Sentinel Hospitalization

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The sentinel hospitalization and the role of palliative care

As hospitalists now care for expanding numbers of America's aging patients, many of whom have chronic, debilitating illnesses or are near the end of life, there is a burgeoning need for innovative approaches to optimize quality of care and control costs, especially in the last year of life.[1, 2] In the inaugural issue of the Journal of Hospital Medicine, an overview of how hospitalists and palliative care specialists can work hand‐in‐hand to care for these seriously ill, hospitalized patients was presented.[3, 4] This perspective highlighted a symbiotic and mutually beneficial relationship between the 2 specialties based on their shared values, missions, and complementary strengths.[3, 4] Since then, a number of collaborative ventures offering palliative care for seriously ill, hospitalized patients have been developed and examined in a variety of settings.[4, 5, 6]

A key collaborative undertaking for hospitalists and palliative care specialists is the appreciation of the unique trajectory of each chronic illness toward the end of life. For example, patients with cancer or neurodegenerative disease tend to have relatively stable functional status until the final months of rapid deterioration. On the other hand, the courses of patients with chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), end‐stage renal disease, and human immunodeficiency virus/acquired immunodeficiency syndrome tend to be punctuated by episodes of acute exacerbation with often nearly complete return to previous status. Finally, dementia usually follows a slow course of gradual decline leading to death.[7] Ideally, active management of symptoms and discussion of prognosis and goals of care should happen in the early stages of these chronic illnesses, yet most often they are left until an acute hospitalization late in the disease course. The following case illustrates the point.

CASE 1

Mrs. M is an 89‐year‐old woman with Alzheimer's dementia diagnosed 7 years ago who has been cared for at home by family members. She is admitted to the hospital for urinary tract infection and volume depletion. She is bedbound, cachectic, and has a stage III decubitus ulcer. Her daughter describes a 6‐month history of feeding problems, 20‐lb weight loss, and 2 recent hospitalizations for aspiration pneumonia. She improves somewhat with hydration and intravenous antibiotics, and the physical therapist recommends rehabilitation. Mrs. M does not have decision‐making capacity, and her long‐time family physician has not inquired about care preferences or goals. The hospitalist team meets with family members to discuss the trajectory and prognosis of advanced dementia, and recommends against artificial nutrition and hydration, and for initiation of palliative care service at a skilled nursing facility.

In this example, the hospitalist team recognizes the advent of frequent infections and diminished oral intake in advanced dementia as signals of increased morbidity and mortality warranting palliative care intervention.[8] This, we suggest, represents a sentinel hospitalization, a hospitalization in the disease course that heralds a need to reassess prognosis, treatment options and intensity, and goals of care. Hospitalists are well positioned to recognize such transition points in the disease course by considering the patient's recent history of illness, to offer an impartial overview of illness progression, and to optimize patient care using principles of palliative care. Additionally, hospitalists have advantages of geographic convenience, readily available consultants, systemic support, and a detachment from the longitudinal patient‐physician relationship, which may enable more accurate medical prognostication.[9]

There are many ways to identify a sentinel hospitalization. For example, hospitalists can use the surprise question, Would you be surprised if the patient died within 12 months? on admission for the majority of cancer and dialysis patients. The answer No predicts a 3.5‐ to 7‐fold increase in 1‐year mortality.[10, 11] In a powerful predictive model for 1‐year mortality using readily available clinical, laboratory, and functional characteristics, medical inpatients in the highest quartiles have 1‐year mortality exceeding 60%.[12] Recently, several more complicated prognostic models have been derived and validated in large cohorts of medical inpatients, which predict short‐term (30‐day) and long‐term (0.5‐1 year) mortality with great accuracy.[13, 14] There are also many disease‐specific prognostic features (eg, diagnosis of metastatic disease with poor performance status or high symptom burden, progression of chronic kidney disease with consideration of hemodialysis, additional stroke in multi‐infarct dementia, and frequent exacerbation of severe COPD or severe CHF).[15, 16, 17, 18, 19, 20, 21] Finally, frequent readmissions and prolonged hospital or intensive care unit stay can also be used.[17, 19] These criteria are summarized in Table 1 with time frames.

Common Criteria Defining a Sentinel Hospitalization
Common Criteria Time Frame References
  • NOTE: Abbreviations: CHF, congestive heart failure; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; GOLD, Global Initiative for Chronic Obstructive Lung Disease; ICU, intensive care unit; NYHA, New York Heart Association; PNA, pneumonia; UTI, urinary tract infection.

No to the surprise question: Would you be surprised if the patient died in 12 months? 1 year [10, 11]
Newly diagnosed metastatic solid cancer Various [17]
Metastatic solid cancer admitted for uncontrolled symptoms Various [17]
Progressive CKD with consideration for hemodialysis 1 year [17, 18]
GOLD stage IV COPD with frequent exacerbation Various [20]
NYHAstage IV CHF with frequent exacerbation 12 years [21]
Advanced dementia with frequent UTI, aspiration PNA, and feeding problem 12 years [8]
Overall prognosis of high mortality using available indices 30 days1 year [12, 13, 14]
More than 3 admissions in last 6 months 6 months [17, 19]
Prolonged ICU stay (>7 days) Weeks [17, 19]

Once a sentinel hospitalization is identified, hospitalists, with input from the patient's primary care physician and subspecialists, can then develop a comprehensive strategy to evaluate current disease management, to educate patient and family accordingly, and to actively integrate palliative care services as appropriate. The next challenge facing the care team is how to deliver the necessary palliative care since it is unnecessary and improper to ask for palliative care specialist consultation for every sentinel hospitalization. We believe that the best approach is for hospitalists to be the primary deliverers of basic palliative care in the hospital while consulting palliative care specialists for refractory symptoms and complex scenarios.[22] According to this generalist‐specialist palliative care model, physicians of all specialties should define and master a basic palliative care skill set for their patients. For hospitalists, the relevant skill set includes assessing and treating pain and other symptoms such as dyspnea, nausea and vomiting, and constipation, estimating prognosis, and initiating goals of care discussions.[22] The following case illustrates this point.

CASE 2

Ms S, a 21‐year‐old Hispanic woman with advanced, recurrent head and neck cancer, status post multiple surgeries, chemotherapy, and radiation therapy, is admitted to the hospitalist service for aspiration pneumonia, which responds to antibiotics rapidly. However, her cancer‐related somatic and neuropathic pain soon becomes refractory to opioids prescribed by the hospitalist team. She also develops significant dyspnea, xerostomia, depression, anxiety, and existential suffering. With the help of the interdisciplinary palliative care team, her pain is relieved by a patient‐controlled analgesia pump and methadone. A palliative care social worker and chaplain visit her and her family daily to address their distress. Eventually, the care team is able to provide a stable medical regimen for symptom control and to use it across the entire care continuum.

In this example, the hospitalist team, with the support of palliative care specialists, provided basic palliative care and longitudinal integration of palliative practices into the patient's overall treatment scheme. Hospitalists, given their scope of practice and sheer volume of patients, are well positioned to rapidly gain competencies in symptom management, empathic communication, and interdisciplinary teamwork.[23, 24] Hospitalists may benefit from innovative and collaborative palliative care education using interactive online modules, case simulation, communication workshops, and observed evaluation and feedback.[25] Several modes of collaboration between hospital medicine and palliative care have been developed including implementation of palliative care consult triggers on admission, palliative care participation in hospitalist interdisciplinary rounds, and disease specific, integrated management programs.[17, 26] These collaborations are particularly important, as the quality of inpatient care at the end of life is still suboptimal and more appropriate use of palliative care will be beneficial.[27] Recently, some hospitals have developed specialized inpatient palliative care units, combining intensive palliation with inpatient medical surgical level of care, as well as providing hospice care. Staffed by palliative care specialists or hospitalists, they provide efficient, cost‐saving care to patients with advanced chronic illness or terminal disease in need of intensive symptom management.[28] Finally, there is mounting evidence supporting the clinical effectiveness of palliative care in diverse specialties such as oncology, pulmonary and critical care, and nephrology.[29] For example, in the setting of metastatic non‐small cell lung cancer, early initiation of palliative care has been shown to improve symptom control and quality of life, reduce chemotherapy use at the end of life, and interestingly, prolong median survival by almost 3 months.[30] This has led to a position statement from American Society of Clinical Oncology encouraging early integration of palliative care into standard oncologic care for advanced disease.[31]

Recognizing a sentinel hospitalization allows palliative care to be integrated at transitions of care and carried forward. For patients with chronic debilitating illnesses who are approaching the end of life, appropriate care transitions will ensure that their short‐ and long‐term care matches their goals of care, assure timely clinical follow‐ups, and help reduce hospital readmission and healthcare resource utilization.[32] Importantly, timely and compassionate communication is a key to the success of both hospital medicine and palliative care. Many patients with life‐limiting diseases prefer to receive prognostic information and to discuss goals of care.[33] How this information is integrated and communicated through the care continuum is crucial, especially in the era of duty hour limits and frequent handoffs. The information exchange needs to facilitate active participation of primary care physicians who may not be involved in hospital care. Some of the innovative strategies for communication and transfer of palliative care information, such as prognosis, goals of care, family meeting consensus, and symptom control interventions, include a palliative care checklist in the electronic health record, incorporation of prognostic and family meeting information in the discharge summary, and links to the national Physician Orders for Life‐Sustaining Treatment advanced care planning program.[34] Of note, a pilot program in the United Kingdom adopting an electronic palliative care summary has reduced after‐hour emergency room visits and hospital readmissions.[35] The following case illustrates this point.

CASE 3

Mrs. K, an 82‐year‐old Russian‐speaking woman with newly diagnosed metastatic pancreatic cancer, is admitted for worsening obstructive jaundice and a second opinion about treatment. A biliary stent is placed and her jaundice slowly improves. The patient and family have requested chemotherapy. However, the oncologist determines that she would only qualify for a phase I trial given her poor performance status. The hospitalist team requests the help of the palliative care consult team to manage her severe pain, depression, and to provide support to the family. After several family meetings, the patient and family choose not to pursue chemotherapy. Given the lack of adequate support at home, she is discharged to a skilled nursing facility for short‐term rehabilitation with plans to transition to the in‐house hospice program. The hospitalist, palliative care attending physician, and the medical director of the rehabilitation facility have a 3‐way phone conference to confirm the plans of care and to ensure a smooth care transition.

In this case, the hospitalist team recognizes that this is a sentinel hospitalization for Mrs. K that requires extensive palliative care intervention. Often, transitioning to skilled nursing facilities (SNF) is the default pathway for patients needing hospice/palliative care, especially when patients and families are not yet ready to discuss prognosis realistically or to accept hospice, or there is not enough support available at home. A recent large cohort study showed that 30% of patients in their last 6‐month of life had used, and nearly 10% of such patients had died, under Medicare's posthospitalization SNF benefit.[36] Although the worsening disease trajectory may not be apparent at hospital discharge, it is more likely that the financial and practical limitation of the Medicare Hospice Benefit accounts for this observation, which includes limited home health aid hours, lack of coverage for room and board, and lower payments to SNFs.[36] Hospitalists can help address the issue of discharge location for patients needing palliative care. Sometimes this requires extensive communication before and after discharge to help enhance the transition from a rehabilitation facility to hospice/palliative care. Appropriately integrated palliative care at the time of care transitions, in the form of hospice or longitudinal home‐based palliative care rather than just routine clinic follow‐up, has the potential to reduce 30‐day readmission for chronically ill, elderly patients and for patients near the end of life.[37, 38] It is critical that national policy, suitable reimbursement, and financial incentives support this practice. A demonstration project, Better Outcomes by Optimizing Safe Transitions (BOOST), organized by the Society of Hospital Medicine, integrates palliative care evaluation into a comprehensive discharge assessment tool. This intervention has been shown to reduce readmissions to acute care hospitals.[39]

In this article, we define a sentinel hospitalization and suggest that its recognition provides an important opportunity for hospitalists to actively integrate palliative care into patients' chronic disease management programs, with inputs from patients, their families, their primary physicians and subspecialists, as well as palliative care specialists. We also recognize that within nonsentinel hospitalizations, there are important opportunities to discuss prognosis, goals of care, and advanced care planning. This approach allows the fresh eyes of hospitalists to assess the patient's current health status and prognosis, to communicate these relevant clinical issues with the patient and family, and to encourage discussions about goals of care and advanced care planning during the sentinel hospitalization. It also provides a structured vehicle for soliciting the patient's (and family's) perspectives and documenting them in the medical record. A compilation of sample items to guide discussion can be found in Table 2. Hospitalists, equipped with basic palliative care skills and supported by hospital‐ and community‐based palliative care teams, can thrive in this unique position of optimizing the quality of care for these patients.[40] Almost 20 years ago, the field of palliative care rose to national prominence on the findings of the SUPPORT (Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments) study, which investigated the suboptimal end‐of‐life experiences of hospitalized adult patients.[41] Since then, the fields of both hospital medicine and palliative care have grown, yet the best is still to come for their collaborative excellence, mutual education, and shared care innovation at the forefront of medicine.

Sample Discussion Items During a Sentinel Hospitalization
Patient/family understanding of disease process and treatment outcomes
Patient/family understanding of disease prognosis
Availability of alternative treatment options including palliative/hospice care
Patient/family wishes/goals of care
Advanced‐care planning including limitations of care
Inventory of symptoms (frequency, severity, modifying factors, timing, and treatments)
Social and financial stress
Emotional and existential stress
Social support system and caregivers
Living arrangements

Disclosure: Nothing to report.

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References
  1. Chadaga SR, Maher MP, Maller N, Mancini D, Mascolo M, Sharma S, et al. Evolving practice of hospital medicine and its impact on hospital throughput and efficiencies. J Hosp Med. 2012;7:649654.
  2. Hogan C, Lunney J, Gabel J, Lynn J. Medicare beneficiaries' costs of care in the last year of life. Health Affairs. 2001;20:188195.
  3. Meier DE. Palliative care in hospitals. J Hosp Med. 2006;1:2128.
  4. Pantilat SZ. Palliative care and hospitalists: a partnership for hope. J Hosp Med. 2006;1:56.
  5. Muir JC, Arnold RM. Palliative care and the hospitalist: an opportunity for cross‐fertilization. Am J Med. 2001;111:10s14s.
  6. Swetz KM, Kamal AH. Palliative care. Ann Intern Med. 2012;156:ITC2‐1, TC2‐2–15; quiz TC2‐16.
  7. Lunney JR, Lynn J, Foley DJ, Lipson S, Guralnik JM. Patterns of functional decline at the end of life. JAMA. 2003;289:23872392.
  8. Mitchell SL, Teno JM, Kiely DK, et al. The clinical course of advanced dementia. N Engl J Med. 2009;361:15291538.
  9. Christakis NA, Lamont EB. Extent and determinants of error in doctor's prognoses in terminally ill patients: prospective cohort study. BMJ. 2000;320:469472.
  10. Moss AH, Lunney JR, Culp S, et al. Prognostic significance of the “surprise” question in cancer patients. J Palliat Med. 2010;13:837840.
  11. Moss AH, Ganjoo J, Sharma S, et al. Utility of the “surprise” question to identify dialysis patients with high mortality. Clin J Am Soc Nephrol. 2008;3:13791384.
  12. Walter LC, Brand RJ, Counsell SR, et al. Development and validation of a prognostic index for 1‐year mortality in older adults after hospitalization. JAMA. 2001;285:29872994.
  13. Cowen ME, Strawderman RL, Czerwinski JL, Smith MJ, Halasyamani LK. Mortality predictions on admission as a context for organizing care activities. J Hosp Med. 2013,8:229235.
  14. Youngwerth J, Min S, Statland B, Allyn R, Fischer S. Caring about prognosis: a validation study of the CARING criteria to identify hospitalized patients at high risk for death at 1 year. J Hosp Med. 2013,8:696701.
  15. Downing M, Lau F, Lesperance M, Karlson N, Shaw J, Kuziemsky C, et al. Meta‐analysis of survival prediction with palliative performance scale. J Palliat Care. 2007;23:245254.
  16. Yourman LC, Lee SJ, Schonberg MA, Widera EW, Smith AK. Prognostic indices for older adults: a systemic review. JAMA. 2012;307:182192.
  17. Weissman DE, Meier DE. Identifying patients in need of a palliative care assessment in the hospital setting. J Palliat Med. 2011;14:1723.
  18. Tamura MK, Covinsky KE, Chertow GM, Yaffe K, Landefeld CS, McCulloch CE. Functional status of elderly adults before and after initiation of dialysis. N Engl J Med. 2009;361:15391547.
  19. Strand JJ, Kamdar MM, Carey EC. Top 10 things palliative care clinicians wished everyone knew about palliative care. Mayo Clin Proc. 2013;88:859865.
  20. Curtis JR. Palliative and end‐of‐life care for patients with severe COPD. Eur Respir J. 2008;32:796803.
  21. Goodlin SJ. Palliative care in congestive heart failure. J Am Coll Cardiol. 2009;54:386396.
  22. Quill TE, Abernethy AP. Generalist plus specialist palliative care—creating a more sustainable model. N Engl J Med. 2013;368:11731175.
  23. Cherlin E, Morris V, Morris J, Johnson‐Hurzeler R, Sullivan GM, Bradley EH. Common myths about caring for patients with terminal illness: opportunities to improve care in the hospital setting. J Hosp Med. 2007;2:357365.
  24. Zaros MC, Curtis JR, Silveira MJ, Elmore JG. Opportunity lost: end‐of‐life discussions in cancer patients who die in the hospital. J Hosp Med. 2013;8:334340.
  25. Case AA, Orrange SM, Weissman DE. Palliative medicine physician education in the United States: a historical review. J Palliat Med. 2013;16:230236.
  26. Widera E, Pantilat SZ. Hospitalization as an opportunity to integrate palliative care in heart failure management. Curr Opin Support Palliat Care. 2009;3:247251.
  27. Walling AM, Asch SM, Lorenz KA, et al. The quality of care provided to hospitalized patients at the end of life. Arch Intern Med. 2010;170:10571063.
  28. Eti S, O'Mahony S, McHugh M, Guilbe R, Blank A, Selwyn P. Outcomes of the acute palliative care unit in an academic medical center [published online ahead of print May 10, 2013]. Am J Hosp Palliat Care. doi: 10.1177/1049909113489164.
  29. Anderson WG, Flint LA, Horton JR, Johnson K, Mourad M, Sharpe BA. Update in hospital palliative care. J Hosp Med. 2013;12:715720.
  30. Temel JS, Greer JA, Muzikansky A, et al. Early palliative care for patients with metastatic non‐small‐cell lung cancer. N Engl J Med. 2010;363:733742.
  31. Greer JA, Jackson VA, Meier DE, Temel JS. Early integration of palliative care services with standard oncology care for patients with advanced cancer. CA Cancer J Clin. 2013;63:349363.
  32. Jack BW, Chetty VK, Anthony D, et al. A reengineered hospital discharge program to decrease rehospitalization: a randomized trial. Ann Intern Med. 2009;150:178187.
  33. Ahalt C, Walter LC, Yourman L, Eng C, Perez‐Stable EJ, Smith AK. “Knowing is better”: preferences of diverse older adults for discussion prognosis. J Gen Intern Med. 2012;27:568575.
  34. Bomba PA, Kemp M, Black JS. POLST, an improvement over traditional advanced directives. Cleve Clin J Med. 2012;79:457464.
  35. Ali AA, Adam R, Taylor D, Murchie P. Use of a structured palliative care summary in patients with established cancer is associated with reduced hospital admissions by out‐of‐hours general practitioners in Grampian [published online ahead of print January 3, 2013]. BMJ Support Palliat Care. doi:10.1136/bmjspcare‐2012‐000371.
  36. Aragon K, Covinsky K, Miao Y, Boscardin WJ, Flint L, Smith AK. Use of the Medicare posthospitalization skilled nursing benefit in the last 6 months of life. Arch Intern Med. 2012;172:15731579.
  37. Brumley R, Enguidanos S, Jamison P, et al. Increased satisfaction with care and lower costs: results of a randomized trial of in‐home palliative care. J Am Geriatr Soc. 2007;55:9931000.
  38. Enguidanos S, Vesper E, Lorenz K. 30‐day readmissions among seriously ill older adults. J Palliat Med. 2012;15:16.
  39. Hansen LO, Greenwald JL, Budnitz T, et al. Project BOOST: effectiveness of a multihospital effort to reduce rehospitalization. J Hosp Med. 2013;8:421427.
  40. Kutner JS. Ensuring safe, quality care for hospitalized people with advanced illness, a core obligation for hospitalists. J Hosp Med. 2007;2:355356.
  41. The SUPPORT Principal Investigators. A controlled trial to improve care for seriously ill hospitalized patients: the Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments (SUPPORT). JAMA. 1995;274:15911598.
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As hospitalists now care for expanding numbers of America's aging patients, many of whom have chronic, debilitating illnesses or are near the end of life, there is a burgeoning need for innovative approaches to optimize quality of care and control costs, especially in the last year of life.[1, 2] In the inaugural issue of the Journal of Hospital Medicine, an overview of how hospitalists and palliative care specialists can work hand‐in‐hand to care for these seriously ill, hospitalized patients was presented.[3, 4] This perspective highlighted a symbiotic and mutually beneficial relationship between the 2 specialties based on their shared values, missions, and complementary strengths.[3, 4] Since then, a number of collaborative ventures offering palliative care for seriously ill, hospitalized patients have been developed and examined in a variety of settings.[4, 5, 6]

