eliminating the underlying pathologies that have triggered the delirious state, as well as on preventing complications of the mental disturbance.

Many of us have had the experience of watching one of our children develop fever and confusion. When our older patients become delirious, it should raise the same level of alarm and activity as when it happens in a child.

When renal sympathetic denervation, an endovascular procedure designed to treat resistant hypertension, failed to meet its efficacy goal in the SYMPLICITY HTN-3 trial,¹ the news was disappointing.

See related article

In this issue of the Cleveland Clinic Journal of Medicine, Shishehbor et al² provide a critical review of the findings of that trial and summarize its intricacies, as well as the results of other important trials of renal denervation therapy for hypertension. To their excellent observations, we would like to add some of our own.

HYPERTENSION: COMMON, OFTEN RESISTANT

The worldwide prevalence of hypertension is increasing. In the year 2000, about 26% of the adult world population had hypertension; by the year 2025, the number is projected to rise to 29%—1.56 billion people.³

Only about 50% of patients with hypertension are treated for it and, of those, about half have it adequately controlled. In one report, about 30% of US patients with hypertension had adequate blood pressure control.⁴

Patients who have uncontrolled hypertension are usually older and more obese, have higher baseline blood pressure and excessive salt intake, and are more likely to have chronic kidney disease, diabetes, obstructive sleep apnea, and aldosterone excess.⁵ Many of these conditions are also associated with increased sympathetic nervous system activity.⁶

Resistance and pseudoresistance

But lack of control of blood pressure is not the same as resistant hypertension. It is important to differentiate resistant hypertension from pseudoresistant hypertension, ie, hypertension that only seems to be resistant.⁷ Resistant hypertension affects 12.8% of all drug-treated hypertensive patients in the United States, according to data from the National Health and Nutrition Examination Survey.⁸

Factors that can cause pseudoresistant hypertension include:

Suboptimal antihypertensive regimens (truly resistant hypertension means blood pressure that remains high despite concurrent treatment with 3 antihypertensive drugs of different classes, 1 of which is a diuretic, in maximal doses)

The white coat effect (higher blood pressure in the office than at home, presumably due to the stress of an office visit)

• Suboptimal blood pressure measurement techniques (eg, use of a cuff that is too small, causing falsely high readings)
• Physician inertia (eg, failure to change a regimen that is not working)
• Lifestyle factors (eg, excessive sodium intake)
• Medications that interfere with blood pressure control (eg, nonsteroidal anti-inflammatory drugs)
• Poor adherence to prescribed medications.

Causes of secondary hypertension such as obstructive sleep apnea, primary aldosteronism, and renal artery stenosis should also be ruled out before concluding that a patient has resistant hypertension.

Hypertension causes a myriad of medical diseases, including accelerated atherosclerosis, myocardial ischemia and infarction, both systolic and diastolic heart failure, rhythm problems (eg, atrial fibrillation), and stroke.

Most patients with resistant hypertension have no identifiable reversible causes of it, exhibit increased sympathetic nervous system activity, and have increased risk of cardiovascular events. The risk can be reduced by treatment.^9,10

Adequate and sustained treatment of hypertension prevents and mitigates its complications. The classic Veterans Administration Cooperative Study in the 1960s demonstrated a 96% reduction in cardiovascular events over 18 months with the use of 3 antihypertensive medications in patients with severe hypertension.¹¹ A reduction of as little as 2 mm Hg in the mean blood pressure has been associated with a 10% reduction in the risk of stroke mortality and a 7% decrease in ischemic heart disease mortality.¹² This is an important consideration when evaluating the clinical end points of hypertension trials.

SYMPLICITY HTN-3 TRIAL: WHAT DID WE LEARN?

As controlling blood pressure is paramount in reducing cardiovascular complications, it is only natural to look for innovative strategies to supplement the medical treatments of hypertension.

The multicenter SYMPLICITY HTN-3 trial¹ was undertaken to establish the efficacy of renal-artery denervation using radiofrequency energy delivered by a catheter-based system (Symplicity RDN, Medtronic, Dublin, Ireland). This randomized, sham-controlled, blinded study did not show a benefit from this procedure with respect to either of its efficacy end points—at 6 months, a reduction in office systolic blood pressure of at least 5 mm Hg more than with medical therapy alone, or a reduction in mean ambulatory systolic pressure of at least 2 mm Hg more than with medical therapy alone.

Despite the negative results, this medium-size (N = 535) randomized clinical trial still represents the highest-level evidence in the field, and we ought to learn something from it.

Limitations of SYMPLICITY HTN-3

Several factors may have contributed to the negative results of the trial. 

Patient selection. For the most part, patients enrolled in renal denervation trials, including SYMPLICITY HTN-3, were not selected on the basis of heightened sympathetic nervous system activity. Assessment of sympathetic nervous system activity may identify the population most likely to achieve an adequate response.

Of note, the baseline blood pressure readings of patients in this trial were higher in the office than on ambulatory monitoring. Patients with white coat hypertension have increased sympathetic nervous system activity and thus might actually be good candidates for renal denervation therapy.

Adequacy of ablation was not measured. Many argue that an objective measure of the adequacy of the denervation procedure (qualitative or quantitative) should have been implemented and, if it had been, the results might have been different. For example, when ablation is performed in the main renal artery as well as the branches, the efficacy in reducing levels of norepinephrine is improved.¹³

Blood pressure fell in both groups. In SYMPLICITY HTN-3 and many other renal denervation trials, patients were assessed using both office and ambulatory blood pressure measurements. The primary end point was the office blood pressure measurement, with a 5-mm Hg difference in reduction chosen to define the superiority margin. This margin was chosen because even small reductions in blood pressure are known to decrease adverse events caused by hypertension. Notably, blood pressure fell significantly in both the control and intervention groups, with an intergroup difference of 2.39 mm Hg (not statistically significant) in favor of denervation.

Medication questions. The SYMPLICITY HTN-3 patients were supposed to be on stable medical regimens with maximal tolerated doses before the procedure. However, it was difficult to assess patients’ adherence to and tolerance of medical therapies. Many (about 40%) of the patients had their medications changed during the study.¹

Therefore, a critical look at the study enrollment criteria may shed more light on the reasons for the negative findings. Did these patients truly have resistant hypertension? Before they underwent the treatment, was their prestudy pharmacologic regimen adequately intensified?

After the findings of the SYMPLICITY HTN-3 study were released, several other trials—such as the Renal Denervation for Hypertension (DENERHTN)¹⁴ and Prague-15 trials¹⁵—reported conflicting results. Notably, these were not sham-controlled trials.

Newer studies with robust trial designs are ongoing. A quick search of www.clinicaltrials.gov reveals that at least 89 active clinical trials of renal denervation are registered as of the date of this writing. Excluding those with unknown status, there are 63 trials open or ongoing.