A key collaborative undertaking for hospitalists and palliative care specialists is the appreciation of the unique trajectory of each chronic illness toward the end of life. For example, patients with cancer or neurodegenerative disease tend to have relatively stable functional status until the final months of rapid deterioration. On the other hand, the courses of patients with chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), end‐stage renal disease, and human immunodeficiency virus/acquired immunodeficiency syndrome tend to be punctuated by episodes of acute exacerbation with often nearly complete return to previous status. Finally, dementia usually follows a slow course of gradual decline leading to death.[7] Ideally, active management of symptoms and discussion of prognosis and goals of care should happen in the early stages of these chronic illnesses, yet most often they are left until an acute hospitalization late in the disease course. The following case illustrates the point.

CASE 1

Mrs. M is an 89‐year‐old woman with Alzheimer's dementia diagnosed 7 years ago who has been cared for at home by family members. She is admitted to the hospital for urinary tract infection and volume depletion. She is bedbound, cachectic, and has a stage III decubitus ulcer. Her daughter describes a 6‐month history of feeding problems, 20‐lb weight loss, and 2 recent hospitalizations for aspiration pneumonia. She improves somewhat with hydration and intravenous antibiotics, and the physical therapist recommends rehabilitation. Mrs. M does not have decision‐making capacity, and her long‐time family physician has not inquired about care preferences or goals. The hospitalist team meets with family members to discuss the trajectory and prognosis of advanced dementia, and recommends against artificial nutrition and hydration, and for initiation of palliative care service at a skilled nursing facility.

In this example, the hospitalist team recognizes the advent of frequent infections and diminished oral intake in advanced dementia as signals of increased morbidity and mortality warranting palliative care intervention.[8] This, we suggest, represents a sentinel hospitalization, a hospitalization in the disease course that heralds a need to reassess prognosis, treatment options and intensity, and goals of care. Hospitalists are well positioned to recognize such transition points in the disease course by considering the patient's recent history of illness, to offer an impartial overview of illness progression, and to optimize patient care using principles of palliative care. Additionally, hospitalists have advantages of geographic convenience, readily available consultants, systemic support, and a detachment from the longitudinal patient‐physician relationship, which may enable more accurate medical prognostication.[9]

There are many ways to identify a sentinel hospitalization. For example, hospitalists can use the surprise question, Would you be surprised if the patient died within 12 months? on admission for the majority of cancer and dialysis patients. The answer No predicts a 3.5‐ to 7‐fold increase in 1‐year mortality.[10, 11] In a powerful predictive model for 1‐year mortality using readily available clinical, laboratory, and functional characteristics, medical inpatients in the highest quartiles have 1‐year mortality exceeding 60%.[12] Recently, several more complicated prognostic models have been derived and validated in large cohorts of medical inpatients, which predict short‐term (30‐day) and long‐term (0.5‐1 year) mortality with great accuracy.[13, 14] There are also many disease‐specific prognostic features (eg, diagnosis of metastatic disease with poor performance status or high symptom burden, progression of chronic kidney disease with consideration of hemodialysis, additional stroke in multi‐infarct dementia, and frequent exacerbation of severe COPD or severe CHF).[15, 16, 17, 18, 19, 20, 21] Finally, frequent readmissions and prolonged hospital or intensive care unit stay can also be used.[17, 19] These criteria are summarized in Table 1 with time frames.

Common Criteria Defining a Sentinel Hospitalization
Common Criteria Time Frame References
  • NOTE: Abbreviations: CHF, congestive heart failure; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; GOLD, Global Initiative for Chronic Obstructive Lung Disease; ICU, intensive care unit; NYHA, New York Heart Association; PNA, pneumonia; UTI, urinary tract infection.

No to the surprise question: Would you be surprised if the patient died in 12 months? 1 year [10, 11]
Newly diagnosed metastatic solid cancer Various [17]
Metastatic solid cancer admitted for uncontrolled symptoms Various [17]
Progressive CKD with consideration for hemodialysis 1 year [17, 18]
GOLD stage IV COPD with frequent exacerbation Various [20]
NYHAstage IV CHF with frequent exacerbation 12 years [21]
Advanced dementia with frequent UTI, aspiration PNA, and feeding problem 12 years [8]
Overall prognosis of high mortality using available indices 30 days1 year [12, 13, 14]
More than 3 admissions in last 6 months 6 months [17, 19]
Prolonged ICU stay (>7 days) Weeks [17, 19]

Once a sentinel hospitalization is identified, hospitalists, with input from the patient's primary care physician and subspecialists, can then develop a comprehensive strategy to evaluate current disease management, to educate patient and family accordingly, and to actively integrate palliative care services as appropriate. The next challenge facing the care team is how to deliver the necessary palliative care since it is unnecessary and improper to ask for palliative care specialist consultation for every sentinel hospitalization. We believe that the best approach is for hospitalists to be the primary deliverers of basic palliative care in the hospital while consulting palliative care specialists for refractory symptoms and complex scenarios.[22] According to this generalist‐specialist palliative care model, physicians of all specialties should define and master a basic palliative care skill set for their patients. For hospitalists, the relevant skill set includes assessing and treating pain and other symptoms such as dyspnea, nausea and vomiting, and constipation, estimating prognosis, and initiating goals of care discussions.[22] The following case illustrates this point.

CASE 2

Ms S, a 21‐year‐old Hispanic woman with advanced, recurrent head and neck cancer, status post multiple surgeries, chemotherapy, and radiation therapy, is admitted to the hospitalist service for aspiration pneumonia, which responds to antibiotics rapidly. However, her cancer‐related somatic and neuropathic pain soon becomes refractory to opioids prescribed by the hospitalist team. She also develops significant dyspnea, xerostomia, depression, anxiety, and existential suffering. With the help of the interdisciplinary palliative care team, her pain is relieved by a patient‐controlled analgesia pump and methadone. A palliative care social worker and chaplain visit her and her family daily to address their distress. Eventually, the care team is able to provide a stable medical regimen for symptom control and to use it across the entire care continuum.

In this example, the hospitalist team, with the support of palliative care specialists, provided basic palliative care and longitudinal integration of palliative practices into the patient's overall treatment scheme. Hospitalists, given their scope of practice and sheer volume of patients, are well positioned to rapidly gain competencies in symptom management, empathic communication, and interdisciplinary teamwork.[23, 24] Hospitalists may benefit from innovative and collaborative palliative care education using interactive online modules, case simulation, communication workshops, and observed evaluation and feedback.[25] Several modes of collaboration between hospital medicine and palliative care have been developed including implementation of palliative care consult triggers on admission, palliative care participation in hospitalist interdisciplinary rounds, and disease specific, integrated management programs.[17, 26] These collaborations are particularly important, as the quality of inpatient care at the end of life is still suboptimal and more appropriate use of palliative care will be beneficial.[27] Recently, some hospitals have developed specialized inpatient palliative care units, combining intensive palliation with inpatient medical surgical level of care, as well as providing hospice care. Staffed by palliative care specialists or hospitalists, they provide efficient, cost‐saving care to patients with advanced chronic illness or terminal disease in need of intensive symptom management.[28] Finally, there is mounting evidence supporting the clinical effectiveness of palliative care in diverse specialties such as oncology, pulmonary and critical care, and nephrology.[29] For example, in the setting of metastatic non‐small cell lung cancer, early initiation of palliative care has been shown to improve symptom control and quality of life, reduce chemotherapy use at the end of life, and interestingly, prolong median survival by almost 3 months.[30] This has led to a position statement from American Society of Clinical Oncology encouraging early integration of palliative care into standard oncologic care for advanced disease.[31]

Recognizing a sentinel hospitalization allows palliative care to be integrated at transitions of care and carried forward. For patients with chronic debilitating illnesses who are approaching the end of life, appropriate care transitions will ensure that their short‐ and long‐term care matches their goals of care, assure timely clinical follow‐ups, and help reduce hospital readmission and healthcare resource utilization.[32] Importantly, timely and compassionate communication is a key to the success of both hospital medicine and palliative care. Many patients with life‐limiting diseases prefer to receive prognostic information and to discuss goals of care.[33] How this information is integrated and communicated through the care continuum is crucial, especially in the era of duty hour limits and frequent handoffs. The information exchange needs to facilitate active participation of primary care physicians who may not be involved in hospital care. Some of the innovative strategies for communication and transfer of palliative care information, such as prognosis, goals of care, family meeting consensus, and symptom control interventions, include a palliative care checklist in the electronic health record, incorporation of prognostic and family meeting information in the discharge summary, and links to the national Physician Orders for Life‐Sustaining Treatment advanced care planning program.[34] Of note, a pilot program in the United Kingdom adopting an electronic palliative care summary has reduced after‐hour emergency room visits and hospital readmissions.[35] The following case illustrates this point.

CASE 3

Mrs. K, an 82‐year‐old Russian‐speaking woman with newly diagnosed metastatic pancreatic cancer, is admitted for worsening obstructive jaundice and a second opinion about treatment. A biliary stent is placed and her jaundice slowly improves. The patient and family have requested chemotherapy. However, the oncologist determines that she would only qualify for a phase I trial given her poor performance status. The hospitalist team requests the help of the palliative care consult team to manage her severe pain, depression, and to provide support to the family. After several family meetings, the patient and family choose not to pursue chemotherapy. Given the lack of adequate support at home, she is discharged to a skilled nursing facility for short‐term rehabilitation with plans to transition to the in‐house hospice program. The hospitalist, palliative care attending physician, and the medical director of the rehabilitation facility have a 3‐way phone conference to confirm the plans of care and to ensure a smooth care transition.

In this case, the hospitalist team recognizes that this is a sentinel hospitalization for Mrs. K that requires extensive palliative care intervention. Often, transitioning to skilled nursing facilities (SNF) is the default pathway for patients needing hospice/palliative care, especially when patients and families are not yet ready to discuss prognosis realistically or to accept hospice, or there is not enough support available at home. A recent large cohort study showed that 30% of patients in their last 6‐month of life had used, and nearly 10% of such patients had died, under Medicare's posthospitalization SNF benefit.[36] Although the worsening disease trajectory may not be apparent at hospital discharge, it is more likely that the financial and practical limitation of the Medicare Hospice Benefit accounts for this observation, which includes limited home health aid hours, lack of coverage for room and board, and lower payments to SNFs.[36] Hospitalists can help address the issue of discharge location for patients needing palliative care. Sometimes this requires extensive communication before and after discharge to help enhance the transition from a rehabilitation facility to hospice/palliative care. Appropriately integrated palliative care at the time of care transitions, in the form of hospice or longitudinal home‐based palliative care rather than just routine clinic follow‐up, has the potential to reduce 30‐day readmission for chronically ill, elderly patients and for patients near the end of life.[37, 38] It is critical that national policy, suitable reimbursement, and financial incentives support this practice. A demonstration project, Better Outcomes by Optimizing Safe Transitions (BOOST), organized by the Society of Hospital Medicine, integrates palliative care evaluation into a comprehensive discharge assessment tool. This intervention has been shown to reduce readmissions to acute care hospitals.[39]

In this article, we define a sentinel hospitalization and suggest that its recognition provides an important opportunity for hospitalists to actively integrate palliative care into patients' chronic disease management programs, with inputs from patients, their families, their primary physicians and subspecialists, as well as palliative care specialists. We also recognize that within nonsentinel hospitalizations, there are important opportunities to discuss prognosis, goals of care, and advanced care planning. This approach allows the fresh eyes of hospitalists to assess the patient's current health status and prognosis, to communicate these relevant clinical issues with the patient and family, and to encourage discussions about goals of care and advanced care planning during the sentinel hospitalization. It also provides a structured vehicle for soliciting the patient's (and family's) perspectives and documenting them in the medical record. A compilation of sample items to guide discussion can be found in Table 2. Hospitalists, equipped with basic palliative care skills and supported by hospital‐ and community‐based palliative care teams, can thrive in this unique position of optimizing the quality of care for these patients.[40] Almost 20 years ago, the field of palliative care rose to national prominence on the findings of the SUPPORT (Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments) study, which investigated the suboptimal end‐of‐life experiences of hospitalized adult patients.[41] Since then, the fields of both hospital medicine and palliative care have grown, yet the best is still to come for their collaborative excellence, mutual education, and shared care innovation at the forefront of medicine.

Sample Discussion Items During a Sentinel Hospitalization
Patient/family understanding of disease process and treatment outcomes
Patient/family understanding of disease prognosis
Availability of alternative treatment options including palliative/hospice care
Patient/family wishes/goals of care
Advanced‐care planning including limitations of care
Inventory of symptoms (frequency, severity, modifying factors, timing, and treatments)
Social and financial stress
Emotional and existential stress
Social support system and caregivers
Living arrangements

Disclosure: Nothing to report.

As hospitalists now care for expanding numbers of America's aging patients, many of whom have chronic, debilitating illnesses or are near the end of life, there is a burgeoning need for innovative approaches to optimize quality of care and control costs, especially in the last year of life.[1, 2] In the inaugural issue of the Journal of Hospital Medicine, an overview of how hospitalists and palliative care specialists can work hand‐in‐hand to care for these seriously ill, hospitalized patients was presented.[3, 4] This perspective highlighted a symbiotic and mutually beneficial relationship between the 2 specialties based on their shared values, missions, and complementary strengths.[3, 4] Since then, a number of collaborative ventures offering palliative care for seriously ill, hospitalized patients have been developed and examined in a variety of settings.[4, 5, 6]

A key collaborative undertaking for hospitalists and palliative care specialists is the appreciation of the unique trajectory of each chronic illness toward the end of life. For example, patients with cancer or neurodegenerative disease tend to have relatively stable functional status until the final months of rapid deterioration. On the other hand, the courses of patients with chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), end‐stage renal disease, and human immunodeficiency virus/acquired immunodeficiency syndrome tend to be punctuated by episodes of acute exacerbation with often nearly complete return to previous status. Finally, dementia usually follows a slow course of gradual decline leading to death.[7] Ideally, active management of symptoms and discussion of prognosis and goals of care should happen in the early stages of these chronic illnesses, yet most often they are left until an acute hospitalization late in the disease course. The following case illustrates the point.

CASE 1

Mrs. M is an 89‐year‐old woman with Alzheimer's dementia diagnosed 7 years ago who has been cared for at home by family members. She is admitted to the hospital for urinary tract infection and volume depletion. She is bedbound, cachectic, and has a stage III decubitus ulcer. Her daughter describes a 6‐month history of feeding problems, 20‐lb weight loss, and 2 recent hospitalizations for aspiration pneumonia. She improves somewhat with hydration and intravenous antibiotics, and the physical therapist recommends rehabilitation. Mrs. M does not have decision‐making capacity, and her long‐time family physician has not inquired about care preferences or goals. The hospitalist team meets with family members to discuss the trajectory and prognosis of advanced dementia, and recommends against artificial nutrition and hydration, and for initiation of palliative care service at a skilled nursing facility.

In this example, the hospitalist team recognizes the advent of frequent infections and diminished oral intake in advanced dementia as signals of increased morbidity and mortality warranting palliative care intervention.[8] This, we suggest, represents a sentinel hospitalization, a hospitalization in the disease course that heralds a need to reassess prognosis, treatment options and intensity, and goals of care. Hospitalists are well positioned to recognize such transition points in the disease course by considering the patient's recent history of illness, to offer an impartial overview of illness progression, and to optimize patient care using principles of palliative care. Additionally, hospitalists have advantages of geographic convenience, readily available consultants, systemic support, and a detachment from the longitudinal patient‐physician relationship, which may enable more accurate medical prognostication.[9]

There are many ways to identify a sentinel hospitalization. For example, hospitalists can use the surprise question, Would you be surprised if the patient died within 12 months? on admission for the majority of cancer and dialysis patients. The answer No predicts a 3.5‐ to 7‐fold increase in 1‐year mortality.[10, 11] In a powerful predictive model for 1‐year mortality using readily available clinical, laboratory, and functional characteristics, medical inpatients in the highest quartiles have 1‐year mortality exceeding 60%.[12] Recently, several more complicated prognostic models have been derived and validated in large cohorts of medical inpatients, which predict short‐term (30‐day) and long‐term (0.5‐1 year) mortality with great accuracy.[13, 14] There are also many disease‐specific prognostic features (eg, diagnosis of metastatic disease with poor performance status or high symptom burden, progression of chronic kidney disease with consideration of hemodialysis, additional stroke in multi‐infarct dementia, and frequent exacerbation of severe COPD or severe CHF).[15, 16, 17, 18, 19, 20, 21] Finally, frequent readmissions and prolonged hospital or intensive care unit stay can also be used.[17, 19] These criteria are summarized in Table 1 with time frames.

Common Criteria Defining a Sentinel Hospitalization
Common Criteria Time Frame References
  • NOTE: Abbreviations: CHF, congestive heart failure; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; GOLD, Global Initiative for Chronic Obstructive Lung Disease; ICU, intensive care unit; NYHA, New York Heart Association; PNA, pneumonia; UTI, urinary tract infection.