Clinical trials are also ongoing to determine the effects of renal denervation in patients with heart failure, atrial fibrillation, sleep apnea, and chronic kidney disease, all of which are known to involve heightened sympathetic nervous system activity.

NOT READY FOR CLINICAL USE

Although nonpharmacologic treatments of hypertension continue to be studied and are supported by an avalanche of trials in animals and small, mostly nonrandomized trials in humans, one should not forget that the SYMPLICITY HTN-3 trial simply did not meet its primary efficacy end points. We need definitive clinical evidence showing that renal denervation reduces either blood pressure or clinical events before it becomes a mainstream therapy in humans.

Additional trials are being conducted that were designed in accordance with the recommendations of the European Clinical Consensus Conference for Renal Denervation¹⁶ in terms of study population, design, and end points. Well-designed studies that conform to those recommendations are critical.

Finally, although our enthusiasm for renal denervation as a treatment of hypertension is tempered, there have been no noteworthy safety concerns related to the procedure, which certainly helps maintain the research momentum in this field.              

When renal sympathetic denervation, an endovascular procedure designed to treat resistant hypertension, failed to meet its efficacy goal in the SYMPLICITY HTN-3 trial,¹ the news was disappointing.

See related article

In this issue of the Cleveland Clinic Journal of Medicine, Shishehbor et al² provide a critical review of the findings of that trial and summarize its intricacies, as well as the results of other important trials of renal denervation therapy for hypertension. To their excellent observations, we would like to add some of our own.

HYPERTENSION: COMMON, OFTEN RESISTANT

The worldwide prevalence of hypertension is increasing. In the year 2000, about 26% of the adult world population had hypertension; by the year 2025, the number is projected to rise to 29%—1.56 billion people.³

Only about 50% of patients with hypertension are treated for it and, of those, about half have it adequately controlled. In one report, about 30% of US patients with hypertension had adequate blood pressure control.⁴

Patients who have uncontrolled hypertension are usually older and more obese, have higher baseline blood pressure and excessive salt intake, and are more likely to have chronic kidney disease, diabetes, obstructive sleep apnea, and aldosterone excess.⁵ Many of these conditions are also associated with increased sympathetic nervous system activity.⁶

Resistance and pseudoresistance

But lack of control of blood pressure is not the same as resistant hypertension. It is important to differentiate resistant hypertension from pseudoresistant hypertension, ie, hypertension that only seems to be resistant.⁷ Resistant hypertension affects 12.8% of all drug-treated hypertensive patients in the United States, according to data from the National Health and Nutrition Examination Survey.⁸

Factors that can cause pseudoresistant hypertension include:

Suboptimal antihypertensive regimens (truly resistant hypertension means blood pressure that remains high despite concurrent treatment with 3 antihypertensive drugs of different classes, 1 of which is a diuretic, in maximal doses)

The white coat effect (higher blood pressure in the office than at home, presumably due to the stress of an office visit)

• Suboptimal blood pressure measurement techniques (eg, use of a cuff that is too small, causing falsely high readings)
• Physician inertia (eg, failure to change a regimen that is not working)
• Lifestyle factors (eg, excessive sodium intake)
• Medications that interfere with blood pressure control (eg, nonsteroidal anti-inflammatory drugs)
• Poor adherence to prescribed medications.

Causes of secondary hypertension such as obstructive sleep apnea, primary aldosteronism, and renal artery stenosis should also be ruled out before concluding that a patient has resistant hypertension.

Hypertension causes a myriad of medical diseases, including accelerated atherosclerosis, myocardial ischemia and infarction, both systolic and diastolic heart failure, rhythm problems (eg, atrial fibrillation), and stroke.

Most patients with resistant hypertension have no identifiable reversible causes of it, exhibit increased sympathetic nervous system activity, and have increased risk of cardiovascular events. The risk can be reduced by treatment.^9,10

Adequate and sustained treatment of hypertension prevents and mitigates its complications. The classic Veterans Administration Cooperative Study in the 1960s demonstrated a 96% reduction in cardiovascular events over 18 months with the use of 3 antihypertensive medications in patients with severe hypertension.¹¹ A reduction of as little as 2 mm Hg in the mean blood pressure has been associated with a 10% reduction in the risk of stroke mortality and a 7% decrease in ischemic heart disease mortality.¹² This is an important consideration when evaluating the clinical end points of hypertension trials.

SYMPLICITY HTN-3 TRIAL: WHAT DID WE LEARN?

As controlling blood pressure is paramount in reducing cardiovascular complications, it is only natural to look for innovative strategies to supplement the medical treatments of hypertension.

The multicenter SYMPLICITY HTN-3 trial¹ was undertaken to establish the efficacy of renal-artery denervation using radiofrequency energy delivered by a catheter-based system (Symplicity RDN, Medtronic, Dublin, Ireland). This randomized, sham-controlled, blinded study did not show a benefit from this procedure with respect to either of its efficacy end points—at 6 months, a reduction in office systolic blood pressure of at least 5 mm Hg more than with medical therapy alone, or a reduction in mean ambulatory systolic pressure of at least 2 mm Hg more than with medical therapy alone.

Despite the negative results, this medium-size (N = 535) randomized clinical trial still represents the highest-level evidence in the field, and we ought to learn something from it.

Limitations of SYMPLICITY HTN-3

Several factors may have contributed to the negative results of the trial. 

Patient selection. For the most part, patients enrolled in renal denervation trials, including SYMPLICITY HTN-3, were not selected on the basis of heightened sympathetic nervous system activity. Assessment of sympathetic nervous system activity may identify the population most likely to achieve an adequate response.

Of note, the baseline blood pressure readings of patients in this trial were higher in the office than on ambulatory monitoring. Patients with white coat hypertension have increased sympathetic nervous system activity and thus might actually be good candidates for renal denervation therapy.

Adequacy of ablation was not measured. Many argue that an objective measure of the adequacy of the denervation procedure (qualitative or quantitative) should have been implemented and, if it had been, the results might have been different. For example, when ablation is performed in the main renal artery as well as the branches, the efficacy in reducing levels of norepinephrine is improved.¹³

Blood pressure fell in both groups. In SYMPLICITY HTN-3 and many other renal denervation trials, patients were assessed using both office and ambulatory blood pressure measurements. The primary end point was the office blood pressure measurement, with a 5-mm Hg difference in reduction chosen to define the superiority margin. This margin was chosen because even small reductions in blood pressure are known to decrease adverse events caused by hypertension. Notably, blood pressure fell significantly in both the control and intervention groups, with an intergroup difference of 2.39 mm Hg (not statistically significant) in favor of denervation.