No to the surprise question: Would you be surprised if the patient died in 12 months? 1 year [10, 11]
Newly diagnosed metastatic solid cancer Various [17]
Metastatic solid cancer admitted for uncontrolled symptoms Various [17]
Progressive CKD with consideration for hemodialysis 1 year [17, 18]
GOLD stage IV COPD with frequent exacerbation Various [20]
NYHAstage IV CHF with frequent exacerbation 12 years [21]
Advanced dementia with frequent UTI, aspiration PNA, and feeding problem 12 years [8]
Overall prognosis of high mortality using available indices 30 days1 year [12, 13, 14]
More than 3 admissions in last 6 months 6 months [17, 19]
Prolonged ICU stay (>7 days) Weeks [17, 19]

Once a sentinel hospitalization is identified, hospitalists, with input from the patient's primary care physician and subspecialists, can then develop a comprehensive strategy to evaluate current disease management, to educate patient and family accordingly, and to actively integrate palliative care services as appropriate. The next challenge facing the care team is how to deliver the necessary palliative care since it is unnecessary and improper to ask for palliative care specialist consultation for every sentinel hospitalization. We believe that the best approach is for hospitalists to be the primary deliverers of basic palliative care in the hospital while consulting palliative care specialists for refractory symptoms and complex scenarios.[22] According to this generalist‐specialist palliative care model, physicians of all specialties should define and master a basic palliative care skill set for their patients. For hospitalists, the relevant skill set includes assessing and treating pain and other symptoms such as dyspnea, nausea and vomiting, and constipation, estimating prognosis, and initiating goals of care discussions.[22] The following case illustrates this point.

CASE 2

Ms S, a 21‐year‐old Hispanic woman with advanced, recurrent head and neck cancer, status post multiple surgeries, chemotherapy, and radiation therapy, is admitted to the hospitalist service for aspiration pneumonia, which responds to antibiotics rapidly. However, her cancer‐related somatic and neuropathic pain soon becomes refractory to opioids prescribed by the hospitalist team. She also develops significant dyspnea, xerostomia, depression, anxiety, and existential suffering. With the help of the interdisciplinary palliative care team, her pain is relieved by a patient‐controlled analgesia pump and methadone. A palliative care social worker and chaplain visit her and her family daily to address their distress. Eventually, the care team is able to provide a stable medical regimen for symptom control and to use it across the entire care continuum.

In this example, the hospitalist team, with the support of palliative care specialists, provided basic palliative care and longitudinal integration of palliative practices into the patient's overall treatment scheme. Hospitalists, given their scope of practice and sheer volume of patients, are well positioned to rapidly gain competencies in symptom management, empathic communication, and interdisciplinary teamwork.[23, 24] Hospitalists may benefit from innovative and collaborative palliative care education using interactive online modules, case simulation, communication workshops, and observed evaluation and feedback.[25] Several modes of collaboration between hospital medicine and palliative care have been developed including implementation of palliative care consult triggers on admission, palliative care participation in hospitalist interdisciplinary rounds, and disease specific, integrated management programs.[17, 26] These collaborations are particularly important, as the quality of inpatient care at the end of life is still suboptimal and more appropriate use of palliative care will be beneficial.[27] Recently, some hospitals have developed specialized inpatient palliative care units, combining intensive palliation with inpatient medical surgical level of care, as well as providing hospice care. Staffed by palliative care specialists or hospitalists, they provide efficient, cost‐saving care to patients with advanced chronic illness or terminal disease in need of intensive symptom management.[28] Finally, there is mounting evidence supporting the clinical effectiveness of palliative care in diverse specialties such as oncology, pulmonary and critical care, and nephrology.[29] For example, in the setting of metastatic non‐small cell lung cancer, early initiation of palliative care has been shown to improve symptom control and quality of life, reduce chemotherapy use at the end of life, and interestingly, prolong median survival by almost 3 months.[30] This has led to a position statement from American Society of Clinical Oncology encouraging early integration of palliative care into standard oncologic care for advanced disease.[31]

Recognizing a sentinel hospitalization allows palliative care to be integrated at transitions of care and carried forward. For patients with chronic debilitating illnesses who are approaching the end of life, appropriate care transitions will ensure that their short‐ and long‐term care matches their goals of care, assure timely clinical follow‐ups, and help reduce hospital readmission and healthcare resource utilization.[32] Importantly, timely and compassionate communication is a key to the success of both hospital medicine and palliative care. Many patients with life‐limiting diseases prefer to receive prognostic information and to discuss goals of care.[33] How this information is integrated and communicated through the care continuum is crucial, especially in the era of duty hour limits and frequent handoffs. The information exchange needs to facilitate active participation of primary care physicians who may not be involved in hospital care. Some of the innovative strategies for communication and transfer of palliative care information, such as prognosis, goals of care, family meeting consensus, and symptom control interventions, include a palliative care checklist in the electronic health record, incorporation of prognostic and family meeting information in the discharge summary, and links to the national Physician Orders for Life‐Sustaining Treatment advanced care planning program.[34] Of note, a pilot program in the United Kingdom adopting an electronic palliative care summary has reduced after‐hour emergency room visits and hospital readmissions.[35] The following case illustrates this point.

CASE 3

Mrs. K, an 82‐year‐old Russian‐speaking woman with newly diagnosed metastatic pancreatic cancer, is admitted for worsening obstructive jaundice and a second opinion about treatment. A biliary stent is placed and her jaundice slowly improves. The patient and family have requested chemotherapy. However, the oncologist determines that she would only qualify for a phase I trial given her poor performance status. The hospitalist team requests the help of the palliative care consult team to manage her severe pain, depression, and to provide support to the family. After several family meetings, the patient and family choose not to pursue chemotherapy. Given the lack of adequate support at home, she is discharged to a skilled nursing facility for short‐term rehabilitation with plans to transition to the in‐house hospice program. The hospitalist, palliative care attending physician, and the medical director of the rehabilitation facility have a 3‐way phone conference to confirm the plans of care and to ensure a smooth care transition.

In this case, the hospitalist team recognizes that this is a sentinel hospitalization for Mrs. K that requires extensive palliative care intervention. Often, transitioning to skilled nursing facilities (SNF) is the default pathway for patients needing hospice/palliative care, especially when patients and families are not yet ready to discuss prognosis realistically or to accept hospice, or there is not enough support available at home. A recent large cohort study showed that 30% of patients in their last 6‐month of life had used, and nearly 10% of such patients had died, under Medicare's posthospitalization SNF benefit.[36] Although the worsening disease trajectory may not be apparent at hospital discharge, it is more likely that the financial and practical limitation of the Medicare Hospice Benefit accounts for this observation, which includes limited home health aid hours, lack of coverage for room and board, and lower payments to SNFs.[36] Hospitalists can help address the issue of discharge location for patients needing palliative care. Sometimes this requires extensive communication before and after discharge to help enhance the transition from a rehabilitation facility to hospice/palliative care. Appropriately integrated palliative care at the time of care transitions, in the form of hospice or longitudinal home‐based palliative care rather than just routine clinic follow‐up, has the potential to reduce 30‐day readmission for chronically ill, elderly patients and for patients near the end of life.[37, 38] It is critical that national policy, suitable reimbursement, and financial incentives support this practice. A demonstration project, Better Outcomes by Optimizing Safe Transitions (BOOST), organized by the Society of Hospital Medicine, integrates palliative care evaluation into a comprehensive discharge assessment tool. This intervention has been shown to reduce readmissions to acute care hospitals.[39]

In this article, we define a sentinel hospitalization and suggest that its recognition provides an important opportunity for hospitalists to actively integrate palliative care into patients' chronic disease management programs, with inputs from patients, their families, their primary physicians and subspecialists, as well as palliative care specialists. We also recognize that within nonsentinel hospitalizations, there are important opportunities to discuss prognosis, goals of care, and advanced care planning. This approach allows the fresh eyes of hospitalists to assess the patient's current health status and prognosis, to communicate these relevant clinical issues with the patient and family, and to encourage discussions about goals of care and advanced care planning during the sentinel hospitalization. It also provides a structured vehicle for soliciting the patient's (and family's) perspectives and documenting them in the medical record. A compilation of sample items to guide discussion can be found in Table 2. Hospitalists, equipped with basic palliative care skills and supported by hospital‐ and community‐based palliative care teams, can thrive in this unique position of optimizing the quality of care for these patients.[40] Almost 20 years ago, the field of palliative care rose to national prominence on the findings of the SUPPORT (Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments) study, which investigated the suboptimal end‐of‐life experiences of hospitalized adult patients.[41] Since then, the fields of both hospital medicine and palliative care have grown, yet the best is still to come for their collaborative excellence, mutual education, and shared care innovation at the forefront of medicine.

Sample Discussion Items During a Sentinel Hospitalization
Patient/family understanding of disease process and treatment outcomes
Patient/family understanding of disease prognosis
Availability of alternative treatment options including palliative/hospice care
Patient/family wishes/goals of care
Advanced‐care planning including limitations of care
Inventory of symptoms (frequency, severity, modifying factors, timing, and treatments)
Social and financial stress
Emotional and existential stress
Social support system and caregivers
Living arrangements

Disclosure: Nothing to report.

References
  1. Chadaga SR, Maher MP, Maller N, Mancini D, Mascolo M, Sharma S, et al. Evolving practice of hospital medicine and its impact on hospital throughput and efficiencies. J Hosp Med. 2012;7:649654.
  2. Hogan C, Lunney J, Gabel J, Lynn J. Medicare beneficiaries' costs of care in the last year of life. Health Affairs. 2001;20:188195.
  3. Meier DE. Palliative care in hospitals. J Hosp Med. 2006;1:2128.
  4. Pantilat SZ. Palliative care and hospitalists: a partnership for hope. J Hosp Med. 2006;1:56.
  5. Muir JC, Arnold RM. Palliative care and the hospitalist: an opportunity for cross‐fertilization. Am J Med. 2001;111:10s14s.
  6. Swetz KM, Kamal AH. Palliative care. Ann Intern Med. 2012;156:ITC2‐1, TC2‐2–15; quiz TC2‐16.
  7. Lunney JR, Lynn J, Foley DJ, Lipson S, Guralnik JM. Patterns of functional decline at the end of life. JAMA. 2003;289:23872392.
  8. Mitchell SL, Teno JM, Kiely DK, et al. The clinical course of advanced dementia. N Engl J Med. 2009;361:15291538.
  9. Christakis NA, Lamont EB. Extent and determinants of error in doctor's prognoses in terminally ill patients: prospective cohort study. BMJ. 2000;320:469472.
  10. Moss AH, Lunney JR, Culp S, et al. Prognostic significance of the “surprise” question in cancer patients. J Palliat Med. 2010;13:837840.
  11. Moss AH, Ganjoo J, Sharma S, et al. Utility of the “surprise” question to identify dialysis patients with high mortality. Clin J Am Soc Nephrol. 2008;3:13791384.
  12. Walter LC, Brand RJ, Counsell SR, et al. Development and validation of a prognostic index for 1‐year mortality in older adults after hospitalization. JAMA. 2001;285:29872994.
  13. Cowen ME, Strawderman RL, Czerwinski JL, Smith MJ, Halasyamani LK. Mortality predictions on admission as a context for organizing care activities. J Hosp Med. 2013,8:229235.
  14. Youngwerth J, Min S, Statland B, Allyn R, Fischer S. Caring about prognosis: a validation study of the CARING criteria to identify hospitalized patients at high risk for death at 1 year. J Hosp Med. 2013,8:696701.
  15. Downing M, Lau F, Lesperance M, Karlson N, Shaw J, Kuziemsky C, et al. Meta‐analysis of survival prediction with palliative performance scale. J Palliat Care. 2007;23:245254.
  16. Yourman LC, Lee SJ, Schonberg MA, Widera EW, Smith AK. Prognostic indices for older adults: a systemic review. JAMA. 2012;307:182192.
  17. Weissman DE, Meier DE. Identifying patients in need of a palliative care assessment in the hospital setting. J Palliat Med. 2011;14:1723.
  18. Tamura MK, Covinsky KE, Chertow GM, Yaffe K, Landefeld CS, McCulloch CE. Functional status of elderly adults before and after initiation of dialysis. N Engl J Med. 2009;361:15391547.
  19. Strand JJ, Kamdar MM, Carey EC. Top 10 things palliative care clinicians wished everyone knew about palliative care. Mayo Clin Proc. 2013;88:859865.
  20. Curtis JR. Palliative and end‐of‐life care for patients with severe COPD. Eur Respir J. 2008;32:796803.
  21. Goodlin SJ. Palliative care in congestive heart failure. J Am Coll Cardiol. 2009;54:386396.
  22. Quill TE, Abernethy AP. Generalist plus specialist palliative care—creating a more sustainable model. N Engl J Med. 2013;368:11731175.
  23. Cherlin E, Morris V, Morris J, Johnson‐Hurzeler R, Sullivan GM, Bradley EH. Common myths about caring for patients with terminal illness: opportunities to improve care in the hospital setting. J Hosp Med. 2007;2:357365.
  24. Zaros MC, Curtis JR, Silveira MJ, Elmore JG. Opportunity lost: end‐of‐life discussions in cancer patients who die in the hospital. J Hosp Med. 2013;8:334340.
  25. Case AA, Orrange SM, Weissman DE. Palliative medicine physician education in the United States: a historical review. J Palliat Med. 2013;16:230236.
  26. Widera E, Pantilat SZ. Hospitalization as an opportunity to integrate palliative care in heart failure management. Curr Opin Support Palliat Care. 2009;3:247251.
  27. Walling AM, Asch SM, Lorenz KA, et al. The quality of care provided to hospitalized patients at the end of life. Arch Intern Med. 2010;170:10571063.
  28. Eti S, O'Mahony S, McHugh M, Guilbe R, Blank A, Selwyn P. Outcomes of the acute palliative care unit in an academic medical center [published online ahead of print May 10, 2013]. Am J Hosp Palliat Care. doi: 10.1177/1049909113489164.
  29. Anderson WG, Flint LA, Horton JR, Johnson K, Mourad M, Sharpe BA. Update in hospital palliative care. J Hosp Med. 2013;12:715720.
  30. Temel JS, Greer JA, Muzikansky A, et al. Early palliative care for patients with metastatic non‐small‐cell lung cancer. N Engl J Med. 2010;363:733742.
  31. Greer JA, Jackson VA, Meier DE, Temel JS. Early integration of palliative care services with standard oncology care for patients with advanced cancer. CA Cancer J Clin. 2013;63:349363.
  32. Jack BW, Chetty VK, Anthony D, et al. A reengineered hospital discharge program to decrease rehospitalization: a randomized trial. Ann Intern Med. 2009;150:178187.
  33. Ahalt C, Walter LC, Yourman L, Eng C, Perez‐Stable EJ, Smith AK. “Knowing is better”: preferences of diverse older adults for discussion prognosis. J Gen Intern Med. 2012;27:568575.
  34. Bomba PA, Kemp M, Black JS. POLST, an improvement over traditional advanced directives. Cleve Clin J Med. 2012;79:457464.
  35. Ali AA, Adam R, Taylor D, Murchie P. Use of a structured palliative care summary in patients with established cancer is associated with reduced hospital admissions by out‐of‐hours general practitioners in Grampian [published online ahead of print January 3, 2013]. BMJ Support Palliat Care. doi:10.1136/bmjspcare‐2012‐000371.
  36. Aragon K, Covinsky K, Miao Y, Boscardin WJ, Flint L, Smith AK. Use of the Medicare posthospitalization skilled nursing benefit in the last 6 months of life. Arch Intern Med. 2012;172:15731579.
  37. Brumley R, Enguidanos S, Jamison P, et al. Increased satisfaction with care and lower costs: results of a randomized trial of in‐home palliative care. J Am Geriatr Soc. 2007;55:9931000.
  38. Enguidanos S, Vesper E, Lorenz K. 30‐day readmissions among seriously ill older adults. J Palliat Med. 2012;15:16.
  39. Hansen LO, Greenwald JL, Budnitz T, et al. Project BOOST: effectiveness of a multihospital effort to reduce rehospitalization. J Hosp Med. 2013;8:421427.
  40. Kutner JS. Ensuring safe, quality care for hospitalized people with advanced illness, a core obligation for hospitalists. J Hosp Med. 2007;2:355356.
  41. The SUPPORT Principal Investigators. A controlled trial to improve care for seriously ill hospitalized patients: the Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments (SUPPORT). JAMA. 1995;274:15911598.
References
  1. Chadaga SR, Maher MP, Maller N, Mancini D, Mascolo M, Sharma S, et al. Evolving practice of hospital medicine and its impact on hospital throughput and efficiencies. J Hosp Med. 2012;7:649654.
  2. Hogan C, Lunney J, Gabel J, Lynn J. Medicare beneficiaries' costs of care in the last year of life. Health Affairs. 2001;20:188195.
  3. Meier DE. Palliative care in hospitals. J Hosp Med. 2006;1:2128.
  4. Pantilat SZ. Palliative care and hospitalists: a partnership for hope. J Hosp Med. 2006;1:56.
  5. Muir JC, Arnold RM. Palliative care and the hospitalist: an opportunity for cross‐fertilization. Am J Med. 2001;111:10s14s.
  6. Swetz KM, Kamal AH. Palliative care. Ann Intern Med. 2012;156:ITC2‐1, TC2‐2–15; quiz TC2‐16.
  7. Lunney JR, Lynn J, Foley DJ, Lipson S, Guralnik JM. Patterns of functional decline at the end of life. JAMA. 2003;289:23872392.
  8. Mitchell SL, Teno JM, Kiely DK, et al. The clinical course of advanced dementia. N Engl J Med. 2009;361:15291538.
  9. Christakis NA, Lamont EB. Extent and determinants of error in doctor's prognoses in terminally ill patients: prospective cohort study. BMJ. 2000;320:469472.
  10. Moss AH, Lunney JR, Culp S, et al. Prognostic significance of the “surprise” question in cancer patients. J Palliat Med. 2010;13:837840.
  11. Moss AH, Ganjoo J, Sharma S, et al. Utility of the “surprise” question to identify dialysis patients with high mortality. Clin J Am Soc Nephrol. 2008;3:13791384.
  12. Walter LC, Brand RJ, Counsell SR, et al. Development and validation of a prognostic index for 1‐year mortality in older adults after hospitalization. JAMA. 2001;285:29872994.
  13. Cowen ME, Strawderman RL, Czerwinski JL, Smith MJ, Halasyamani LK. Mortality predictions on admission as a context for organizing care activities. J Hosp Med. 2013,8:229235.
  14. Youngwerth J, Min S, Statland B, Allyn R, Fischer S. Caring about prognosis: a validation study of the CARING criteria to identify hospitalized patients at high risk for death at 1 year. J Hosp Med. 2013,8:696701.
  15. Downing M, Lau F, Lesperance M, Karlson N, Shaw J, Kuziemsky C, et al. Meta‐analysis of survival prediction with palliative performance scale. J Palliat Care. 2007;23:245254.
  16. Yourman LC, Lee SJ, Schonberg MA, Widera EW, Smith AK. Prognostic indices for older adults: a systemic review. JAMA. 2012;307:182192.
  17. Weissman DE, Meier DE. Identifying patients in need of a palliative care assessment in the hospital setting. J Palliat Med. 2011;14:1723.
  18. Tamura MK, Covinsky KE, Chertow GM, Yaffe K, Landefeld CS, McCulloch CE. Functional status of elderly adults before and after initiation of dialysis. N Engl J Med. 2009;361:15391547.
  19. Strand JJ, Kamdar MM, Carey EC. Top 10 things palliative care clinicians wished everyone knew about palliative care. Mayo Clin Proc. 2013;88:859865.
  20. Curtis JR. Palliative and end‐of‐life care for patients with severe COPD. Eur Respir J. 2008;32:796803.
  21. Goodlin SJ. Palliative care in congestive heart failure. J Am Coll Cardiol. 2009;54:386396.
  22. Quill TE, Abernethy AP. Generalist plus specialist palliative care—creating a more sustainable model. N Engl J Med. 2013;368:11731175.
  23. Cherlin E, Morris V, Morris J, Johnson‐Hurzeler R, Sullivan GM, Bradley EH. Common myths about caring for patients with terminal illness: opportunities to improve care in the hospital setting. J Hosp Med. 2007;2:357365.
  24. Zaros MC, Curtis JR, Silveira MJ, Elmore JG. Opportunity lost: end‐of‐life discussions in cancer patients who die in the hospital. J Hosp Med. 2013;8:334340.
  25. Case AA, Orrange SM, Weissman DE. Palliative medicine physician education in the United States: a historical review. J Palliat Med. 2013;16:230236.
  26. Widera E, Pantilat SZ. Hospitalization as an opportunity to integrate palliative care in heart failure management. Curr Opin Support Palliat Care. 2009;3:247251.
  27. Walling AM, Asch SM, Lorenz KA, et al. The quality of care provided to hospitalized patients at the end of life. Arch Intern Med. 2010;170:10571063.
  28. Eti S, O'Mahony S, McHugh M, Guilbe R, Blank A, Selwyn P. Outcomes of the acute palliative care unit in an academic medical center [published online ahead of print May 10, 2013]. Am J Hosp Palliat Care. doi: 10.1177/1049909113489164.
  29. Anderson WG, Flint LA, Horton JR, Johnson K, Mourad M, Sharpe BA. Update in hospital palliative care. J Hosp Med. 2013;12:715720.
  30. Temel JS, Greer JA, Muzikansky A, et al. Early palliative care for patients with metastatic non‐small‐cell lung cancer. N Engl J Med. 2010;363:733742.
  31. Greer JA, Jackson VA, Meier DE, Temel JS. Early integration of palliative care services with standard oncology care for patients with advanced cancer. CA Cancer J Clin. 2013;63:349363.
  32. Jack BW, Chetty VK, Anthony D, et al. A reengineered hospital discharge program to decrease rehospitalization: a randomized trial. Ann Intern Med. 2009;150:178187.
  33. Ahalt C, Walter LC, Yourman L, Eng C, Perez‐Stable EJ, Smith AK. “Knowing is better”: preferences of diverse older adults for discussion prognosis. J Gen Intern Med. 2012;27:568575.
  34. Bomba PA, Kemp M, Black JS. POLST, an improvement over traditional advanced directives. Cleve Clin J Med. 2012;79:457464.
  35. Ali AA, Adam R, Taylor D, Murchie P. Use of a structured palliative care summary in patients with established cancer is associated with reduced hospital admissions by out‐of‐hours general practitioners in Grampian [published online ahead of print January 3, 2013]. BMJ Support Palliat Care. doi:10.1136/bmjspcare‐2012‐000371.
  36. Aragon K, Covinsky K, Miao Y, Boscardin WJ, Flint L, Smith AK. Use of the Medicare posthospitalization skilled nursing benefit in the last 6 months of life. Arch Intern Med. 2012;172:15731579.
  37. Brumley R, Enguidanos S, Jamison P, et al. Increased satisfaction with care and lower costs: results of a randomized trial of in‐home palliative care. J Am Geriatr Soc. 2007;55:9931000.
  38. Enguidanos S, Vesper E, Lorenz K. 30‐day readmissions among seriously ill older adults. J Palliat Med. 2012;15:16.
  39. Hansen LO, Greenwald JL, Budnitz T, et al. Project BOOST: effectiveness of a multihospital effort to reduce rehospitalization. J Hosp Med. 2013;8:421427.
  40. Kutner JS. Ensuring safe, quality care for hospitalized people with advanced illness, a core obligation for hospitalists. J Hosp Med. 2007;2:355356.
  41. The SUPPORT Principal Investigators. A controlled trial to improve care for seriously ill hospitalized patients: the Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments (SUPPORT). JAMA. 1995;274:15911598.
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The carewell in hospital questionnaire: A measure of frail elderly inpatient experiences with individualized and integrated hospital care