Medication questions. The SYMPLICITY HTN-3 patients were supposed to be on stable medical regimens with maximal tolerated doses before the procedure. However, it was difficult to assess patients’ adherence to and tolerance of medical therapies. Many (about 40%) of the patients had their medications changed during the study.¹

Therefore, a critical look at the study enrollment criteria may shed more light on the reasons for the negative findings. Did these patients truly have resistant hypertension? Before they underwent the treatment, was their prestudy pharmacologic regimen adequately intensified?

After the findings of the SYMPLICITY HTN-3 study were released, several other trials—such as the Renal Denervation for Hypertension (DENERHTN)¹⁴ and Prague-15 trials¹⁵—reported conflicting results. Notably, these were not sham-controlled trials.

Newer studies with robust trial designs are ongoing. A quick search of www.clinicaltrials.gov reveals that at least 89 active clinical trials of renal denervation are registered as of the date of this writing. Excluding those with unknown status, there are 63 trials open or ongoing.

Clinical trials are also ongoing to determine the effects of renal denervation in patients with heart failure, atrial fibrillation, sleep apnea, and chronic kidney disease, all of which are known to involve heightened sympathetic nervous system activity.

NOT READY FOR CLINICAL USE

Although nonpharmacologic treatments of hypertension continue to be studied and are supported by an avalanche of trials in animals and small, mostly nonrandomized trials in humans, one should not forget that the SYMPLICITY HTN-3 trial simply did not meet its primary efficacy end points. We need definitive clinical evidence showing that renal denervation reduces either blood pressure or clinical events before it becomes a mainstream therapy in humans.

Additional trials are being conducted that were designed in accordance with the recommendations of the European Clinical Consensus Conference for Renal Denervation¹⁶ in terms of study population, design, and end points. Well-designed studies that conform to those recommendations are critical.

Finally, although our enthusiasm for renal denervation as a treatment of hypertension is tempered, there have been no noteworthy safety concerns related to the procedure, which certainly helps maintain the research momentum in this field.              

When renal sympathetic denervation, an endovascular procedure designed to treat resistant hypertension, failed to meet its efficacy goal in the SYMPLICITY HTN-3 trial,¹ the news was disappointing.

See related article

In this issue of the Cleveland Clinic Journal of Medicine, Shishehbor et al² provide a critical review of the findings of that trial and summarize its intricacies, as well as the results of other important trials of renal denervation therapy for hypertension. To their excellent observations, we would like to add some of our own.

HYPERTENSION: COMMON, OFTEN RESISTANT

The worldwide prevalence of hypertension is increasing. In the year 2000, about 26% of the adult world population had hypertension; by the year 2025, the number is projected to rise to 29%—1.56 billion people.³

Only about 50% of patients with hypertension are treated for it and, of those, about half have it adequately controlled. In one report, about 30% of US patients with hypertension had adequate blood pressure control.⁴

Patients who have uncontrolled hypertension are usually older and more obese, have higher baseline blood pressure and excessive salt intake, and are more likely to have chronic kidney disease, diabetes, obstructive sleep apnea, and aldosterone excess.⁵ Many of these conditions are also associated with increased sympathetic nervous system activity.⁶

Resistance and pseudoresistance

But lack of control of blood pressure is not the same as resistant hypertension. It is important to differentiate resistant hypertension from pseudoresistant hypertension, ie, hypertension that only seems to be resistant.⁷ Resistant hypertension affects 12.8% of all drug-treated hypertensive patients in the United States, according to data from the National Health and Nutrition Examination Survey.⁸

Factors that can cause pseudoresistant hypertension include:

Suboptimal antihypertensive regimens (truly resistant hypertension means blood pressure that remains high despite concurrent treatment with 3 antihypertensive drugs of different classes, 1 of which is a diuretic, in maximal doses)

The white coat effect (higher blood pressure in the office than at home, presumably due to the stress of an office visit)

• Suboptimal blood pressure measurement techniques (eg, use of a cuff that is too small, causing falsely high readings)
• Physician inertia (eg, failure to change a regimen that is not working)
• Lifestyle factors (eg, excessive sodium intake)
• Medications that interfere with blood pressure control (eg, nonsteroidal anti-inflammatory drugs)
• Poor adherence to prescribed medications.

Causes of secondary hypertension such as obstructive sleep apnea, primary aldosteronism, and renal artery stenosis should also be ruled out before concluding that a patient has resistant hypertension.

Hypertension causes a myriad of medical diseases, including accelerated atherosclerosis, myocardial ischemia and infarction, both systolic and diastolic heart failure, rhythm problems (eg, atrial fibrillation), and stroke.

Most patients with resistant hypertension have no identifiable reversible causes of it, exhibit increased sympathetic nervous system activity, and have increased risk of cardiovascular events. The risk can be reduced by treatment.^9,10

Adequate and sustained treatment of hypertension prevents and mitigates its complications. The classic Veterans Administration Cooperative Study in the 1960s demonstrated a 96% reduction in cardiovascular events over 18 months with the use of 3 antihypertensive medications in patients with severe hypertension.¹¹ A reduction of as little as 2 mm Hg in the mean blood pressure has been associated with a 10% reduction in the risk of stroke mortality and a 7% decrease in ischemic heart disease mortality.¹² This is an important consideration when evaluating the clinical end points of hypertension trials.

SYMPLICITY HTN-3 TRIAL: WHAT DID WE LEARN?

As controlling blood pressure is paramount in reducing cardiovascular complications, it is only natural to look for innovative strategies to supplement the medical treatments of hypertension.

The multicenter SYMPLICITY HTN-3 trial¹ was undertaken to establish the efficacy of renal-artery denervation using radiofrequency energy delivered by a catheter-based system (Symplicity RDN, Medtronic, Dublin, Ireland). This randomized, sham-controlled, blinded study did not show a benefit from this procedure with respect to either of its efficacy end points—at 6 months, a reduction in office systolic blood pressure of at least 5 mm Hg more than with medical therapy alone, or a reduction in mean ambulatory systolic pressure of at least 2 mm Hg more than with medical therapy alone.

Despite the negative results, this medium-size (N = 535) randomized clinical trial still represents the highest-level evidence in the field, and we ought to learn something from it.

Limitations of SYMPLICITY HTN-3

Several factors may have contributed to the negative results of the trial. 

Patient selection. For the most part, patients enrolled in renal denervation trials, including SYMPLICITY HTN-3, were not selected on the basis of heightened sympathetic nervous system activity. Assessment of sympathetic nervous system activity may identify the population most likely to achieve an adequate response.

Of note, the baseline blood pressure readings of patients in this trial were higher in the office than on ambulatory monitoring. Patients with white coat hypertension have increased sympathetic nervous system activity and thus might actually be good candidates for renal denervation therapy.

Adequacy of ablation was not measured. Many argue that an objective measure of the adequacy of the denervation procedure (qualitative or quantitative) should have been implemented and, if it had been, the results might have been different. For example, when ablation is performed in the main renal artery as well as the branches, the efficacy in reducing levels of norepinephrine is improved.¹³

Blood pressure fell in both groups. In SYMPLICITY HTN-3 and many other renal denervation trials, patients were assessed using both office and ambulatory blood pressure measurements. The primary end point was the office blood pressure measurement, with a 5-mm Hg difference in reduction chosen to define the superiority margin. This margin was chosen because even small reductions in blood pressure are known to decrease adverse events caused by hypertension. Notably, blood pressure fell significantly in both the control and intervention groups, with an intergroup difference of 2.39 mm Hg (not statistically significant) in favor of denervation.

Medication questions. The SYMPLICITY HTN-3 patients were supposed to be on stable medical regimens with maximal tolerated doses before the procedure. However, it was difficult to assess patients’ adherence to and tolerance of medical therapies. Many (about 40%) of the patients had their medications changed during the study.¹

Therefore, a critical look at the study enrollment criteria may shed more light on the reasons for the negative findings. Did these patients truly have resistant hypertension? Before they underwent the treatment, was their prestudy pharmacologic regimen adequately intensified?

After the findings of the SYMPLICITY HTN-3 study were released, several other trials—such as the Renal Denervation for Hypertension (DENERHTN)¹⁴ and Prague-15 trials¹⁵—reported conflicting results. Notably, these were not sham-controlled trials.

Newer studies with robust trial designs are ongoing. A quick search of www.clinicaltrials.gov reveals that at least 89 active clinical trials of renal denervation are registered as of the date of this writing. Excluding those with unknown status, there are 63 trials open or ongoing.

Clinical trials are also ongoing to determine the effects of renal denervation in patients with heart failure, atrial fibrillation, sleep apnea, and chronic kidney disease, all of which are known to involve heightened sympathetic nervous system activity.

NOT READY FOR CLINICAL USE

Although nonpharmacologic treatments of hypertension continue to be studied and are supported by an avalanche of trials in animals and small, mostly nonrandomized trials in humans, one should not forget that the SYMPLICITY HTN-3 trial simply did not meet its primary efficacy end points. We need definitive clinical evidence showing that renal denervation reduces either blood pressure or clinical events before it becomes a mainstream therapy in humans.

Additional trials are being conducted that were designed in accordance with the recommendations of the European Clinical Consensus Conference for Renal Denervation¹⁶ in terms of study population, design, and end points. Well-designed studies that conform to those recommendations are critical.

Finally, although our enthusiasm for renal denervation as a treatment of hypertension is tempered, there have been no noteworthy safety concerns related to the procedure, which certainly helps maintain the research momentum in this field.              

Inappropriate resource utilization is a pervasive problem in healthcare, and it has received increasing emphasis over the last few years as financial strain on the healthcare system has grown. This waste has led to new models of care—bundled care payments, accountable care organizations, and merit-based payment systems. Professional organizations have also emphasized the provision of high-value care and avoiding unnecessary diagnostic testing and treatment. In April 2012, the American Board of Internal Medicine (ABIM) launched the Choosing Wisely initiative to assist professional societies in putting forth recommendations on clinical circumstances in which particular tests and procedures should be avoided.

Until recently, teaching cost-effective care was not widely considered an important part of internal medicine residency programs. In a 2010 study surveying residents about resource utilization feedback, only 37% of internal medicine residents reported receiving any feedback on resource utilization and 20% reported receiving regular feedback.¹ These findings are especially significant in the broader context of national healthcare spending, as there is evidence that physicians who train in high-spending localities tend to have high-spending patterns later in their careers.² Another study showed similar findings when looking at region of training relative to success at recognizing high-value care on ABIM test questions.³ The Accreditation Council for Graduate Medical Education has developed the Clinical Learning Environment Review program to help address this need. This program provides feedback to teaching hospitals about their success at teaching residents and fellows to provide high-value medical care.

Given the current zeitgeist of emphasizing cost-effective, high-value care, appropriate utilization of routine labs is one area that stands out as an especially low-hanging fruit. The Society of Hospital Medicine, as part of the Choosing Wisely campaign, recommended minimizing routine lab draws in hospitalized patients with clinical and laboratory stability.⁴ Certainly, avoiding unnecessary routine lab draws is ideal because it saves patients the pain of superfluous phlebotomy, allows phlebotomy resources to be directed to blood draws with actual clinical utility, and saves money. There is also good evidence that hospital-acquired anemia, an effect of overuse of routine blood draws, has an adverse impact on morbidity and mortality in postmyocardial infarction patients^5,6 and more generally in hospitalized patients.⁷

Several studies have examined lab utilization on teaching services. Not surprisingly, the vast majority of test utilization is attributable to the interns (45%) and residents (26%), rather than attendings.⁸ Another study showed that internal medicine residents at one center had a much stronger self-reported predilection for ordering daily recurring routine labs rather than one-time labs for the following morning when admitting patients and when picking up patients, as compared with hospitalist attendings.⁹ This self-reported tendency translated into ordering more complete blood counts and basic chemistry panels per patient per day. A qualitative study looking at why internal medicine and general surgery residents ordered unnecessary labs yielded a number of responses, including ingrained habit, lack of price transparency, clinical uncertainty, belief that the attending expected it, and absence of a culture emphasizing resource utilization.¹⁰

In this issue of the Journal of Hospital Medicine, Kurtzman and colleagues report on a mixed-methods study looking at internal medicine resident engagement at their center with an electronic medical record–associated dashboard providing feedback on lab utilization.¹¹ Over a 6-month period, the residents randomized into the dashboard group received weekly e-mails while on service with a brief synopsis of their lab utilization relative to their peers and also a link to a dashboard with a time-series display of their relative lab ordering. While the majority of residents (74%) opened the e-mail, only a minority (21%) actually accessed the dashboard. Also, there was not a statistically significant relationship between dashboard use and lab ordering, though there was a trend to decreased lab ordering associated with opening the dashboard. The residents who participated in a focus group expressed both positive and negative opinions on the dashboard.

This is one example of social comparison feedback, which aims to improve performance by providing information to physicians on their performance relative to their peers. It has been shown to be effective in other areas of clinical medicine like limiting antibiotic overutilization in patients with upper respiratory infections.¹² One study examining social comparison feedback and objective feedback found that social comparison feedback improved performance for a simulated work task more for high performers but less for low performers than standard objective feedback.¹³ The utility of this type of feedback has not been extensively studied in healthcare.

However, the audit and feedback strategy, of which social comparison feedback is a subtype, has been extensively studied in healthcare. A 2012 Cochrane Review found that audit and feedback leads to “small but potentially important improvements in professional practice.”¹⁴ They found a wide variation in the effect of feedback among the 140 studies they analyzed. The factors strongly associated with a significant improvement after feedback were as follows: poor performance at baseline, a colleague or supervisor as the one providing the audit and feedback, repetitive feedback, feedback given both verbally and in writing, and clear advice or guidance on how to improve. Many of these components were missing from this study—that may be one reason the authors did not find a significant relationship between dashboard use and lab ordering.