Patient‐reported quality of care is currently an important outcome measure. Ideally, quality of care is assessed by measuring patient's experiences rather than patient satisfaction, as most patients are satisfied with the care they receive, even if the quality is poor.[1] Within the study of the CareWell in Hospital (CWH) program[2]which aims to improve quality of care for frail inpatients age 70 yearswe aimed to assess experiences using a questionnaire to determine the quality of hospital care from the perspective of elderly inpatients. This questionnaire should specifically address whether individualized, integrated care is delivered, with an emphasis on autonomy and maintaining patient independence as well as integrating well‐being into hospital care, all of which are aims of the CWH program. In this, it follows the perspective of integrated care as enabling the achievement of common goals and optimal care results from the patients' view: Care should be sensitive to the characteristics and needs of individual patients.[3]

In the Netherlands, a patient questionnaire to measure experiences with hospital care was carefully developed (partially based on the Consumer Assessment of Healthcare Providers and Systems) and is used to obtain information for national benchmarking: the Consumer Quality Index (CQI).[4] However, we considered this questionnaire containing 78 core questions as well as the time between discharge and measurement (often several months) too long for frail elderly patients, as they have complex, multidisciplinary needs and may have difficulty communicating their needs and reporting their experienced quality of care.

Here, we report on the development and validation of a questionnaire that is based on the CQI and can be used to measure the quality of individualized and integrated hospital care as experienced by inpatients age 70 years.

METHODS

Development

The predefined criteria for the questionnaire were that it should be brief, thereby reducing the burden placed on frail elderly persons; cover the aims of CWH; and measure experiences rather than satisfaction.

Ten categories were initially formulated to match CWH's goals of autonomy, independence, well‐being, individualized care, communication, coordination of care, continuity of care, patient safety, and competence of physicians and nurses. Items from the CQI questionnaire database[5] were selected for each category. Ten members of a panel representing the elderly target group were invited to select the 3 most important questions in each category (first Delphi round). This panel is an important party within a regional network of care and well‐being organizations and involved in discussing the various regional care and/or well‐being projects when it concerns their content and value for elderly persons. They represent elderly persons through their position in elderly‐care or informal care organizations or from personal experiences. During a second Delphi round, they determined whether the individual items of the concept questionnaire were clearly stated, comprehensible to frail elderly patients, represent quality of care, have appropriate answer categories, and so forth. The final questionnaire was edited to match the reading level of a 12‐year‐old and approved by the panel in a face‐to‐face meeting. By this process, content validity was ensured.[6]

Data Collection

The final questionnaire was mailed to both frail and nonfrail medical and surgical inpatients who were included in the CWH before‐after study (January 2011 to July 2012) 1 week after their discharge, by a research assistant (see Supporting Information, Appendix A, in the online version of this article for a description of the study and CWH program).

Patients in the CWH study who returned the questionnaire during the postimplementation measurement period were asked to participate in the test‐retest reliability study until a predetermined sample size of 75 was reached (March 2012 to November 2012). The target interval between returning the first and second questionnaire was 2 to 14 days.[7]

In addition, patients admitted to the geriatrics departmentand therefore assumed to be frailreceived the questionnaire upon discharge (February 2012 to April 2013). The geriatrics department administered the questionnaire anonymously for evaluation and quality‐improvement purposes, as part of usual care. The secretary included the questionnaire in all patient files, and a nurse provided the questionnaire to patients together with other important discharge documents. This questionnaire also included a question regarding goal attainment, as this reflects whether what is important to the most frail elderly patients was accomplished.

Validation and Analysis

Data were analyzed using the statistical software program SPSS version 18.0 (SPSS Inc., Chicago, IL.).

Data

Characteristics of (non)responders, levels of missing data, and measurement range were assessed using descriptive statistics.

Reliability

Internal consistency was assessed by calculating Cronbach's for all available questionnaires with complete data. The answer categories were recoded to a 010 scale; 10 represents the highest quality of care. Test‐retest reliability[6] was assessed by calculating Cohen's for individual questions and intraclass correlation (ICC) for the questionnaire's mean score.

Validity

The following hypotheses were tested in order to assess construct validity: lower scores for female patients[8] and for patients who rate their health lower,[9] and with higher education[8, 9]; higher scores for patients who had an elective admission[8] and whose treatment goals were achieved (own reasoning). Finally, whether patients answered the questionnaire independently or with help should not affect scores (own reasoning). The Spearman was calculated for nonparametric and ordinal data.

In addition, we performed a Kruskal‐Wallis analysis to test the hypothesis that patients admitted to different departments have different scores. Second, we used the Mann‐Whitney U test to detect differences before and after implementation of the CWH program.

For all these analyses, only questionnaires with complete data were included.

RESULTS

Development

The selected answers within the categories communication and competence of nurses and physicians by the panel overlapped with questions from the other 8 categories; thus, the final questionnaire contains 8 core questions (Table 1) (see Supporting Information, Appendix B, in the online version of this article).

The 8 Core Questions of the CareWell in Hospital Questionnaire
Question
  • NOTE: The questionnaire for the geriatrics department included 1 additional question: Within a few days of your hospital admission, a doctor discussed the goal of the admission with you. Did you achieve your goal(s) satisfactorily? (no, not at all; yes, partially; yes, completely; don't know; doctor did not discuss my goals). See Supporting Information, Appendix A, in the online version of this article for the entire questionnaire, including the answer categories.

1. Were you informed sufficiently by your doctor regarding the various options for treating your health problems?
2. Were you able to indicate which treatment and/or care you preferred?
3. During your hospital stay, could you co‐decide what was important to your care?
4. During your hospital stay, were you supported in keeping busy and finding social contacts and activities?
5. Did you know to whom you can go within the hospital with questions, problems, or complaints?
6. Before discharge, did you talk with a member of the hospital staff regarding the care you would need after discharge?
7. Did a member of the hospital staff inform the key people and/or care providers of your discharge from the hospital?
8. During your hospital stay, did you experience 1 or more of the following events?
Did you fall?
Did you become confused?
Did you develop pressure ulcers?
Did medication errors occur?
Did you develop a urinary tract infection?
Did you develop a wound infection?
Did you experience complications with your surgery and/or treatment?

Data Collection

Figure 1 shows a flowchart of the questionnaires.

Figure 1
Flowchart of the available questionnaires returned by elderly inpatients. Abbreviations: CWH, CareWell in Hospital.

Table 2 presents data of responders compared with nonresponders who were included in the CWH study (N = 293). Patients were age 70 years and admitted 48 hours. Patients responded 14.8 11.3 days after discharge (n = 265). Response rate was 75.8%. From 18 responders no baseline characteristics were available, as only the questionnaire was collected from them to reach n = 75 for test‐retest purposes.

Characteristics of the Responding (n = 293) and Nonresponding (n = 88) Patients Included in the CareWell in Hospital Before‐After Study
No. Responders No. Nonresponders P Value
  • NOTE: Data on baseline characteristics from 18 patients in the post‐CWH measurement period are missing, and from those patients only the CareWell in Hospital questionnaires were gathered in order to reach n = 75 for test‐retest purposes. CIRS‐G ranging from 0 to 56 (with a higher score indicating more comorbidity).[14] MMSE ranging from 0 to 30 (with 30 representing the best score). Length of stay is defined as the time between admission to a CWH study department and discharge from a CWH study department. Abbreviations: CIRS‐G, Cumulative Illness Rating ScaleGeriatrics; CWH, CareWell in Hospital; MMSE, Mini‐Mental State Examination; SD, standard deviation.

Age, y SD 275 76.9 5.2 88 77.3 5.5 0.701
Male sex, n (%) 275 156 (56.7) 88 52 (59.1) 0.696
CIRS‐G, score SD 274 12.8 5.0 88 13.9 5.0 0.071
MMSE admission, score SD 264 26.7 3.7 82 25.1 4.8 0.001
MMSE discharge, score SD 230 26.9 3.7 66 25.8 4.4 0.026
Length of stay, days SD 275 8.2 7.4 88 9.6 9.7 0.322
Department, surgical (%) 275 170 (61.8) 88 56 (63.6) 0.759
Admission type, n (%) 275 88 0.343
Emergency 82 (29.8) 22 (25.0)
Elective 138 (50.2) 52 (59.1)
From other hospital or other department 55 (20.0) 14 (15.9)
Marital status, alone (%) 273 187 (68.5) 84 50 (59.5) 0.128
Discharge destination, n (%) 275 88 0.000
Home 197 (71.6) 54 (61.4)
Other hospital 69 (25.1) 20 (22.7)
Care facility 9 (3.3) 14 (15.9)
Readmission, n (%) 275 38 (13.8) 88 7 (8.0) 0.146
Readmission <1 mo, n (%) 275 28 (10.2) 88 14 (15.9) 0.144
Death <3 mo following discharge, n (%) 274 9 (3.3) 86 5 (5.8) 0.233
Received CWH intervention 149 43 (28.9) 33 15 (45.5) 0.064

Patients in the geriatrics department responded in 10.5 15.0 days (n = 111). Mean length of stay was 9.0 7.2 days (n = 116). Data regarding other baseline characteristics and response rate were unavailable due to privacy concerns.

Data Characteristics

Table 3 summarizes data of all 470 questionnaires. Response rates to the answer options ranged from 3.8% to 66.8%. Missing data among the questions ranged from 1.7% within question 8 to 7.0% within question 4. Upon combining the answer categories I don't know and missing, 7/8 questions had >10% missing data; the questions 2 and 3 had the highest percentage of missing data due to the I don't know answer option. The reasons stated by the respondents for why they could not answer these questions included cognitive disabilities; the perception that, because there was only one option (eg, in case of emergency admissions), the question did not apply to them; and/or that the patients preferred not to co‐decide because they felt that the physician knows best and can decide what is best.

Data Quality and Range and Test‐Retest Reliability of All Questionnaires Received
Data (n = 470) Test‐Retest (n = 78)
No. % No.
  • NOTE: For adverse events, the minimum amount of missing data was 1.7%. Sum scores range from 0 to 80. Mean scores range from 0 to 10. = Cohen's . Abbreviations: DK, don't know; ICC, intraclass correlation coefficient; Max, maximum; MIS, missing.

Sufficiently informed regarding treatment options 65 0.278
Not at all 23 4.9
Sometimes 90 19.1
Often 115 24.5
Every time 191 40.6
Don't know 29 6.2
Missing 21 4.7
Treatment and care preferences discussed 59 0.415
Not at all 89 18.9
Sometimes 78 16.6
Often 61 13.0
Every time 111 23.6
Don't know 103 21.9
Missing 28 6.0
Co‐decide regarding important issues 56 0.295
Not at all 75 16.0
Sometimes 86 18.3
Often 67 14.3
Every time 112 23.8
Don't know 98 20.9
Missing 32 6.8
Supported in finding (social) activities 73 0.533
Not at all 72 15.3
A little 66 14.0
Good 109 23.2
Very good 36 7.7
Not applicable 130 27.7
Don't know 24 5.1
Missing 33 7.0
Knows relevant person for questions, problems, complaints 77 0.652
Yes 279 59.4
No 107 22.8
Don't know 67 14.3
Missing 17 3.6
Discussed postdischarge care needs 75 0.574
Yes, sufficient 311 66.2
Yes, but insufficient 26 5.5
No 99 20.3
I don't know/I don't remember 18 3.8
Missing 19 4.0
Hospital informed other important people/providers of discharge 69 0.405
No 45 9.6
Some were informed 54 11.5
Yes 314 66.8
Don't know 38 8.1
Missing 19 4.0
Adverse events during hospital admission DK MIS 78 0.816
Fall, confusion, pressure ulcer, medication error, bladder infection, wound infection, complication of surgery/treatment Max 9.1% Max 4.3%
Sum Mean No. ICC
Mean score on the total questionnaire, complete cases (n = 222) 51.9 18.3 6.5 2.3 39 0.745

Reliability

Of the 470 questionnaires, 222 (47.2%) had complete data and were used to analyze internal consistency. Cronbach's for the 8‐item questionnaire was 0.70 (good internal consistency).

Seventy‐eight questionnaires were available to measure test‐retest reliability. The interval between test‐retest was 8.7 4.8 days; 94.7% was returned within the targeted 14 days. Thirty‐eight patients had complete data for both measurements: ICC on the mean score of the questionnaire was 0.75 (95% confidence interval [CI]: 0.56‐0.86), which indicates good test‐retest reliability (Table 3). Including patients with incomplete data (1 to 2 missing items) yielded an ICC >0.70. Among the individual questions, Cohen's ranged from 0.28 to 0.82.

Validity

The mean questionnaire score was significantly correlated with goals achieved while hospitalized (Table 4).

Construct Validity of the CareWell in Hospital Questionnaire Based on All Questionnaires With Complete Data on Both the Variable and the Questionnaire Score
Variable Response No.a Score SD Correlation
  • NOTE: Mean scores range from 0 to 10. Abbreviations: F, female; M, male; SD, standard deviation.

  • The number differs per analysis. Education level was not known for every patient; this variable was extracted from a different questionnaire. Admission type includes only emergency admission and elective admission; patients could also be transferred from another department or hospital, but this was not included as a category as this might include emergency as well as elective admissions. Goal of admission was only available for patients from the geriatrics department, whereas educational level and admission type were not available for patients from the geriatrics department.

  • Correlation (Spearman ) is significant at the 0.01 level (1‐tailed for goal achieved).

Sex M 114 6.3 2.3 0.080
F 108 6.7 2.3
Health status Excellent 1 0.071
Very good 5 7.9 2.0
Good 52 6.7 2.4
Fair 120 6.5 2.2
Poor 28 6.2 2.1
Education level <6 grades primary school 4 4.9 1.2 0.068
Primary school 19 6.4 2.5
Higher than primary school 6 7.6 1.2
Practical training 27 6.0 2.2
Secondary vocational training 41 6.1 2.5
Pre‐university education 2 7.2 4.0
University/higher education 20 6.8 2.2
Admission type Emergency 31 6.5 2.6 0.015
Elective 61 6.6 2.0
Goal of admission achieved Yes 33 7.6 1.7 0.319b
Partially 24 6.6 2.1
No 6 4.7 2.8
Respondent Patient only 117 6.7 2.2 0.063
Patient with help 59 5.9 2.3
Other person 41 6.7 2.4

Mean scores did not differ significantly between departments (geriatrics: 6.8 2.2, n = 88; cardiothoracic surgery and lung diseases: 6.5 2.4, n = 54; internal medicine: 6.3 2.5, n = 30; general surgery: 6.0 2.2, n = 50; P = 0.234).

In addition, mean scores did not differ significantly before (6.5 2.2, n = 53) and after (6.1 2.4, n = 67) implementation of the CWH study (P = 0.320).

DISCUSSION

The CareWell in Hospital patient questionnaire is a brief 8‐item questionnaire to assess the experiences of elderly patients regarding integrated hospital care. It showed good internal consistency and test‐retest reliability, and low responsiveness. Here we discuss some issues related to the preset criteria of the questionnaire.

First, a panel representing the elderly target population was used to develop the questionnaire in order to ensure content validity, which was confirmed by good internal consistency. Yet, with respect to individualized, integrated care for frail elderly patients, we recommend including a question regarding the involvement of informal caregivers during the hospital stay, as they are important partners in healthcare.[10]

Second, the questionnaire was kept short because it should not be a burden and feasible for frail patients to complete. Nonetheless, some of the questions had a high nonresponse rate, and many patients answered I don't know, particularly to the questions 2 and 3. It does not necessarily mean that these questions are poor in quality; it could also indicate that offering individualized care is not yet embedded in the culture of elderly patients and care professionals, such that patients consider such questions to be irrelevant.[11, 12] Nevertheless, we suggest to further explore the feasibility of the questionnaire and potential additional methods for the most frail elderly,[13] who might have been excluded from the CWH study sample at this point (Table 2).

Third, the questionnaire measures experiences rather than satisfaction. Patient‐satisfaction scores are generally tightly correlated with the age, sex, education level, health status, and the person completing the questionnaire.[8] In our study, the correlation did not reach statistical significance. Nevertheless, the achievement of preset goals was correlated significantly with mean CWH scores (Table 4). These findings may indicate that individualized care experiences can indeed be assessed better using this questionnaire. Test‐retest reliability also supports validity, as we expectedand, indeed, sawhigher reliability among the more objective questions (eg, question 8). The most valuing question is question 1, which also had the lowest reliability; the word sufficiently should perhaps be removed in the next version in order to increase its reliability and objectivity.

Finally, scores did not differ between before and after implementation of the CWH program, which suggests either that the questionnaire is unable to detect change or that the program was not sufficiently effective to invoke change yet. The latter option seems plausible, as changes in the provision of individualized care were ongoing. In addition, the items on which favorable differences can be seen for CWH are in fact the items that could be most directly influenced by the CWH interventionists, questions 4, 6, and 7 (see Supporting Information, Appendix C, in the online version of this article). Lastly, we performed an extra analysis concerning the discriminating property of the questionnaire in a subgroup of frail elderly patients; we do see a significant difference in scores between the frail patients in the geriatrics department and the frail patients who received the CWH intervention: 6.8 (n = 88) vs 4.8 (n = 13) for complete data, respectively, P = 0.013; and 6.8 (n = 155) vs 5.7 (n = 37) for incomplete data (2 items missing), P = 0.017 (Mann‐Whitney U test). This may indicate that the questionnaire can measure differences in quality of care for specifically the frail elderly patients between departments. However, these issuesincluding validity and reliability characteristics per specific patient subgroupwarrant further research using a larger sample.

CONCLUSIONS

In conclusion, the CareWell in Hospital patient questionnaire is a feasible and reliable tool for assessing experiences of frail elderly inpatients in the provision of individualized, integrated care. To improve the questionnaire, we recommend to add a question regarding the participation of informal caregivers during the hospital stay, investigate the response rate to questions regarding participation and shared decision‐making, and study responsiveness issues further.

Acknowledgements

The authors thank Gerda van Straaten, Anne Kuijpers, and Thijs Cauven for their support with data collection. We thank all members of the ZOWEL Study Group and the panel representing the elderly target group.

Disclosures: The work was made possible by grant 60‐6190‐098‐272 and grant 60‐61900‐98‐129 of the National Programme for Elderly Care, coordinated and sponsored by ZonMw, The Netherlands, Organization of Health Research and Development. The authors report no conflicts of interest.

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References
  1. Kalucy L, Katterl R, Jackson‐Bowers E. Patient Experience of Health Care Performance. Adelaide, Australia: Primary Health Care Research November 2009. Available at: http://dspace.flinders.edu.au/jspui/bitstream/2328/26594/1/PIR NOV 09 Full.pdf.
  2. Bakker FC, Persoon A, Schoon Y, Rikkert MGM. Hospital Elder Life Program integrated in Dutch hospital care: a pilot study. J Am Geriatr Soc. 2013;61(4):641642.
  3. Kodner DL, Spreeuwenberg C. Integrated care: meaning, logic, applications, and implications—a discussion paper. Int J Integr Care. 2002;2:e12.
  4. Sixma H, Spreeuwenberg P, Zuidgeest M, Rademakers J. CQ‐index Ziekenhuisopname: meetinstrumentontwikkeling. Kwaliteit van de zorg tijdens ziekenhuisopnames vanuit het perspectief van patiënten. De ontwikkeling van het instrument, de psychometrische eigenschappen en het discriminerend vermogen [in Dutch]. Utrecht, The Netherlands: NIVEL (Netherlands Institute for Health Services Research), 2009.
  5. Centrum Klantervaring Zorg.CQI vragenbank (CQI questionnaire database). Available at: http://nvl002.nivel.nl/CQI. Accessed May–June 2010.
  6. Terwee CB, Bot SD, Boer MR, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol. 2007;60(1):3442.
  7. Streiner D, Norman G. Health Measurement Scales: A Practical Guide to Their Development and Use. 4th ed. Oxford, UK: Oxford University Press; 2008:182–183.
  8. Hordacre AL, Taylor A, Pirone C, Adams RJ. Assessing patient satisfaction: implications for South Australian public hospitals. Aust Health Rev. 2005;29(4):439446.
  9. Hekkert KD, Cihangir S, Kleefstra SM, Berg B, Kool RB. Patient satisfaction revisited: a multilevel approach. Soc Sci Med. 2009;69(1):6875.
  10. Wressle E, Eriksson L, Fahlander A, et al. Relatives' perspective on the quality of geriatric care and rehabilitation—development and testing of a questionnaire. Scand J Caring Sci. 2008;22(4):590595.
  11. Ekdahl AW, Andersson L, Wiréhn AB, Friedrichsen M. Are elderly people with co‐morbidities involved adequately in medical decision making when hospitalised? A cross‐sectional survey. BMC Geriatr. 2011;11:46.
  12. Wilkinson C, Khanji M, Cotter PE, Dunne O, O'Keeffe ST. Preferences of acutely ill patients for participation in medical decision‐making. Qual Saf Health Care. 2008;17(2):97100.
  13. Goldberg SE, Harwood RH. Experience of general hospital care in older patients with cognitive impairment: are we measuring the most vulnerable patients' experience? BMJ Qual Saf. 2013;doi:10.1136/bmjqs‐2013‐001961.
  14. Miller M, Towers A. A Manual of Guidelines for Scoring the Cumulative Illness Rating Scale for Geriatrics (CIRS‐G). Pittsburgh, PA: University of Pittsburgh School of Medicine, Department of Geriatric Psychiatry; 1991.
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Patient‐reported quality of care is currently an important outcome measure. Ideally, quality of care is assessed by measuring patient's experiences rather than patient satisfaction, as most patients are satisfied with the care they receive, even if the quality is poor.[1] Within the study of the CareWell in Hospital (CWH) program[2]which aims to improve quality of care for frail inpatients age 70 yearswe aimed to assess experiences using a questionnaire to determine the quality of hospital care from the perspective of elderly inpatients. This questionnaire should specifically address whether individualized, integrated care is delivered, with an emphasis on autonomy and maintaining patient independence as well as integrating well‐being into hospital care, all of which are aims of the CWH program. In this, it follows the perspective of integrated care as enabling the achievement of common goals and optimal care results from the patients' view: Care should be sensitive to the characteristics and needs of individual patients.[3]

In the Netherlands, a patient questionnaire to measure experiences with hospital care was carefully developed (partially based on the Consumer Assessment of Healthcare Providers and Systems) and is used to obtain information for national benchmarking: the Consumer Quality Index (CQI).[4] However, we considered this questionnaire containing 78 core questions as well as the time between discharge and measurement (often several months) too long for frail elderly patients, as they have complex, multidisciplinary needs and may have difficulty communicating their needs and reporting their experienced quality of care.

Here, we report on the development and validation of a questionnaire that is based on the CQI and can be used to measure the quality of individualized and integrated hospital care as experienced by inpatients age 70 years.

METHODS

Development

The predefined criteria for the questionnaire were that it should be brief, thereby reducing the burden placed on frail elderly persons; cover the aims of CWH; and measure experiences rather than satisfaction.

Ten categories were initially formulated to match CWH's goals of autonomy, independence, well‐being, individualized care, communication, coordination of care, continuity of care, patient safety, and competence of physicians and nurses. Items from the CQI questionnaire database[5] were selected for each category. Ten members of a panel representing the elderly target group were invited to select the 3 most important questions in each category (first Delphi round). This panel is an important party within a regional network of care and well‐being organizations and involved in discussing the various regional care and/or well‐being projects when it concerns their content and value for elderly persons. They represent elderly persons through their position in elderly‐care or informal care organizations or from personal experiences. During a second Delphi round, they determined whether the individual items of the concept questionnaire were clearly stated, comprehensible to frail elderly patients, represent quality of care, have appropriate answer categories, and so forth. The final questionnaire was edited to match the reading level of a 12‐year‐old and approved by the panel in a face‐to‐face meeting. By this process, content validity was ensured.[6]

Data Collection

The final questionnaire was mailed to both frail and nonfrail medical and surgical inpatients who were included in the CWH before‐after study (January 2011 to July 2012) 1 week after their discharge, by a research assistant (see Supporting Information, Appendix A, in the online version of this article for a description of the study and CWH program).

Patients in the CWH study who returned the questionnaire during the postimplementation measurement period were asked to participate in the test‐retest reliability study until a predetermined sample size of 75 was reached (March 2012 to November 2012). The target interval between returning the first and second questionnaire was 2 to 14 days.[7]

In addition, patients admitted to the geriatrics departmentand therefore assumed to be frailreceived the questionnaire upon discharge (February 2012 to April 2013). The geriatrics department administered the questionnaire anonymously for evaluation and quality‐improvement purposes, as part of usual care. The secretary included the questionnaire in all patient files, and a nurse provided the questionnaire to patients together with other important discharge documents. This questionnaire also included a question regarding goal attainment, as this reflects whether what is important to the most frail elderly patients was accomplished.

Validation and Analysis

Data were analyzed using the statistical software program SPSS version 18.0 (SPSS Inc., Chicago, IL.).

Data

Characteristics of (non)responders, levels of missing data, and measurement range were assessed using descriptive statistics.

Reliability

Internal consistency was assessed by calculating Cronbach's for all available questionnaires with complete data. The answer categories were recoded to a 010 scale; 10 represents the highest quality of care. Test‐retest reliability[6] was assessed by calculating Cohen's for individual questions and intraclass correlation (ICC) for the questionnaire's mean score.

Validity

The following hypotheses were tested in order to assess construct validity: lower scores for female patients[8] and for patients who rate their health lower,[9] and with higher education[8, 9]; higher scores for patients who had an elective admission[8] and whose treatment goals were achieved (own reasoning). Finally, whether patients answered the questionnaire independently or with help should not affect scores (own reasoning). The Spearman was calculated for nonparametric and ordinal data.

In addition, we performed a Kruskal‐Wallis analysis to test the hypothesis that patients admitted to different departments have different scores. Second, we used the Mann‐Whitney U test to detect differences before and after implementation of the CWH program.

For all these analyses, only questionnaires with complete data were included.

RESULTS

Development

The selected answers within the categories communication and competence of nurses and physicians by the panel overlapped with questions from the other 8 categories; thus, the final questionnaire contains 8 core questions (Table 1) (see Supporting Information, Appendix B, in the online version of this article).

The 8 Core Questions of the CareWell in Hospital Questionnaire
Question
  • NOTE: The questionnaire for the geriatrics department included 1 additional question: Within a few days of your hospital admission, a doctor discussed the goal of the admission with you. Did you achieve your goal(s) satisfactorily? (no, not at all; yes, partially; yes, completely; don't know; doctor did not discuss my goals). See Supporting Information, Appendix A, in the online version of this article for the entire questionnaire, including the answer categories.

1. Were you informed sufficiently by your doctor regarding the various options for treating your health problems?
2. Were you able to indicate which treatment and/or care you preferred?
3. During your hospital stay, could you co‐decide what was important to your care?
4. During your hospital stay, were you supported in keeping busy and finding social contacts and activities?
5. Did you know to whom you can go within the hospital with questions, problems, or complaints?
6. Before discharge, did you talk with a member of the hospital staff regarding the care you would need after discharge?
7. Did a member of the hospital staff inform the key people and/or care providers of your discharge from the hospital?
8. During your hospital stay, did you experience 1 or more of the following events?
Did you fall?
Did you become confused?
Did you develop pressure ulcers?
Did medication errors occur?
Did you develop a urinary tract infection?
Did you develop a wound infection?
Did you experience complications with your surgery and/or treatment?

Data Collection

Figure 1 shows a flowchart of the questionnaires.

Figure 1
Flowchart of the available questionnaires returned by elderly inpatients. Abbreviations: CWH, CareWell in Hospital.

Table 2 presents data of responders compared with nonresponders who were included in the CWH study (N = 293). Patients were age 70 years and admitted 48 hours. Patients responded 14.8 11.3 days after discharge (n = 265). Response rate was 75.8%. From 18 responders no baseline characteristics were available, as only the questionnaire was collected from them to reach n = 75 for test‐retest purposes.

Characteristics of the Responding (n = 293) and Nonresponding (n = 88) Patients Included in the CareWell in Hospital Before‐After Study
No. Responders No. Nonresponders P Value
  • NOTE: Data on baseline characteristics from 18 patients in the post‐CWH measurement period are missing, and from those patients only the CareWell in Hospital questionnaires were gathered in order to reach n = 75 for test‐retest purposes. CIRS‐G ranging from 0 to 56 (with a higher score indicating more comorbidity).[14] MMSE ranging from 0 to 30 (with 30 representing the best score). Length of stay is defined as the time between admission to a CWH study department and discharge from a CWH study department. Abbreviations: CIRS‐G, Cumulative Illness Rating ScaleGeriatrics; CWH, CareWell in Hospital; MMSE, Mini‐Mental State Examination; SD, standard deviation.

Age, y SD 275 76.9 5.2 88 77.3 5.5 0.701
Male sex, n (%) 275 156 (56.7) 88 52 (59.1) 0.696
CIRS‐G, score SD 274 12.8 5.0 88 13.9 5.0 0.071
MMSE admission, score SD 264 26.7 3.7 82 25.1 4.8 0.001
MMSE discharge, score SD 230 26.9 3.7 66 25.8 4.4 0.026
Length of stay, days SD 275 8.2 7.4 88 9.6 9.7 0.322
Department, surgical (%) 275 170 (61.8) 88 56 (63.6) 0.759
Admission type, n (%) 275 88 0.343
Emergency 82 (29.8) 22 (25.0)
Elective 138 (50.2) 52 (59.1)
From other hospital or other department 55 (20.0) 14 (15.9)
Marital status, alone (%) 273 187 (68.5) 84 50 (59.5) 0.128
Discharge destination, n (%) 275 88 0.000
Home 197 (71.6) 54 (61.4)
Other hospital 69 (25.1) 20 (22.7)
Care facility 9 (3.3) 14 (15.9)
Readmission, n (%) 275 38 (13.8) 88 7 (8.0) 0.146
Readmission <1 mo, n (%) 275 28 (10.2) 88 14 (15.9) 0.144
Death <3 mo following discharge, n (%) 274 9 (3.3) 86 5 (5.8) 0.233
Received CWH intervention 149 43 (28.9) 33 15 (45.5) 0.064

Patients in the geriatrics department responded in 10.5 15.0 days (n = 111). Mean length of stay was 9.0 7.2 days (n = 116). Data regarding other baseline characteristics and response rate were unavailable due to privacy concerns.

Data Characteristics

Table 3 summarizes data of all 470 questionnaires. Response rates to the answer options ranged from 3.8% to 66.8%. Missing data among the questions ranged from 1.7% within question 8 to 7.0% within question 4. Upon combining the answer categories I don't know and missing, 7/8 questions had >10% missing data; the questions 2 and 3 had the highest percentage of missing data due to the I don't know answer option. The reasons stated by the respondents for why they could not answer these questions included cognitive disabilities; the perception that, because there was only one option (eg, in case of emergency admissions), the question did not apply to them; and/or that the patients preferred not to co‐decide because they felt that the physician knows best and can decide what is best.

Data Quality and Range and Test‐Retest Reliability of All Questionnaires Received
Data (n = 470) Test‐Retest (n = 78)
No. % No.
  • NOTE: For adverse events, the minimum amount of missing data was 1.7%. Sum scores range from 0 to 80. Mean scores range from 0 to 10. = Cohen's . Abbreviations: DK, don't know; ICC, intraclass correlation coefficient; Max, maximum; MIS, missing.

Sufficiently informed regarding treatment options 65 0.278
Not at all 23 4.9
Sometimes 90 19.1
Often 115 24.5
Every time 191 40.6
Don't know 29 6.2
Missing 21 4.7
Treatment and care preferences discussed 59 0.415
Not at all 89 18.9
Sometimes 78 16.6
Often 61 13.0
Every time 111 23.6
Don't know 103 21.9
Missing 28 6.0
Co‐decide regarding important issues 56 0.295
Not at all 75 16.0
Sometimes 86 18.3
Often 67 14.3
Every time 112 23.8
Don't know 98 20.9
Missing 32 6.8
Supported in finding (social) activities 73 0.533
Not at all 72 15.3
A little 66 14.0
Good 109 23.2
Very good 36 7.7
Not applicable 130 27.7
Don't know 24 5.1
Missing 33 7.0
Knows relevant person for questions, problems, complaints 77 0.652
Yes 279 59.4
No 107 22.8
Don't know 67 14.3
Missing 17 3.6
Discussed postdischarge care needs 75 0.574
Yes, sufficient 311 66.2
Yes, but insufficient 26 5.5
No 99 20.3
I don't know/I don't remember 18 3.8
Missing 19 4.0
Hospital informed other important people/providers of discharge 69 0.405
No 45 9.6
Some were informed 54 11.5
Yes 314 66.8
Don't know 38 8.1
Missing 19 4.0
Adverse events during hospital admission DK MIS 78 0.816
Fall, confusion, pressure ulcer, medication error, bladder infection, wound infection, complication of surgery/treatment Max 9.1% Max 4.3%
Sum Mean No. ICC
Mean score on the total questionnaire, complete cases (n = 222) 51.9 18.3 6.5 2.3 39 0.745

Reliability

Of the 470 questionnaires, 222 (47.2%) had complete data and were used to analyze internal consistency. Cronbach's for the 8‐item questionnaire was 0.70 (good internal consistency).