A number of interventions, however, have been shown to decrease lab utilization, including unbundling of the components of the metabolic panel and disallowing daily recurring lab orders,¹⁵ fee displays,¹⁶ cost reminders,¹⁷ didactics and data feedback,¹⁸ and a multifaceted approach (didactics, monthly feedback, checklist, and financial incentives).¹⁹ A multipronged strategy, including an element of education, audit and feedback, hard-stop limits on redundant lab ordering, and fee information is likely to be the most successful strategy to reducing lab overutilization for both residents and attending physicians. Resource overutilization is a multifactorial problem, and multifactorial problems call for multifaceted solutions. Moreover, it may be necessary to employ both “carrot” and “stick” elements to such an approach, rewarding physicians who practice appropriate stewardship, but also penalizing practitioners who do not appropriately adjust their lab ordering tendencies after receiving feedback showing overuse.

Physician behavior is difficult to change, and there are many reasons why physicians order inappropriate tests and studies, including provider uncertainty, fear of malpractice litigation, and inadequate time to consider the utility of a test. Audit and feedback should be integrated into residency curriculums focusing on high-value care, in which hospitalists should play a central role. If supervising attendings are not integrated into such curriculums and continue to both overorder tests themselves and allow residents to do so, then the informal curriculum will trump the formal one.

Physicians respond to incentives, and appropriately designed incentives should be developed to help steer them to order only those tests and studies that are medically indicated. Such incentives must be provided alongside audit and feedback with appropriate goals that account for patient complexity. Ultimately, routine lab ordering is just one area of overutilization in hospital medicine, and the techniques that are successful at reducing overuse in this arena will need to be applied to other aspects of medicine like imaging and medication prescribing.

Disclosure

The authors declare no conflicts of interest.

Inappropriate resource utilization is a pervasive problem in healthcare, and it has received increasing emphasis over the last few years as financial strain on the healthcare system has grown. This waste has led to new models of care—bundled care payments, accountable care organizations, and merit-based payment systems. Professional organizations have also emphasized the provision of high-value care and avoiding unnecessary diagnostic testing and treatment. In April 2012, the American Board of Internal Medicine (ABIM) launched the Choosing Wisely initiative to assist professional societies in putting forth recommendations on clinical circumstances in which particular tests and procedures should be avoided.

Until recently, teaching cost-effective care was not widely considered an important part of internal medicine residency programs. In a 2010 study surveying residents about resource utilization feedback, only 37% of internal medicine residents reported receiving any feedback on resource utilization and 20% reported receiving regular feedback.¹ These findings are especially significant in the broader context of national healthcare spending, as there is evidence that physicians who train in high-spending localities tend to have high-spending patterns later in their careers.² Another study showed similar findings when looking at region of training relative to success at recognizing high-value care on ABIM test questions.³ The Accreditation Council for Graduate Medical Education has developed the Clinical Learning Environment Review program to help address this need. This program provides feedback to teaching hospitals about their success at teaching residents and fellows to provide high-value medical care.

Given the current zeitgeist of emphasizing cost-effective, high-value care, appropriate utilization of routine labs is one area that stands out as an especially low-hanging fruit. The Society of Hospital Medicine, as part of the Choosing Wisely campaign, recommended minimizing routine lab draws in hospitalized patients with clinical and laboratory stability.⁴ Certainly, avoiding unnecessary routine lab draws is ideal because it saves patients the pain of superfluous phlebotomy, allows phlebotomy resources to be directed to blood draws with actual clinical utility, and saves money. There is also good evidence that hospital-acquired anemia, an effect of overuse of routine blood draws, has an adverse impact on morbidity and mortality in postmyocardial infarction patients^5,6 and more generally in hospitalized patients.⁷

Several studies have examined lab utilization on teaching services. Not surprisingly, the vast majority of test utilization is attributable to the interns (45%) and residents (26%), rather than attendings.⁸ Another study showed that internal medicine residents at one center had a much stronger self-reported predilection for ordering daily recurring routine labs rather than one-time labs for the following morning when admitting patients and when picking up patients, as compared with hospitalist attendings.⁹ This self-reported tendency translated into ordering more complete blood counts and basic chemistry panels per patient per day. A qualitative study looking at why internal medicine and general surgery residents ordered unnecessary labs yielded a number of responses, including ingrained habit, lack of price transparency, clinical uncertainty, belief that the attending expected it, and absence of a culture emphasizing resource utilization.¹⁰

In this issue of the Journal of Hospital Medicine, Kurtzman and colleagues report on a mixed-methods study looking at internal medicine resident engagement at their center with an electronic medical record–associated dashboard providing feedback on lab utilization.¹¹ Over a 6-month period, the residents randomized into the dashboard group received weekly e-mails while on service with a brief synopsis of their lab utilization relative to their peers and also a link to a dashboard with a time-series display of their relative lab ordering. While the majority of residents (74%) opened the e-mail, only a minority (21%) actually accessed the dashboard. Also, there was not a statistically significant relationship between dashboard use and lab ordering, though there was a trend to decreased lab ordering associated with opening the dashboard. The residents who participated in a focus group expressed both positive and negative opinions on the dashboard.

This is one example of social comparison feedback, which aims to improve performance by providing information to physicians on their performance relative to their peers. It has been shown to be effective in other areas of clinical medicine like limiting antibiotic overutilization in patients with upper respiratory infections.¹² One study examining social comparison feedback and objective feedback found that social comparison feedback improved performance for a simulated work task more for high performers but less for low performers than standard objective feedback.¹³ The utility of this type of feedback has not been extensively studied in healthcare.

However, the audit and feedback strategy, of which social comparison feedback is a subtype, has been extensively studied in healthcare. A 2012 Cochrane Review found that audit and feedback leads to “small but potentially important improvements in professional practice.”¹⁴ They found a wide variation in the effect of feedback among the 140 studies they analyzed. The factors strongly associated with a significant improvement after feedback were as follows: poor performance at baseline, a colleague or supervisor as the one providing the audit and feedback, repetitive feedback, feedback given both verbally and in writing, and clear advice or guidance on how to improve. Many of these components were missing from this study—that may be one reason the authors did not find a significant relationship between dashboard use and lab ordering.

A number of interventions, however, have been shown to decrease lab utilization, including unbundling of the components of the metabolic panel and disallowing daily recurring lab orders,¹⁵ fee displays,¹⁶ cost reminders,¹⁷ didactics and data feedback,¹⁸ and a multifaceted approach (didactics, monthly feedback, checklist, and financial incentives).¹⁹ A multipronged strategy, including an element of education, audit and feedback, hard-stop limits on redundant lab ordering, and fee information is likely to be the most successful strategy to reducing lab overutilization for both residents and attending physicians. Resource overutilization is a multifactorial problem, and multifactorial problems call for multifaceted solutions. Moreover, it may be necessary to employ both “carrot” and “stick” elements to such an approach, rewarding physicians who practice appropriate stewardship, but also penalizing practitioners who do not appropriately adjust their lab ordering tendencies after receiving feedback showing overuse.

Physician behavior is difficult to change, and there are many reasons why physicians order inappropriate tests and studies, including provider uncertainty, fear of malpractice litigation, and inadequate time to consider the utility of a test. Audit and feedback should be integrated into residency curriculums focusing on high-value care, in which hospitalists should play a central role. If supervising attendings are not integrated into such curriculums and continue to both overorder tests themselves and allow residents to do so, then the informal curriculum will trump the formal one.

Physicians respond to incentives, and appropriately designed incentives should be developed to help steer them to order only those tests and studies that are medically indicated. Such incentives must be provided alongside audit and feedback with appropriate goals that account for patient complexity. Ultimately, routine lab ordering is just one area of overutilization in hospital medicine, and the techniques that are successful at reducing overuse in this arena will need to be applied to other aspects of medicine like imaging and medication prescribing.

Disclosure

The authors declare no conflicts of interest.

Inappropriate resource utilization is a pervasive problem in healthcare, and it has received increasing emphasis over the last few years as financial strain on the healthcare system has grown. This waste has led to new models of care—bundled care payments, accountable care organizations, and merit-based payment systems. Professional organizations have also emphasized the provision of high-value care and avoiding unnecessary diagnostic testing and treatment. In April 2012, the American Board of Internal Medicine (ABIM) launched the Choosing Wisely initiative to assist professional societies in putting forth recommendations on clinical circumstances in which particular tests and procedures should be avoided.

Until recently, teaching cost-effective care was not widely considered an important part of internal medicine residency programs. In a 2010 study surveying residents about resource utilization feedback, only 37% of internal medicine residents reported receiving any feedback on resource utilization and 20% reported receiving regular feedback.¹ These findings are especially significant in the broader context of national healthcare spending, as there is evidence that physicians who train in high-spending localities tend to have high-spending patterns later in their careers.² Another study showed similar findings when looking at region of training relative to success at recognizing high-value care on ABIM test questions.³ The Accreditation Council for Graduate Medical Education has developed the Clinical Learning Environment Review program to help address this need. This program provides feedback to teaching hospitals about their success at teaching residents and fellows to provide high-value medical care.

Given the current zeitgeist of emphasizing cost-effective, high-value care, appropriate utilization of routine labs is one area that stands out as an especially low-hanging fruit. The Society of Hospital Medicine, as part of the Choosing Wisely campaign, recommended minimizing routine lab draws in hospitalized patients with clinical and laboratory stability.⁴ Certainly, avoiding unnecessary routine lab draws is ideal because it saves patients the pain of superfluous phlebotomy, allows phlebotomy resources to be directed to blood draws with actual clinical utility, and saves money. There is also good evidence that hospital-acquired anemia, an effect of overuse of routine blood draws, has an adverse impact on morbidity and mortality in postmyocardial infarction patients^5,6 and more generally in hospitalized patients.⁷

Several studies have examined lab utilization on teaching services. Not surprisingly, the vast majority of test utilization is attributable to the interns (45%) and residents (26%), rather than attendings.⁸ Another study showed that internal medicine residents at one center had a much stronger self-reported predilection for ordering daily recurring routine labs rather than one-time labs for the following morning when admitting patients and when picking up patients, as compared with hospitalist attendings.⁹ This self-reported tendency translated into ordering more complete blood counts and basic chemistry panels per patient per day. A qualitative study looking at why internal medicine and general surgery residents ordered unnecessary labs yielded a number of responses, including ingrained habit, lack of price transparency, clinical uncertainty, belief that the attending expected it, and absence of a culture emphasizing resource utilization.¹⁰

In this issue of the Journal of Hospital Medicine, Kurtzman and colleagues report on a mixed-methods study looking at internal medicine resident engagement at their center with an electronic medical record–associated dashboard providing feedback on lab utilization.¹¹ Over a 6-month period, the residents randomized into the dashboard group received weekly e-mails while on service with a brief synopsis of their lab utilization relative to their peers and also a link to a dashboard with a time-series display of their relative lab ordering. While the majority of residents (74%) opened the e-mail, only a minority (21%) actually accessed the dashboard. Also, there was not a statistically significant relationship between dashboard use and lab ordering, though there was a trend to decreased lab ordering associated with opening the dashboard. The residents who participated in a focus group expressed both positive and negative opinions on the dashboard.

This is one example of social comparison feedback, which aims to improve performance by providing information to physicians on their performance relative to their peers. It has been shown to be effective in other areas of clinical medicine like limiting antibiotic overutilization in patients with upper respiratory infections.¹² One study examining social comparison feedback and objective feedback found that social comparison feedback improved performance for a simulated work task more for high performers but less for low performers than standard objective feedback.¹³ The utility of this type of feedback has not been extensively studied in healthcare.

However, the audit and feedback strategy, of which social comparison feedback is a subtype, has been extensively studied in healthcare. A 2012 Cochrane Review found that audit and feedback leads to “small but potentially important improvements in professional practice.”¹⁴ They found a wide variation in the effect of feedback among the 140 studies they analyzed. The factors strongly associated with a significant improvement after feedback were as follows: poor performance at baseline, a colleague or supervisor as the one providing the audit and feedback, repetitive feedback, feedback given both verbally and in writing, and clear advice or guidance on how to improve. Many of these components were missing from this study—that may be one reason the authors did not find a significant relationship between dashboard use and lab ordering.

A number of interventions, however, have been shown to decrease lab utilization, including unbundling of the components of the metabolic panel and disallowing daily recurring lab orders,¹⁵ fee displays,¹⁶ cost reminders,¹⁷ didactics and data feedback,¹⁸ and a multifaceted approach (didactics, monthly feedback, checklist, and financial incentives).¹⁹ A multipronged strategy, including an element of education, audit and feedback, hard-stop limits on redundant lab ordering, and fee information is likely to be the most successful strategy to reducing lab overutilization for both residents and attending physicians. Resource overutilization is a multifactorial problem, and multifactorial problems call for multifaceted solutions. Moreover, it may be necessary to employ both “carrot” and “stick” elements to such an approach, rewarding physicians who practice appropriate stewardship, but also penalizing practitioners who do not appropriately adjust their lab ordering tendencies after receiving feedback showing overuse.