Seventy‐eight questionnaires were available to measure test‐retest reliability. The interval between test‐retest was 8.7 4.8 days; 94.7% was returned within the targeted 14 days. Thirty‐eight patients had complete data for both measurements: ICC on the mean score of the questionnaire was 0.75 (95% confidence interval [CI]: 0.56‐0.86), which indicates good test‐retest reliability (Table 3). Including patients with incomplete data (1 to 2 missing items) yielded an ICC >0.70. Among the individual questions, Cohen's ranged from 0.28 to 0.82.

Validity

The mean questionnaire score was significantly correlated with goals achieved while hospitalized (Table 4).

Construct Validity of the CareWell in Hospital Questionnaire Based on All Questionnaires With Complete Data on Both the Variable and the Questionnaire Score
Variable Response No.a Score SD Correlation
  • NOTE: Mean scores range from 0 to 10. Abbreviations: F, female; M, male; SD, standard deviation.

  • The number differs per analysis. Education level was not known for every patient; this variable was extracted from a different questionnaire. Admission type includes only emergency admission and elective admission; patients could also be transferred from another department or hospital, but this was not included as a category as this might include emergency as well as elective admissions. Goal of admission was only available for patients from the geriatrics department, whereas educational level and admission type were not available for patients from the geriatrics department.

  • Correlation (Spearman ) is significant at the 0.01 level (1‐tailed for goal achieved).

Sex M 114 6.3 2.3 0.080
F 108 6.7 2.3
Health status Excellent 1 0.071
Very good 5 7.9 2.0
Good 52 6.7 2.4
Fair 120 6.5 2.2
Poor 28 6.2 2.1
Education level <6 grades primary school 4 4.9 1.2 0.068
Primary school 19 6.4 2.5
Higher than primary school 6 7.6 1.2
Practical training 27 6.0 2.2
Secondary vocational training 41 6.1 2.5
Pre‐university education 2 7.2 4.0
University/higher education 20 6.8 2.2
Admission type Emergency 31 6.5 2.6 0.015
Elective 61 6.6 2.0
Goal of admission achieved Yes 33 7.6 1.7 0.319b
Partially 24 6.6 2.1
No 6 4.7 2.8
Respondent Patient only 117 6.7 2.2 0.063
Patient with help 59 5.9 2.3
Other person 41 6.7 2.4

Mean scores did not differ significantly between departments (geriatrics: 6.8 2.2, n = 88; cardiothoracic surgery and lung diseases: 6.5 2.4, n = 54; internal medicine: 6.3 2.5, n = 30; general surgery: 6.0 2.2, n = 50; P = 0.234).

In addition, mean scores did not differ significantly before (6.5 2.2, n = 53) and after (6.1 2.4, n = 67) implementation of the CWH study (P = 0.320).

DISCUSSION

The CareWell in Hospital patient questionnaire is a brief 8‐item questionnaire to assess the experiences of elderly patients regarding integrated hospital care. It showed good internal consistency and test‐retest reliability, and low responsiveness. Here we discuss some issues related to the preset criteria of the questionnaire.

First, a panel representing the elderly target population was used to develop the questionnaire in order to ensure content validity, which was confirmed by good internal consistency. Yet, with respect to individualized, integrated care for frail elderly patients, we recommend including a question regarding the involvement of informal caregivers during the hospital stay, as they are important partners in healthcare.[10]

Second, the questionnaire was kept short because it should not be a burden and feasible for frail patients to complete. Nonetheless, some of the questions had a high nonresponse rate, and many patients answered I don't know, particularly to the questions 2 and 3. It does not necessarily mean that these questions are poor in quality; it could also indicate that offering individualized care is not yet embedded in the culture of elderly patients and care professionals, such that patients consider such questions to be irrelevant.[11, 12] Nevertheless, we suggest to further explore the feasibility of the questionnaire and potential additional methods for the most frail elderly,[13] who might have been excluded from the CWH study sample at this point (Table 2).

Third, the questionnaire measures experiences rather than satisfaction. Patient‐satisfaction scores are generally tightly correlated with the age, sex, education level, health status, and the person completing the questionnaire.[8] In our study, the correlation did not reach statistical significance. Nevertheless, the achievement of preset goals was correlated significantly with mean CWH scores (Table 4). These findings may indicate that individualized care experiences can indeed be assessed better using this questionnaire. Test‐retest reliability also supports validity, as we expectedand, indeed, sawhigher reliability among the more objective questions (eg, question 8). The most valuing question is question 1, which also had the lowest reliability; the word sufficiently should perhaps be removed in the next version in order to increase its reliability and objectivity.

Finally, scores did not differ between before and after implementation of the CWH program, which suggests either that the questionnaire is unable to detect change or that the program was not sufficiently effective to invoke change yet. The latter option seems plausible, as changes in the provision of individualized care were ongoing. In addition, the items on which favorable differences can be seen for CWH are in fact the items that could be most directly influenced by the CWH interventionists, questions 4, 6, and 7 (see Supporting Information, Appendix C, in the online version of this article). Lastly, we performed an extra analysis concerning the discriminating property of the questionnaire in a subgroup of frail elderly patients; we do see a significant difference in scores between the frail patients in the geriatrics department and the frail patients who received the CWH intervention: 6.8 (n = 88) vs 4.8 (n = 13) for complete data, respectively, P = 0.013; and 6.8 (n = 155) vs 5.7 (n = 37) for incomplete data (2 items missing), P = 0.017 (Mann‐Whitney U test). This may indicate that the questionnaire can measure differences in quality of care for specifically the frail elderly patients between departments. However, these issuesincluding validity and reliability characteristics per specific patient subgroupwarrant further research using a larger sample.

CONCLUSIONS

In conclusion, the CareWell in Hospital patient questionnaire is a feasible and reliable tool for assessing experiences of frail elderly inpatients in the provision of individualized, integrated care. To improve the questionnaire, we recommend to add a question regarding the participation of informal caregivers during the hospital stay, investigate the response rate to questions regarding participation and shared decision‐making, and study responsiveness issues further.

Acknowledgements

The authors thank Gerda van Straaten, Anne Kuijpers, and Thijs Cauven for their support with data collection. We thank all members of the ZOWEL Study Group and the panel representing the elderly target group.

Disclosures: The work was made possible by grant 60‐6190‐098‐272 and grant 60‐61900‐98‐129 of the National Programme for Elderly Care, coordinated and sponsored by ZonMw, The Netherlands, Organization of Health Research and Development. The authors report no conflicts of interest.

Patient‐reported quality of care is currently an important outcome measure. Ideally, quality of care is assessed by measuring patient's experiences rather than patient satisfaction, as most patients are satisfied with the care they receive, even if the quality is poor.[1] Within the study of the CareWell in Hospital (CWH) program[2]which aims to improve quality of care for frail inpatients age 70 yearswe aimed to assess experiences using a questionnaire to determine the quality of hospital care from the perspective of elderly inpatients. This questionnaire should specifically address whether individualized, integrated care is delivered, with an emphasis on autonomy and maintaining patient independence as well as integrating well‐being into hospital care, all of which are aims of the CWH program. In this, it follows the perspective of integrated care as enabling the achievement of common goals and optimal care results from the patients' view: Care should be sensitive to the characteristics and needs of individual patients.[3]

In the Netherlands, a patient questionnaire to measure experiences with hospital care was carefully developed (partially based on the Consumer Assessment of Healthcare Providers and Systems) and is used to obtain information for national benchmarking: the Consumer Quality Index (CQI).[4] However, we considered this questionnaire containing 78 core questions as well as the time between discharge and measurement (often several months) too long for frail elderly patients, as they have complex, multidisciplinary needs and may have difficulty communicating their needs and reporting their experienced quality of care.

Here, we report on the development and validation of a questionnaire that is based on the CQI and can be used to measure the quality of individualized and integrated hospital care as experienced by inpatients age 70 years.

METHODS

Development

The predefined criteria for the questionnaire were that it should be brief, thereby reducing the burden placed on frail elderly persons; cover the aims of CWH; and measure experiences rather than satisfaction.

Ten categories were initially formulated to match CWH's goals of autonomy, independence, well‐being, individualized care, communication, coordination of care, continuity of care, patient safety, and competence of physicians and nurses. Items from the CQI questionnaire database[5] were selected for each category. Ten members of a panel representing the elderly target group were invited to select the 3 most important questions in each category (first Delphi round). This panel is an important party within a regional network of care and well‐being organizations and involved in discussing the various regional care and/or well‐being projects when it concerns their content and value for elderly persons. They represent elderly persons through their position in elderly‐care or informal care organizations or from personal experiences. During a second Delphi round, they determined whether the individual items of the concept questionnaire were clearly stated, comprehensible to frail elderly patients, represent quality of care, have appropriate answer categories, and so forth. The final questionnaire was edited to match the reading level of a 12‐year‐old and approved by the panel in a face‐to‐face meeting. By this process, content validity was ensured.[6]

Data Collection

The final questionnaire was mailed to both frail and nonfrail medical and surgical inpatients who were included in the CWH before‐after study (January 2011 to July 2012) 1 week after their discharge, by a research assistant (see Supporting Information, Appendix A, in the online version of this article for a description of the study and CWH program).

Patients in the CWH study who returned the questionnaire during the postimplementation measurement period were asked to participate in the test‐retest reliability study until a predetermined sample size of 75 was reached (March 2012 to November 2012). The target interval between returning the first and second questionnaire was 2 to 14 days.[7]

In addition, patients admitted to the geriatrics departmentand therefore assumed to be frailreceived the questionnaire upon discharge (February 2012 to April 2013). The geriatrics department administered the questionnaire anonymously for evaluation and quality‐improvement purposes, as part of usual care. The secretary included the questionnaire in all patient files, and a nurse provided the questionnaire to patients together with other important discharge documents. This questionnaire also included a question regarding goal attainment, as this reflects whether what is important to the most frail elderly patients was accomplished.

Validation and Analysis

Data were analyzed using the statistical software program SPSS version 18.0 (SPSS Inc., Chicago, IL.).

Data

Characteristics of (non)responders, levels of missing data, and measurement range were assessed using descriptive statistics.

Reliability

Internal consistency was assessed by calculating Cronbach's for all available questionnaires with complete data. The answer categories were recoded to a 010 scale; 10 represents the highest quality of care. Test‐retest reliability[6] was assessed by calculating Cohen's for individual questions and intraclass correlation (ICC) for the questionnaire's mean score.

Validity

The following hypotheses were tested in order to assess construct validity: lower scores for female patients[8] and for patients who rate their health lower,[9] and with higher education[8, 9]; higher scores for patients who had an elective admission[8] and whose treatment goals were achieved (own reasoning). Finally, whether patients answered the questionnaire independently or with help should not affect scores (own reasoning). The Spearman was calculated for nonparametric and ordinal data.

In addition, we performed a Kruskal‐Wallis analysis to test the hypothesis that patients admitted to different departments have different scores. Second, we used the Mann‐Whitney U test to detect differences before and after implementation of the CWH program.

For all these analyses, only questionnaires with complete data were included.

RESULTS

Development

The selected answers within the categories communication and competence of nurses and physicians by the panel overlapped with questions from the other 8 categories; thus, the final questionnaire contains 8 core questions (Table 1) (see Supporting Information, Appendix B, in the online version of this article).

The 8 Core Questions of the CareWell in Hospital Questionnaire
Question
  • NOTE: The questionnaire for the geriatrics department included 1 additional question: Within a few days of your hospital admission, a doctor discussed the goal of the admission with you. Did you achieve your goal(s) satisfactorily? (no, not at all; yes, partially; yes, completely; don't know; doctor did not discuss my goals). See Supporting Information, Appendix A, in the online version of this article for the entire questionnaire, including the answer categories.

1. Were you informed sufficiently by your doctor regarding the various options for treating your health problems?
2. Were you able to indicate which treatment and/or care you preferred?
3. During your hospital stay, could you co‐decide what was important to your care?
4. During your hospital stay, were you supported in keeping busy and finding social contacts and activities?
5. Did you know to whom you can go within the hospital with questions, problems, or complaints?
6. Before discharge, did you talk with a member of the hospital staff regarding the care you would need after discharge?
7. Did a member of the hospital staff inform the key people and/or care providers of your discharge from the hospital?
8. During your hospital stay, did you experience 1 or more of the following events?
Did you fall?
Did you become confused?
Did you develop pressure ulcers?
Did medication errors occur?
Did you develop a urinary tract infection?
Did you develop a wound infection?
Did you experience complications with your surgery and/or treatment?

Data Collection

Figure 1 shows a flowchart of the questionnaires.

Figure 1
Flowchart of the available questionnaires returned by elderly inpatients. Abbreviations: CWH, CareWell in Hospital.

Table 2 presents data of responders compared with nonresponders who were included in the CWH study (N = 293). Patients were age 70 years and admitted 48 hours. Patients responded 14.8 11.3 days after discharge (n = 265). Response rate was 75.8%. From 18 responders no baseline characteristics were available, as only the questionnaire was collected from them to reach n = 75 for test‐retest purposes.

Characteristics of the Responding (n = 293) and Nonresponding (n = 88) Patients Included in the CareWell in Hospital Before‐After Study
No. Responders No. Nonresponders P Value
  • NOTE: Data on baseline characteristics from 18 patients in the post‐CWH measurement period are missing, and from those patients only the CareWell in Hospital questionnaires were gathered in order to reach n = 75 for test‐retest purposes. CIRS‐G ranging from 0 to 56 (with a higher score indicating more comorbidity).[14] MMSE ranging from 0 to 30 (with 30 representing the best score). Length of stay is defined as the time between admission to a CWH study department and discharge from a CWH study department. Abbreviations: CIRS‐G, Cumulative Illness Rating ScaleGeriatrics; CWH, CareWell in Hospital; MMSE, Mini‐Mental State Examination; SD, standard deviation.

Age, y SD 275 76.9 5.2 88 77.3 5.5 0.701
Male sex, n (%) 275 156 (56.7) 88 52 (59.1) 0.696
CIRS‐G, score SD 274 12.8 5.0 88 13.9 5.0 0.071
MMSE admission, score SD 264 26.7 3.7 82 25.1 4.8 0.001
MMSE discharge, score SD 230 26.9 3.7 66 25.8 4.4 0.026
Length of stay, days SD 275 8.2 7.4 88 9.6 9.7 0.322
Department, surgical (%) 275 170 (61.8) 88 56 (63.6) 0.759
Admission type, n (%) 275 88 0.343
Emergency 82 (29.8) 22 (25.0)
Elective 138 (50.2) 52 (59.1)
From other hospital or other department 55 (20.0) 14 (15.9)
Marital status, alone (%) 273 187 (68.5) 84 50 (59.5) 0.128
Discharge destination, n (%) 275 88 0.000
Home 197 (71.6) 54 (61.4)
Other hospital 69 (25.1) 20 (22.7)
Care facility 9 (3.3) 14 (15.9)
Readmission, n (%) 275 38 (13.8) 88 7 (8.0) 0.146
Readmission <1 mo, n (%) 275 28 (10.2) 88 14 (15.9) 0.144
Death <3 mo following discharge, n (%) 274 9 (3.3) 86 5 (5.8) 0.233
Received CWH intervention 149 43 (28.9) 33 15 (45.5) 0.064

Patients in the geriatrics department responded in 10.5 15.0 days (n = 111). Mean length of stay was 9.0 7.2 days (n = 116). Data regarding other baseline characteristics and response rate were unavailable due to privacy concerns.

Data Characteristics

Table 3 summarizes data of all 470 questionnaires. Response rates to the answer options ranged from 3.8% to 66.8%. Missing data among the questions ranged from 1.7% within question 8 to 7.0% within question 4. Upon combining the answer categories I don't know and missing, 7/8 questions had >10% missing data; the questions 2 and 3 had the highest percentage of missing data due to the I don't know answer option. The reasons stated by the respondents for why they could not answer these questions included cognitive disabilities; the perception that, because there was only one option (eg, in case of emergency admissions), the question did not apply to them; and/or that the patients preferred not to co‐decide because they felt that the physician knows best and can decide what is best.

Data Quality and Range and Test‐Retest Reliability of All Questionnaires Received
Data (n = 470) Test‐Retest (n = 78)
No. % No.
  • NOTE: For adverse events, the minimum amount of missing data was 1.7%. Sum scores range from 0 to 80. Mean scores range from 0 to 10. = Cohen's . Abbreviations: DK, don't know; ICC, intraclass correlation coefficient; Max, maximum; MIS, missing.

Sufficiently informed regarding treatment options 65 0.278
Not at all 23 4.9
Sometimes 90 19.1
Often 115 24.5
Every time 191 40.6
Don't know 29 6.2
Missing 21 4.7
Treatment and care preferences discussed 59 0.415
Not at all 89 18.9
Sometimes 78 16.6
Often 61 13.0
Every time 111 23.6
Don't know 103 21.9
Missing 28 6.0
Co‐decide regarding important issues 56 0.295
Not at all 75 16.0
Sometimes 86 18.3
Often 67 14.3
Every time 112 23.8
Don't know 98 20.9
Missing 32 6.8
Supported in finding (social) activities 73 0.533
Not at all 72 15.3
A little 66 14.0
Good 109 23.2
Very good 36 7.7
Not applicable 130 27.7
Don't know 24 5.1
Missing 33 7.0
Knows relevant person for questions, problems, complaints 77 0.652
Yes 279 59.4
No 107 22.8
Don't know 67 14.3
Missing 17 3.6
Discussed postdischarge care needs 75 0.574
Yes, sufficient 311 66.2
Yes, but insufficient 26 5.5
No 99 20.3
I don't know/I don't remember 18 3.8
Missing 19 4.0
Hospital informed other important people/providers of discharge 69 0.405
No 45 9.6
Some were informed 54 11.5
Yes 314 66.8
Don't know 38 8.1
Missing 19 4.0
Adverse events during hospital admission DK MIS 78 0.816
Fall, confusion, pressure ulcer, medication error, bladder infection, wound infection, complication of surgery/treatment Max 9.1% Max 4.3%
Sum Mean No. ICC
Mean score on the total questionnaire, complete cases (n = 222) 51.9 18.3 6.5 2.3 39 0.745

Reliability

Of the 470 questionnaires, 222 (47.2%) had complete data and were used to analyze internal consistency. Cronbach's for the 8‐item questionnaire was 0.70 (good internal consistency).

Seventy‐eight questionnaires were available to measure test‐retest reliability. The interval between test‐retest was 8.7 4.8 days; 94.7% was returned within the targeted 14 days. Thirty‐eight patients had complete data for both measurements: ICC on the mean score of the questionnaire was 0.75 (95% confidence interval [CI]: 0.56‐0.86), which indicates good test‐retest reliability (Table 3). Including patients with incomplete data (1 to 2 missing items) yielded an ICC >0.70. Among the individual questions, Cohen's ranged from 0.28 to 0.82.

Validity

The mean questionnaire score was significantly correlated with goals achieved while hospitalized (Table 4).

Construct Validity of the CareWell in Hospital Questionnaire Based on All Questionnaires With Complete Data on Both the Variable and the Questionnaire Score
Variable Response No.a Score SD Correlation
  • NOTE: Mean scores range from 0 to 10. Abbreviations: F, female; M, male; SD, standard deviation.