Physician behavior is difficult to change, and there are many reasons why physicians order inappropriate tests and studies, including provider uncertainty, fear of malpractice litigation, and inadequate time to consider the utility of a test. Audit and feedback should be integrated into residency curriculums focusing on high-value care, in which hospitalists should play a central role. If supervising attendings are not integrated into such curriculums and continue to both overorder tests themselves and allow residents to do so, then the informal curriculum will trump the formal one.

Physicians respond to incentives, and appropriately designed incentives should be developed to help steer them to order only those tests and studies that are medically indicated. Such incentives must be provided alongside audit and feedback with appropriate goals that account for patient complexity. Ultimately, routine lab ordering is just one area of overutilization in hospital medicine, and the techniques that are successful at reducing overuse in this arena will need to be applied to other aspects of medicine like imaging and medication prescribing.

Disclosure

The authors declare no conflicts of interest.

Let’s face it—rates of hospital admission are on the rise, but there are still just 7 days in a week. That means that patients are increasingly admitted on weekdays and on the weekend, requiring more nurses and doctors to look after them. Why then are there no lines for coffee on a Saturday? Does this reduced intensity of staffing translate into worse care for our patients?

Since one of its earliest descriptions in hospitalized patients, the “weekend effect” has been extensively studied in various patient populations and hospital settings.^1-5 The results have been varied, depending on the place of care,⁶ reason for care, type of admission,^5,7 or admitting diagnosis.^1,8,9 Many researchers have posited the drivers behind the weekend effect, including understaffed wards, intensity of specialist care, delays in procedural treatments, or severity of illness, but the truth is that we still don’t know.

Pauls et al. performed a robust systematic review and meta-analysis examining the rates of in-hospital mortality in patients admitted on the weekend compared with those admitted on weekdays.¹⁰ They analyzed predetermined subgroups to identify system- and patient-level factors associated with a difference in weekend mortality.

A total of 97 studies—comprising an astounding 51 million patients—was included in the study. They found that individuals admitted on the weekend carried an almost 20% increase in the risk of death compared with those who landed in hospital on a weekday. The effect was present for both in-hospital deaths and when looking specifically at 30-day mortality. Translating these findings into practice, an additional 14 deaths per 1000 admissions occur when patients are admitted on the weekend. Brain surgery can be less risky.¹¹

Despite this concerning finding, no individual factor was identified that could account for the effect. There was a 16% and 11% increase in mortality in weekend patients associated with decreased hospital staffing and delays to procedural therapies, respectively. No differences were found when examining reduced rates of procedures or illness severity on weekends compared with weekdays. But one must always interpret subgroup analyses, even prespecified ones, with caution because they often lack the statistical power to make concrete conclusions.

To this end, an important finding of the study by Pauls et al. highlights the variation in mortality risk as it relates to the weekend effect.¹⁰ Even for individuals with cancer, a disease with a relatively predictable rate of decline, there are weekend differences in mortality risk that depend upon the type of cancer.^8,12 This heterogeneity persists when examining for the possible factors that contribute to the effect, introducing a significant amount of noise into the analysis, and may explain why research to date has been unable to find the proverbial black cat in the coal cellar.

One thing Pauls et al. makes clear is that the weekend effect appears to be a real phenomenon, despite significant heterogeneity in the literature.¹⁰ Only a high-quality, systematic review has the capability to draw such conclusions. Prior work demonstrates that this effect is substantial in some individuals,and this study confirms that it perseveres beyond an immediate time period following admission.^1,9 The elements contributing to the weekend effect remain undefined and are likely as complex as our healthcare system itself.

Society and policy makers should resist the tantalizing urge to invoke interventions aimed at fixing this issue before fully understanding the drivers of a system problem. The government of the United Kingdom has decreed a manifesto to create a “7-day National Health Service,” in which weekend services and physician staffing will match that of the weekdays. Considering recent labor tensions between junior doctors in the United Kingdom over pay and working hours, the stakes are at an all-time high.

But such drastic measures violate a primary directive of quality improvement science to study and understand the problem before reflexively jumping to solutions. This will require new research endeavors aimed at determining the underlying factor(s) responsible for the weekend effect. Once we are confident in its cause, only then can careful evaluation of targeted interventions aimed at the highest-risk admissions be instituted. As global hospital and healthcare budgets bend under increasing strain, a critical component of any proposed intervention must be to examine the cost-effectiveness in doing so. Because the weekend effect is one of increased mortality, it will be hard to justify an acceptable price for an individual’s life. And it is not as straightforward as a randomized trial examining the efficacy of parachutes. Any formal evaluation must account for the unintended consequences and opportunity costs of implementing a potential fix aimed at minimizing the weekend effect.

The weekend effect has now been studied for over 15 years. Pauls et al. add to our knowledge of this phenomenon, confirming that the overall risk of mortality for patients admitted on the weekend is real, variable, and substantial.¹⁰ As more individuals are admitted to hospitals, resulting in increasing numbers of admissions on the weekend, a desperate search for the underlying cause must be carried out before we can fix it. Whatever the means to the end, our elation will continue to be tempered by a feeling of uneasiness every time our coworkers joyously exclaim, “TGIF!”

Disclosure

The authors have nothing to disclose.

Let’s face it—rates of hospital admission are on the rise, but there are still just 7 days in a week. That means that patients are increasingly admitted on weekdays and on the weekend, requiring more nurses and doctors to look after them. Why then are there no lines for coffee on a Saturday? Does this reduced intensity of staffing translate into worse care for our patients?

Since one of its earliest descriptions in hospitalized patients, the “weekend effect” has been extensively studied in various patient populations and hospital settings.^1-5 The results have been varied, depending on the place of care,⁶ reason for care, type of admission,^5,7 or admitting diagnosis.^1,8,9 Many researchers have posited the drivers behind the weekend effect, including understaffed wards, intensity of specialist care, delays in procedural treatments, or severity of illness, but the truth is that we still don’t know.

Pauls et al. performed a robust systematic review and meta-analysis examining the rates of in-hospital mortality in patients admitted on the weekend compared with those admitted on weekdays.¹⁰ They analyzed predetermined subgroups to identify system- and patient-level factors associated with a difference in weekend mortality.

A total of 97 studies—comprising an astounding 51 million patients—was included in the study. They found that individuals admitted on the weekend carried an almost 20% increase in the risk of death compared with those who landed in hospital on a weekday. The effect was present for both in-hospital deaths and when looking specifically at 30-day mortality. Translating these findings into practice, an additional 14 deaths per 1000 admissions occur when patients are admitted on the weekend. Brain surgery can be less risky.¹¹

Despite this concerning finding, no individual factor was identified that could account for the effect. There was a 16% and 11% increase in mortality in weekend patients associated with decreased hospital staffing and delays to procedural therapies, respectively. No differences were found when examining reduced rates of procedures or illness severity on weekends compared with weekdays. But one must always interpret subgroup analyses, even prespecified ones, with caution because they often lack the statistical power to make concrete conclusions.