  • The number differs per analysis. Education level was not known for every patient; this variable was extracted from a different questionnaire. Admission type includes only emergency admission and elective admission; patients could also be transferred from another department or hospital, but this was not included as a category as this might include emergency as well as elective admissions. Goal of admission was only available for patients from the geriatrics department, whereas educational level and admission type were not available for patients from the geriatrics department.

  • Correlation (Spearman ) is significant at the 0.01 level (1‐tailed for goal achieved).

Sex M 114 6.3 2.3 0.080
F 108 6.7 2.3
Health status Excellent 1 0.071
Very good 5 7.9 2.0
Good 52 6.7 2.4
Fair 120 6.5 2.2
Poor 28 6.2 2.1
Education level <6 grades primary school 4 4.9 1.2 0.068
Primary school 19 6.4 2.5
Higher than primary school 6 7.6 1.2
Practical training 27 6.0 2.2
Secondary vocational training 41 6.1 2.5
Pre‐university education 2 7.2 4.0
University/higher education 20 6.8 2.2
Admission type Emergency 31 6.5 2.6 0.015
Elective 61 6.6 2.0
Goal of admission achieved Yes 33 7.6 1.7 0.319b
Partially 24 6.6 2.1
No 6 4.7 2.8
Respondent Patient only 117 6.7 2.2 0.063
Patient with help 59 5.9 2.3
Other person 41 6.7 2.4

Mean scores did not differ significantly between departments (geriatrics: 6.8 2.2, n = 88; cardiothoracic surgery and lung diseases: 6.5 2.4, n = 54; internal medicine: 6.3 2.5, n = 30; general surgery: 6.0 2.2, n = 50; P = 0.234).

In addition, mean scores did not differ significantly before (6.5 2.2, n = 53) and after (6.1 2.4, n = 67) implementation of the CWH study (P = 0.320).

DISCUSSION

The CareWell in Hospital patient questionnaire is a brief 8‐item questionnaire to assess the experiences of elderly patients regarding integrated hospital care. It showed good internal consistency and test‐retest reliability, and low responsiveness. Here we discuss some issues related to the preset criteria of the questionnaire.

First, a panel representing the elderly target population was used to develop the questionnaire in order to ensure content validity, which was confirmed by good internal consistency. Yet, with respect to individualized, integrated care for frail elderly patients, we recommend including a question regarding the involvement of informal caregivers during the hospital stay, as they are important partners in healthcare.[10]

Second, the questionnaire was kept short because it should not be a burden and feasible for frail patients to complete. Nonetheless, some of the questions had a high nonresponse rate, and many patients answered I don't know, particularly to the questions 2 and 3. It does not necessarily mean that these questions are poor in quality; it could also indicate that offering individualized care is not yet embedded in the culture of elderly patients and care professionals, such that patients consider such questions to be irrelevant.[11, 12] Nevertheless, we suggest to further explore the feasibility of the questionnaire and potential additional methods for the most frail elderly,[13] who might have been excluded from the CWH study sample at this point (Table 2).

Third, the questionnaire measures experiences rather than satisfaction. Patient‐satisfaction scores are generally tightly correlated with the age, sex, education level, health status, and the person completing the questionnaire.[8] In our study, the correlation did not reach statistical significance. Nevertheless, the achievement of preset goals was correlated significantly with mean CWH scores (Table 4). These findings may indicate that individualized care experiences can indeed be assessed better using this questionnaire. Test‐retest reliability also supports validity, as we expectedand, indeed, sawhigher reliability among the more objective questions (eg, question 8). The most valuing question is question 1, which also had the lowest reliability; the word sufficiently should perhaps be removed in the next version in order to increase its reliability and objectivity.

Finally, scores did not differ between before and after implementation of the CWH program, which suggests either that the questionnaire is unable to detect change or that the program was not sufficiently effective to invoke change yet. The latter option seems plausible, as changes in the provision of individualized care were ongoing. In addition, the items on which favorable differences can be seen for CWH are in fact the items that could be most directly influenced by the CWH interventionists, questions 4, 6, and 7 (see Supporting Information, Appendix C, in the online version of this article). Lastly, we performed an extra analysis concerning the discriminating property of the questionnaire in a subgroup of frail elderly patients; we do see a significant difference in scores between the frail patients in the geriatrics department and the frail patients who received the CWH intervention: 6.8 (n = 88) vs 4.8 (n = 13) for complete data, respectively, P = 0.013; and 6.8 (n = 155) vs 5.7 (n = 37) for incomplete data (2 items missing), P = 0.017 (Mann‐Whitney U test). This may indicate that the questionnaire can measure differences in quality of care for specifically the frail elderly patients between departments. However, these issuesincluding validity and reliability characteristics per specific patient subgroupwarrant further research using a larger sample.

CONCLUSIONS

In conclusion, the CareWell in Hospital patient questionnaire is a feasible and reliable tool for assessing experiences of frail elderly inpatients in the provision of individualized, integrated care. To improve the questionnaire, we recommend to add a question regarding the participation of informal caregivers during the hospital stay, investigate the response rate to questions regarding participation and shared decision‐making, and study responsiveness issues further.

Acknowledgements

The authors thank Gerda van Straaten, Anne Kuijpers, and Thijs Cauven for their support with data collection. We thank all members of the ZOWEL Study Group and the panel representing the elderly target group.

Disclosures: The work was made possible by grant 60‐6190‐098‐272 and grant 60‐61900‐98‐129 of the National Programme for Elderly Care, coordinated and sponsored by ZonMw, The Netherlands, Organization of Health Research and Development. The authors report no conflicts of interest.

References
  1. Kalucy L, Katterl R, Jackson‐Bowers E. Patient Experience of Health Care Performance. Adelaide, Australia: Primary Health Care Research November 2009. Available at: http://dspace.flinders.edu.au/jspui/bitstream/2328/26594/1/PIR NOV 09 Full.pdf.
  2. Bakker FC, Persoon A, Schoon Y, Rikkert MGM. Hospital Elder Life Program integrated in Dutch hospital care: a pilot study. J Am Geriatr Soc. 2013;61(4):641642.
  3. Kodner DL, Spreeuwenberg C. Integrated care: meaning, logic, applications, and implications—a discussion paper. Int J Integr Care. 2002;2:e12.
  4. Sixma H, Spreeuwenberg P, Zuidgeest M, Rademakers J. CQ‐index Ziekenhuisopname: meetinstrumentontwikkeling. Kwaliteit van de zorg tijdens ziekenhuisopnames vanuit het perspectief van patiënten. De ontwikkeling van het instrument, de psychometrische eigenschappen en het discriminerend vermogen [in Dutch]. Utrecht, The Netherlands: NIVEL (Netherlands Institute for Health Services Research), 2009.
  5. Centrum Klantervaring Zorg.CQI vragenbank (CQI questionnaire database). Available at: http://nvl002.nivel.nl/CQI. Accessed May–June 2010.
  6. Terwee CB, Bot SD, Boer MR, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol. 2007;60(1):3442.
  7. Streiner D, Norman G. Health Measurement Scales: A Practical Guide to Their Development and Use. 4th ed. Oxford, UK: Oxford University Press; 2008:182–183.
  8. Hordacre AL, Taylor A, Pirone C, Adams RJ. Assessing patient satisfaction: implications for South Australian public hospitals. Aust Health Rev. 2005;29(4):439446.
  9. Hekkert KD, Cihangir S, Kleefstra SM, Berg B, Kool RB. Patient satisfaction revisited: a multilevel approach. Soc Sci Med. 2009;69(1):6875.
  10. Wressle E, Eriksson L, Fahlander A, et al. Relatives' perspective on the quality of geriatric care and rehabilitation—development and testing of a questionnaire. Scand J Caring Sci. 2008;22(4):590595.
  11. Ekdahl AW, Andersson L, Wiréhn AB, Friedrichsen M. Are elderly people with co‐morbidities involved adequately in medical decision making when hospitalised? A cross‐sectional survey. BMC Geriatr. 2011;11:46.
  12. Wilkinson C, Khanji M, Cotter PE, Dunne O, O'Keeffe ST. Preferences of acutely ill patients for participation in medical decision‐making. Qual Saf Health Care. 2008;17(2):97100.
  13. Goldberg SE, Harwood RH. Experience of general hospital care in older patients with cognitive impairment: are we measuring the most vulnerable patients' experience? BMJ Qual Saf. 2013;doi:10.1136/bmjqs‐2013‐001961.
  14. Miller M, Towers A. A Manual of Guidelines for Scoring the Cumulative Illness Rating Scale for Geriatrics (CIRS‐G). Pittsburgh, PA: University of Pittsburgh School of Medicine, Department of Geriatric Psychiatry; 1991.
References
  1. Kalucy L, Katterl R, Jackson‐Bowers E. Patient Experience of Health Care Performance. Adelaide, Australia: Primary Health Care Research November 2009. Available at: http://dspace.flinders.edu.au/jspui/bitstream/2328/26594/1/PIR NOV 09 Full.pdf.
  2. Bakker FC, Persoon A, Schoon Y, Rikkert MGM. Hospital Elder Life Program integrated in Dutch hospital care: a pilot study. J Am Geriatr Soc. 2013;61(4):641642.
  3. Kodner DL, Spreeuwenberg C. Integrated care: meaning, logic, applications, and implications—a discussion paper. Int J Integr Care. 2002;2:e12.
  4. Sixma H, Spreeuwenberg P, Zuidgeest M, Rademakers J. CQ‐index Ziekenhuisopname: meetinstrumentontwikkeling. Kwaliteit van de zorg tijdens ziekenhuisopnames vanuit het perspectief van patiënten. De ontwikkeling van het instrument, de psychometrische eigenschappen en het discriminerend vermogen [in Dutch]. Utrecht, The Netherlands: NIVEL (Netherlands Institute for Health Services Research), 2009.
  5. Centrum Klantervaring Zorg.CQI vragenbank (CQI questionnaire database). Available at: http://nvl002.nivel.nl/CQI. Accessed May–June 2010.
  6. Terwee CB, Bot SD, Boer MR, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol. 2007;60(1):3442.
  7. Streiner D, Norman G. Health Measurement Scales: A Practical Guide to Their Development and Use. 4th ed. Oxford, UK: Oxford University Press; 2008:182–183.
  8. Hordacre AL, Taylor A, Pirone C, Adams RJ. Assessing patient satisfaction: implications for South Australian public hospitals. Aust Health Rev. 2005;29(4):439446.
  9. Hekkert KD, Cihangir S, Kleefstra SM, Berg B, Kool RB. Patient satisfaction revisited: a multilevel approach. Soc Sci Med. 2009;69(1):6875.
  10. Wressle E, Eriksson L, Fahlander A, et al. Relatives' perspective on the quality of geriatric care and rehabilitation—development and testing of a questionnaire. Scand J Caring Sci. 2008;22(4):590595.
  11. Ekdahl AW, Andersson L, Wiréhn AB, Friedrichsen M. Are elderly people with co‐morbidities involved adequately in medical decision making when hospitalised? A cross‐sectional survey. BMC Geriatr. 2011;11:46.
  12. Wilkinson C, Khanji M, Cotter PE, Dunne O, O'Keeffe ST. Preferences of acutely ill patients for participation in medical decision‐making. Qual Saf Health Care. 2008;17(2):97100.
  13. Goldberg SE, Harwood RH. Experience of general hospital care in older patients with cognitive impairment: are we measuring the most vulnerable patients' experience? BMJ Qual Saf. 2013;doi:10.1136/bmjqs‐2013‐001961.
  14. Miller M, Towers A. A Manual of Guidelines for Scoring the Cumulative Illness Rating Scale for Geriatrics (CIRS‐G). Pittsburgh, PA: University of Pittsburgh School of Medicine, Department of Geriatric Psychiatry; 1991.
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Journal of Hospital Medicine - 9(5)
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Address for correspondence and reprint requests: Franka Bakker, MSc, Department of Geriatric Medicine 925, Radboud University Medical Center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands; Telephone: +31 24 3616772; Fax: +31 24 3617408; E‐mail: [email protected]
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Cooling the resuscitated sudden dead

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Cooling the resuscitated sudden dead

In the last 30 years, there have been immense advances in the treatment and prevention of sudden cardiac arrest, including beta-blocker therapy and automatic implantable cardiac defibrillators.

In addition, communities have organized emergency medical systems (EMS) designed to provide early cardiac care for the prevention and treatment of cardiac arrest occurring outside the hospital (OHCA). One of the great frustrations of physicians working in the EMS environment is the successful cardiac resuscitation for the patient who is left with severe neurological impairment or brain death. It is clear that resuscitation of the brain is very time dependent. Complete interruption of blood flow to the brain leads to the loss of consciousness within seconds and death of vulnerable neurons in several brain regions occurs within minutes, whereas 20-40 minutes of ischemia is required to kill cardiac myocytes.

To improve survival and prevent the neurological sequelae of OHCA, total body hypothermia is advised based on animal laboratory experiments and a few small clinical studies carried out in a total of 179 OHCA patients (N. Engl. J. Med. 2002;346:557-63 and 549-56).

Both studies show both a neurological and survival benefit – particularly in patients resuscitated from ventricular fibrillation – in comatose patients in whom resuscitation was achieved within 5-10 minutes after witnessed cardiac arrest when cooled to 32-34 degrees Celsius within 60 minutes of collapse. These studies led to the recommendation by the International Liaison Committee on Resuscitation (Circulation 2004;110;3385-97) that cooling to 32-34 degrees Celsius for 12-24 hours should be used in unconscious patients with OHCA with VF and possibly non-VF arrests.

These recommendations were supported by the AHA Guideline Committee (Circulation 2010;122:S768-86) As a result, cooling comatose OHCA patients after resuscitation is widely used in emergency departments in the United States and Europe with the use of a variety of devices and techniques including large volume saline, external cooling devices, intravenous catheter devices, and intranasal devices. When hypothermia was initially recommended, a number of questions were unanswered and remain unanswered despite multiple publications and wide clinical experience in the succeeding 12 years. Some of those questions include the timing, duration, and intensity of cooling, the preferable technique of cooling, and risk and benefits of the different cooling techniques.

In the United States, pressure infusion of 2 liters of ice cold saline is the usual initial method of cooling to 32-34 degrees Celsius followed by 12-36 hours with surface cooling.

Investigators in Seattle randomized OHCA patients prior to hypothermia or standard therapy with both VF and non-VF rhythms before hospitalization to improve the previous reported benefit when initiated in hospital (JAMA 2014;311;45-52).

The initiation of prehospital therapy achieved cooling 1 hour earlier than in previous hospitalization studies. The result in 1,359 OHCAs over a 5-year period raises important questions about the benefit of hypothermia. The researchers failed to find any benefit in regard to neurological outcomes or mortality. In VF OHCA, they observed a survival rate to hospital discharge of 62.7 % (intervention group) and 64.3% (controls). In the patients without VF, those rates were 19.2 and 16.3, respectively.

Neurological outcomes were also similar for patients with VF at 57.5% (intervention group) and 61.9% (controls), respectively. The non-VF rates were 14.4% (intervention) and 13.4 % (controls). Hypothermia was associated with significant adverse events, including pulmonary edema and increased use of diuretics.

These observations are contrary to previous observations and should provide an opportunity to reevaluate hypothermia for OHCA. These patients represent a series of complex metabolic issues that deserve careful research to provide answers to some of the outstanding issues. The recent studies provide an environment of equipoise where we can step back and revaluate this complex procedure in randomized control trials.

Dr. Goldstein, medical editor of Cardiology News, is professor of medicine at Wayne State University and division head emeritus of cardiovascular medicine at Henry Ford Hospital, both in Detroit. He is on data safety monitoring committees for the National Institutes of Health and several pharmaceutical companies.

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In the last 30 years, there have been immense advances in the treatment and prevention of sudden cardiac arrest, including beta-blocker therapy and automatic implantable cardiac defibrillators.

In addition, communities have organized emergency medical systems (EMS) designed to provide early cardiac care for the prevention and treatment of cardiac arrest occurring outside the hospital (OHCA). One of the great frustrations of physicians working in the EMS environment is the successful cardiac resuscitation for the patient who is left with severe neurological impairment or brain death. It is clear that resuscitation of the brain is very time dependent. Complete interruption of blood flow to the brain leads to the loss of consciousness within seconds and death of vulnerable neurons in several brain regions occurs within minutes, whereas 20-40 minutes of ischemia is required to kill cardiac myocytes.

To improve survival and prevent the neurological sequelae of OHCA, total body hypothermia is advised based on animal laboratory experiments and a few small clinical studies carried out in a total of 179 OHCA patients (N. Engl. J. Med. 2002;346:557-63 and 549-56).

Both studies show both a neurological and survival benefit – particularly in patients resuscitated from ventricular fibrillation – in comatose patients in whom resuscitation was achieved within 5-10 minutes after witnessed cardiac arrest when cooled to 32-34 degrees Celsius within 60 minutes of collapse. These studies led to the recommendation by the International Liaison Committee on Resuscitation (Circulation 2004;110;3385-97) that cooling to 32-34 degrees Celsius for 12-24 hours should be used in unconscious patients with OHCA with VF and possibly non-VF arrests.

These recommendations were supported by the AHA Guideline Committee (Circulation 2010;122:S768-86) As a result, cooling comatose OHCA patients after resuscitation is widely used in emergency departments in the United States and Europe with the use of a variety of devices and techniques including large volume saline, external cooling devices, intravenous catheter devices, and intranasal devices. When hypothermia was initially recommended, a number of questions were unanswered and remain unanswered despite multiple publications and wide clinical experience in the succeeding 12 years. Some of those questions include the timing, duration, and intensity of cooling, the preferable technique of cooling, and risk and benefits of the different cooling techniques.

In the United States, pressure infusion of 2 liters of ice cold saline is the usual initial method of cooling to 32-34 degrees Celsius followed by 12-36 hours with surface cooling.

Investigators in Seattle randomized OHCA patients prior to hypothermia or standard therapy with both VF and non-VF rhythms before hospitalization to improve the previous reported benefit when initiated in hospital (JAMA 2014;311;45-52).

The initiation of prehospital therapy achieved cooling 1 hour earlier than in previous hospitalization studies. The result in 1,359 OHCAs over a 5-year period raises important questions about the benefit of hypothermia. The researchers failed to find any benefit in regard to neurological outcomes or mortality. In VF OHCA, they observed a survival rate to hospital discharge of 62.7 % (intervention group) and 64.3% (controls). In the patients without VF, those rates were 19.2 and 16.3, respectively.

Neurological outcomes were also similar for patients with VF at 57.5% (intervention group) and 61.9% (controls), respectively. The non-VF rates were 14.4% (intervention) and 13.4 % (controls). Hypothermia was associated with significant adverse events, including pulmonary edema and increased use of diuretics.

These observations are contrary to previous observations and should provide an opportunity to reevaluate hypothermia for OHCA. These patients represent a series of complex metabolic issues that deserve careful research to provide answers to some of the outstanding issues. The recent studies provide an environment of equipoise where we can step back and revaluate this complex procedure in randomized control trials.

Dr. Goldstein, medical editor of Cardiology News, is professor of medicine at Wayne State University and division head emeritus of cardiovascular medicine at Henry Ford Hospital, both in Detroit. He is on data safety monitoring committees for the National Institutes of Health and several pharmaceutical companies.