To this end, an important finding of the study by Pauls et al. highlights the variation in mortality risk as it relates to the weekend effect.¹⁰ Even for individuals with cancer, a disease with a relatively predictable rate of decline, there are weekend differences in mortality risk that depend upon the type of cancer.^8,12 This heterogeneity persists when examining for the possible factors that contribute to the effect, introducing a significant amount of noise into the analysis, and may explain why research to date has been unable to find the proverbial black cat in the coal cellar.

One thing Pauls et al. makes clear is that the weekend effect appears to be a real phenomenon, despite significant heterogeneity in the literature.¹⁰ Only a high-quality, systematic review has the capability to draw such conclusions. Prior work demonstrates that this effect is substantial in some individuals,and this study confirms that it perseveres beyond an immediate time period following admission.^1,9 The elements contributing to the weekend effect remain undefined and are likely as complex as our healthcare system itself.

Society and policy makers should resist the tantalizing urge to invoke interventions aimed at fixing this issue before fully understanding the drivers of a system problem. The government of the United Kingdom has decreed a manifesto to create a “7-day National Health Service,” in which weekend services and physician staffing will match that of the weekdays. Considering recent labor tensions between junior doctors in the United Kingdom over pay and working hours, the stakes are at an all-time high.

But such drastic measures violate a primary directive of quality improvement science to study and understand the problem before reflexively jumping to solutions. This will require new research endeavors aimed at determining the underlying factor(s) responsible for the weekend effect. Once we are confident in its cause, only then can careful evaluation of targeted interventions aimed at the highest-risk admissions be instituted. As global hospital and healthcare budgets bend under increasing strain, a critical component of any proposed intervention must be to examine the cost-effectiveness in doing so. Because the weekend effect is one of increased mortality, it will be hard to justify an acceptable price for an individual’s life. And it is not as straightforward as a randomized trial examining the efficacy of parachutes. Any formal evaluation must account for the unintended consequences and opportunity costs of implementing a potential fix aimed at minimizing the weekend effect.

The weekend effect has now been studied for over 15 years. Pauls et al. add to our knowledge of this phenomenon, confirming that the overall risk of mortality for patients admitted on the weekend is real, variable, and substantial.¹⁰ As more individuals are admitted to hospitals, resulting in increasing numbers of admissions on the weekend, a desperate search for the underlying cause must be carried out before we can fix it. Whatever the means to the end, our elation will continue to be tempered by a feeling of uneasiness every time our coworkers joyously exclaim, “TGIF!”

Disclosure

The authors have nothing to disclose.

Let’s face it—rates of hospital admission are on the rise, but there are still just 7 days in a week. That means that patients are increasingly admitted on weekdays and on the weekend, requiring more nurses and doctors to look after them. Why then are there no lines for coffee on a Saturday? Does this reduced intensity of staffing translate into worse care for our patients?

Since one of its earliest descriptions in hospitalized patients, the “weekend effect” has been extensively studied in various patient populations and hospital settings.^1-5 The results have been varied, depending on the place of care,⁶ reason for care, type of admission,^5,7 or admitting diagnosis.^1,8,9 Many researchers have posited the drivers behind the weekend effect, including understaffed wards, intensity of specialist care, delays in procedural treatments, or severity of illness, but the truth is that we still don’t know.

Pauls et al. performed a robust systematic review and meta-analysis examining the rates of in-hospital mortality in patients admitted on the weekend compared with those admitted on weekdays.¹⁰ They analyzed predetermined subgroups to identify system- and patient-level factors associated with a difference in weekend mortality.

A total of 97 studies—comprising an astounding 51 million patients—was included in the study. They found that individuals admitted on the weekend carried an almost 20% increase in the risk of death compared with those who landed in hospital on a weekday. The effect was present for both in-hospital deaths and when looking specifically at 30-day mortality. Translating these findings into practice, an additional 14 deaths per 1000 admissions occur when patients are admitted on the weekend. Brain surgery can be less risky.¹¹

Despite this concerning finding, no individual factor was identified that could account for the effect. There was a 16% and 11% increase in mortality in weekend patients associated with decreased hospital staffing and delays to procedural therapies, respectively. No differences were found when examining reduced rates of procedures or illness severity on weekends compared with weekdays. But one must always interpret subgroup analyses, even prespecified ones, with caution because they often lack the statistical power to make concrete conclusions.

To this end, an important finding of the study by Pauls et al. highlights the variation in mortality risk as it relates to the weekend effect.¹⁰ Even for individuals with cancer, a disease with a relatively predictable rate of decline, there are weekend differences in mortality risk that depend upon the type of cancer.^8,12 This heterogeneity persists when examining for the possible factors that contribute to the effect, introducing a significant amount of noise into the analysis, and may explain why research to date has been unable to find the proverbial black cat in the coal cellar.

One thing Pauls et al. makes clear is that the weekend effect appears to be a real phenomenon, despite significant heterogeneity in the literature.¹⁰ Only a high-quality, systematic review has the capability to draw such conclusions. Prior work demonstrates that this effect is substantial in some individuals,and this study confirms that it perseveres beyond an immediate time period following admission.^1,9 The elements contributing to the weekend effect remain undefined and are likely as complex as our healthcare system itself.

Society and policy makers should resist the tantalizing urge to invoke interventions aimed at fixing this issue before fully understanding the drivers of a system problem. The government of the United Kingdom has decreed a manifesto to create a “7-day National Health Service,” in which weekend services and physician staffing will match that of the weekdays. Considering recent labor tensions between junior doctors in the United Kingdom over pay and working hours, the stakes are at an all-time high.

But such drastic measures violate a primary directive of quality improvement science to study and understand the problem before reflexively jumping to solutions. This will require new research endeavors aimed at determining the underlying factor(s) responsible for the weekend effect. Once we are confident in its cause, only then can careful evaluation of targeted interventions aimed at the highest-risk admissions be instituted. As global hospital and healthcare budgets bend under increasing strain, a critical component of any proposed intervention must be to examine the cost-effectiveness in doing so. Because the weekend effect is one of increased mortality, it will be hard to justify an acceptable price for an individual’s life. And it is not as straightforward as a randomized trial examining the efficacy of parachutes. Any formal evaluation must account for the unintended consequences and opportunity costs of implementing a potential fix aimed at minimizing the weekend effect.

The weekend effect has now been studied for over 15 years. Pauls et al. add to our knowledge of this phenomenon, confirming that the overall risk of mortality for patients admitted on the weekend is real, variable, and substantial.¹⁰ As more individuals are admitted to hospitals, resulting in increasing numbers of admissions on the weekend, a desperate search for the underlying cause must be carried out before we can fix it. Whatever the means to the end, our elation will continue to be tempered by a feeling of uneasiness every time our coworkers joyously exclaim, “TGIF!”

Disclosure

The authors have nothing to disclose.