In the last 30 years, there have been immense advances in the treatment and prevention of sudden cardiac arrest, including beta-blocker therapy and automatic implantable cardiac defibrillators.

In addition, communities have organized emergency medical systems (EMS) designed to provide early cardiac care for the prevention and treatment of cardiac arrest occurring outside the hospital (OHCA). One of the great frustrations of physicians working in the EMS environment is the successful cardiac resuscitation for the patient who is left with severe neurological impairment or brain death. It is clear that resuscitation of the brain is very time dependent. Complete interruption of blood flow to the brain leads to the loss of consciousness within seconds and death of vulnerable neurons in several brain regions occurs within minutes, whereas 20-40 minutes of ischemia is required to kill cardiac myocytes.

To improve survival and prevent the neurological sequelae of OHCA, total body hypothermia is advised based on animal laboratory experiments and a few small clinical studies carried out in a total of 179 OHCA patients (N. Engl. J. Med. 2002;346:557-63 and 549-56).

Both studies show both a neurological and survival benefit – particularly in patients resuscitated from ventricular fibrillation – in comatose patients in whom resuscitation was achieved within 5-10 minutes after witnessed cardiac arrest when cooled to 32-34 degrees Celsius within 60 minutes of collapse. These studies led to the recommendation by the International Liaison Committee on Resuscitation (Circulation 2004;110;3385-97) that cooling to 32-34 degrees Celsius for 12-24 hours should be used in unconscious patients with OHCA with VF and possibly non-VF arrests.

These recommendations were supported by the AHA Guideline Committee (Circulation 2010;122:S768-86) As a result, cooling comatose OHCA patients after resuscitation is widely used in emergency departments in the United States and Europe with the use of a variety of devices and techniques including large volume saline, external cooling devices, intravenous catheter devices, and intranasal devices. When hypothermia was initially recommended, a number of questions were unanswered and remain unanswered despite multiple publications and wide clinical experience in the succeeding 12 years. Some of those questions include the timing, duration, and intensity of cooling, the preferable technique of cooling, and risk and benefits of the different cooling techniques.

In the United States, pressure infusion of 2 liters of ice cold saline is the usual initial method of cooling to 32-34 degrees Celsius followed by 12-36 hours with surface cooling.

Investigators in Seattle randomized OHCA patients prior to hypothermia or standard therapy with both VF and non-VF rhythms before hospitalization to improve the previous reported benefit when initiated in hospital (JAMA 2014;311;45-52).

The initiation of prehospital therapy achieved cooling 1 hour earlier than in previous hospitalization studies. The result in 1,359 OHCAs over a 5-year period raises important questions about the benefit of hypothermia. The researchers failed to find any benefit in regard to neurological outcomes or mortality. In VF OHCA, they observed a survival rate to hospital discharge of 62.7 % (intervention group) and 64.3% (controls). In the patients without VF, those rates were 19.2 and 16.3, respectively.

Neurological outcomes were also similar for patients with VF at 57.5% (intervention group) and 61.9% (controls), respectively. The non-VF rates were 14.4% (intervention) and 13.4 % (controls). Hypothermia was associated with significant adverse events, including pulmonary edema and increased use of diuretics.

These observations are contrary to previous observations and should provide an opportunity to reevaluate hypothermia for OHCA. These patients represent a series of complex metabolic issues that deserve careful research to provide answers to some of the outstanding issues. The recent studies provide an environment of equipoise where we can step back and revaluate this complex procedure in randomized control trials.

Dr. Goldstein, medical editor of Cardiology News, is professor of medicine at Wayne State University and division head emeritus of cardiovascular medicine at Henry Ford Hospital, both in Detroit. He is on data safety monitoring committees for the National Institutes of Health and several pharmaceutical companies.

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Former JNC 8 hypertension panel issues minority report

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Former JNC 8 hypertension panel issues minority report

The controversial hypertension-management guidelines released by the former JNC 8 panel in December was not the group’s last word. There was a minority report, too, published almost a month later in mid-January.

Five of the 17 members of the group originally assembled in 2008 by the National Heart, Lung, and Blood Institute (NHLBI) to research and write the eighth edition of the official U.S. hypertension guidelines not only disagreed with their 12 colleagues about resetting the systolic blood pressure target to 150 mm Hg from the prior target of 140 mm Hg for people aged 60-79 without diabetes or chronic kidney disease, but also felt strongly enough to write an article about it.

Courtesy Michael V. Hayes, Wikimedia Commons
The controversial hypertension-management guidelines released by the former JNC 8 panel in December was not the group's last word. There was a minority report, too, published almost a month later in mid-January.

A published minority report is not how most medical guideline writing panels usually work.

The history of the Eighth Joint National Committee (JNC 8) already featured some unusual twists. After many months of unexpected delays leading up to the report’s release, the NHLBI announced last June that it would hand off the JNC 8 process to an appropriate medical group. A few weeks later, the institute announced that JNC 8 would get published under the auspices of the American Heart Association and American College of Cardiology. Then came word that the arrangement had fallen through, leaving what became the former JNC 8 panel to release its data analysis and recommendations without endorsement from a medical association.

The fact that the 150–mm Hg systolic target for treating 60- to 79-year-olds was controversial among the panel members themselves was no surprise. The former JNC 8 panel’s majority report in December acknowledged their lack of consensus on this issue. What had been previously unknown was exactly how the panel split, and the minority view that led to the disagreement.

The five dissenters were Dr. Jackson T. Wright Jr., Case Medical Center, Cleveland; Dr. Lawrence J. Fine, NHLBI, Bethesda, Md.; Daniel T. Lackland, Ph.D., Medical University of South Carolina, Charleston; Dr. Gbenga Ogedegbe, New York University; and Cheryl R. Dennison Himmelfarb, Ph.D., Johns Hopkins University, Baltimore.

Summarizing their view in their report, the five said they "believed that evidence was insufficient to increase the SBP goal from its current level of less than 140 mm Hg because of concern that increasing the goal may cause harm by increasing the risk for CVD and partially undoing the remarkable progress in reducing cardiovascular mortality in Americans older than 60 years. Because of the overall evidence, including the RCT data reviewed by the panel, and the decrease in CVD mortality, we concluded that the evidence for increasing a blood pressure target in high-risk populations should be at least as strong as the evidence required to decrease the recommended blood pressure target. In addition, one target would simplify implementation for clinicians."

The unusual circumstances that surrounded release of the former JNC 8 panel’s report and the controversial systolic target they set initially raised questions about the impact the recommendations would have on U.S. practice. The minority report puts an asterisk on the majority report and dilutes its influence even more.

[email protected]

On Twitter @mitchelzoler

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The controversial hypertension-management guidelines released by the former JNC 8 panel in December was not the group’s last word. There was a minority report, too, published almost a month later in mid-January.

Five of the 17 members of the group originally assembled in 2008 by the National Heart, Lung, and Blood Institute (NHLBI) to research and write the eighth edition of the official U.S. hypertension guidelines not only disagreed with their 12 colleagues about resetting the systolic blood pressure target to 150 mm Hg from the prior target of 140 mm Hg for people aged 60-79 without diabetes or chronic kidney disease, but also felt strongly enough to write an article about it.

Courtesy Michael V. Hayes, Wikimedia Commons
The controversial hypertension-management guidelines released by the former JNC 8 panel in December was not the group's last word. There was a minority report, too, published almost a month later in mid-January.

A published minority report is not how most medical guideline writing panels usually work.

The history of the Eighth Joint National Committee (JNC 8) already featured some unusual twists. After many months of unexpected delays leading up to the report’s release, the NHLBI announced last June that it would hand off the JNC 8 process to an appropriate medical group. A few weeks later, the institute announced that JNC 8 would get published under the auspices of the American Heart Association and American College of Cardiology. Then came word that the arrangement had fallen through, leaving what became the former JNC 8 panel to release its data analysis and recommendations without endorsement from a medical association.

The fact that the 150–mm Hg systolic target for treating 60- to 79-year-olds was controversial among the panel members themselves was no surprise. The former JNC 8 panel’s majority report in December acknowledged their lack of consensus on this issue. What had been previously unknown was exactly how the panel split, and the minority view that led to the disagreement.

The five dissenters were Dr. Jackson T. Wright Jr., Case Medical Center, Cleveland; Dr. Lawrence J. Fine, NHLBI, Bethesda, Md.; Daniel T. Lackland, Ph.D., Medical University of South Carolina, Charleston; Dr. Gbenga Ogedegbe, New York University; and Cheryl R. Dennison Himmelfarb, Ph.D., Johns Hopkins University, Baltimore.

Summarizing their view in their report, the five said they "believed that evidence was insufficient to increase the SBP goal from its current level of less than 140 mm Hg because of concern that increasing the goal may cause harm by increasing the risk for CVD and partially undoing the remarkable progress in reducing cardiovascular mortality in Americans older than 60 years. Because of the overall evidence, including the RCT data reviewed by the panel, and the decrease in CVD mortality, we concluded that the evidence for increasing a blood pressure target in high-risk populations should be at least as strong as the evidence required to decrease the recommended blood pressure target. In addition, one target would simplify implementation for clinicians."

The unusual circumstances that surrounded release of the former JNC 8 panel’s report and the controversial systolic target they set initially raised questions about the impact the recommendations would have on U.S. practice. The minority report puts an asterisk on the majority report and dilutes its influence even more.

[email protected]

On Twitter @mitchelzoler

The controversial hypertension-management guidelines released by the former JNC 8 panel in December was not the group’s last word. There was a minority report, too, published almost a month later in mid-January.

Five of the 17 members of the group originally assembled in 2008 by the National Heart, Lung, and Blood Institute (NHLBI) to research and write the eighth edition of the official U.S. hypertension guidelines not only disagreed with their 12 colleagues about resetting the systolic blood pressure target to 150 mm Hg from the prior target of 140 mm Hg for people aged 60-79 without diabetes or chronic kidney disease, but also felt strongly enough to write an article about it.

Courtesy Michael V. Hayes, Wikimedia Commons
The controversial hypertension-management guidelines released by the former JNC 8 panel in December was not the group's last word. There was a minority report, too, published almost a month later in mid-January.

A published minority report is not how most medical guideline writing panels usually work.

The history of the Eighth Joint National Committee (JNC 8) already featured some unusual twists. After many months of unexpected delays leading up to the report’s release, the NHLBI announced last June that it would hand off the JNC 8 process to an appropriate medical group. A few weeks later, the institute announced that JNC 8 would get published under the auspices of the American Heart Association and American College of Cardiology. Then came word that the arrangement had fallen through, leaving what became the former JNC 8 panel to release its data analysis and recommendations without endorsement from a medical association.

The fact that the 150–mm Hg systolic target for treating 60- to 79-year-olds was controversial among the panel members themselves was no surprise. The former JNC 8 panel’s majority report in December acknowledged their lack of consensus on this issue. What had been previously unknown was exactly how the panel split, and the minority view that led to the disagreement.

The five dissenters were Dr. Jackson T. Wright Jr., Case Medical Center, Cleveland; Dr. Lawrence J. Fine, NHLBI, Bethesda, Md.; Daniel T. Lackland, Ph.D., Medical University of South Carolina, Charleston; Dr. Gbenga Ogedegbe, New York University; and Cheryl R. Dennison Himmelfarb, Ph.D., Johns Hopkins University, Baltimore.

Summarizing their view in their report, the five said they "believed that evidence was insufficient to increase the SBP goal from its current level of less than 140 mm Hg because of concern that increasing the goal may cause harm by increasing the risk for CVD and partially undoing the remarkable progress in reducing cardiovascular mortality in Americans older than 60 years. Because of the overall evidence, including the RCT data reviewed by the panel, and the decrease in CVD mortality, we concluded that the evidence for increasing a blood pressure target in high-risk populations should be at least as strong as the evidence required to decrease the recommended blood pressure target. In addition, one target would simplify implementation for clinicians."

The unusual circumstances that surrounded release of the former JNC 8 panel’s report and the controversial systolic target they set initially raised questions about the impact the recommendations would have on U.S. practice. The minority report puts an asterisk on the majority report and dilutes its influence even more.

[email protected]

On Twitter @mitchelzoler

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A new prognostic model for PTCL?

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SAN FRANCISCO—Unlike its predecessors, a new prognostic model suggests race and histology are important predictors of outcome in patients with peripheral T-cell lymphoma (PTCL).

Researchers analyzed nearly 9000 patients diagnosed with PTCL in the US and found evidence to suggest that patient age and race, as well as histology and disease stage can be used to predict overall survival (OS).

The group’s findings also suggested the use of radiation is associated with improved OS. And later diagnosis may be associated with favorable outcome.

Adam M. Petrich, MD, of Northwestern University in Chicago, presented this research at the 6th Annual T-cell Lymphoma Forum, which took place January 23-25. Dr Petrich was 1 of 2 speakers to receive a Young Investigator Award for his presentation.

Dr Petrich noted that at least 5 models have been used to predict outcomes in patients with newly diagnosed PTCL—the International Prognostic Index (IPI), the Prognostic Index for PTCL (PIT), the International PTCL Project model (IPTCLP), the modified Prognostic Index for T-cell Lymphoma (mPIT), and the Extranodal Natural Killer/T Cell Lymphoma (ENKTL) model.

But these models have limitations, including small patient numbers and issues with applicability. So Dr Petrich and his colleagues wanted to take a closer look at prognostic factors in PTCL, to determine which factors from previously published models remain relevant.

Patient characteristics

The researchers used data from the SEER database, which included 20 state and local registries and captured 28% of the US population. There were 8802 cases of PTCL diagnosed between 2000 and 2010.

Patients ranged in age from 20 to 85 years, and 59% were male. With regard to race, 77% of patients were white, 13% were black, 9% were classified as “other,” and 1% were of unknown race.

Forty-eight percent of patients had stage I-II disease, 31% had stage III-IV, and the stage was unknown for 21% of patients. Extranodal disease was absent in 60% of patients, present in 26%, and unknown in 14%.

Histologies were as follows:

  • 38.1% of patients had PTCL-not otherwise specified (PTCL-NOS)
  • 24.2% had anaplastic large-cell lymphoma (ALCL)
  • 12.7% had angioimmunoblastic T-cell lymphoma (AITL)
  • 9.3% had adult T-cell leukemia/lymphoma (ATLL)
  • 6.9% had extranodal NK/T-cell lymphoma (ENKTL)
  • 3.2% had T-cell-prolymphocytic leukemia(T-PLL)
  • 2.5% had T-cell large granular lymphocytic leukemia (T-LGL)
  • 1.2% had subcutaneous panniculitis-like T-cell lymphoma (SCPTCL)
  • 1.1% had enteropathy-associated T-cell lymphoma (EATL)
  • 0.6% had hepatosplenic T-cell lymphoma (HSTL).

Prognostic factors revealed

The researchers performed univariate and multivariate analyses to determine the importance of the aforementioned factors on OS.

“We decided, since we have a large number of patients, to use a very stringent P value,” Dr Petrich said. “Only those that are less than 0.0001 were considered significant.”

In univariate analysis, age, race, disease stage, extranodal disease, use of radiation, and histology all significantly impacted OS. But in multivariate analysis, only race, age, histology, and disease stage retained significance.

“Extranodal disease is associated with protection from overall survival, but that P value did not reach significance (P=0.009),” Dr Petrich said.

Likewise, patients diagnosed from 2009 to 2010 had better OS than patients diagnosed from 2000 to 2008, but this did not meet the significance criterion (P=0.0002).

On the other hand, OS was significantly worse for black patients compared to white patients. And compared to patients aged 20-24, those 55 years of age and older had a significantly increased risk of death.

Compared to patients with PTCL-NOS, those with EATL, ENKTL, and T-LGL all had significantly worse OS. And patients with advanced-stage disease had significantly worse OS.

The researchers also looked at the use of radiation and found that it had a significant impact on survival.

 

 

“Of course, this isn’t a pre-treatment variable, but we did add it as sort of an exploratory analysis,” Dr Petrich said. “And regardless of disease stage, [radiation] seems to be associated with improved survival. But when we include it in a multivariate analysis, it’s also highly associated with protection from 5-year mortality (P<0.0001).”

Creating, validating the prognostic model

Dr Petrich and his colleagues created a prognostic model based on some of the aforementioned factors. They assigned points according to hazard ratios (HRs).

Patients received 1 point for each of the following factors: age 55 or older (HR 1.51), black race (HR 1.43), distant-stage disease (HR 1.79), PTCL-NOS (reference), AITL (HR 1.19), ALCL (HR 0.88), and ATLL (HR 1.34).

Patients received 2 points for each of the following histologies: HSTL (HR 1.76), EATL (HR 2.32), ENKTL (HR 1.50), and T-PLL (HR couldn’t be calculated). And they received 0 points for SCPTL (HR 0.71) and T-LGL (HR 0.43).

The researchers then applied the model to the population of 8802 patients and evaluated survival. The median OS was more than 120 months for patients with a score of 0-1, 36 months for those with a score of 2, 14 months for those with a score of 3, and 9 months for those with score of 4 or 5.

“We have good discrimination of outcome based on this scoring system, with patients with the most favorable prognosis having median survival that’s out over 10 years,” Dr Petrich said.

The researchers also obtained good discrimination when they tested the model in a validation cohort of 112 patients, Dr Petrich said. He noted, however, that validating the model with a larger patient population would provide better results.

He also pointed out that this study had its limitations, such as missing data and a lack of uniformity with regard to treatment. But the research does reveal factors that are likely important prognostic indicators in PTCL.

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SAN FRANCISCO—Unlike its predecessors, a new prognostic model suggests race and histology are important predictors of outcome in patients with peripheral T-cell lymphoma (PTCL).

Researchers analyzed nearly 9000 patients diagnosed with PTCL in the US and found evidence to suggest that patient age and race, as well as histology and disease stage can be used to predict overall survival (OS).

The group’s findings also suggested the use of radiation is associated with improved OS. And later diagnosis may be associated with favorable outcome.

Adam M. Petrich, MD, of Northwestern University in Chicago, presented this research at the 6th Annual T-cell Lymphoma Forum, which took place January 23-25. Dr Petrich was 1 of 2 speakers to receive a Young Investigator Award for his presentation.

Dr Petrich noted that at least 5 models have been used to predict outcomes in patients with newly diagnosed PTCL—the International Prognostic Index (IPI), the Prognostic Index for PTCL (PIT), the International PTCL Project model (IPTCLP), the modified Prognostic Index for T-cell Lymphoma (mPIT), and the Extranodal Natural Killer/T Cell Lymphoma (ENKTL) model.

But these models have limitations, including small patient numbers and issues with applicability. So Dr Petrich and his colleagues wanted to take a closer look at prognostic factors in PTCL, to determine which factors from previously published models remain relevant.

Patient characteristics

The researchers used data from the SEER database, which included 20 state and local registries and captured 28% of the US population. There were 8802 cases of PTCL diagnosed between 2000 and 2010.

Patients ranged in age from 20 to 85 years, and 59% were male. With regard to race, 77% of patients were white, 13% were black, 9% were classified as “other,” and 1% were of unknown race.

Forty-eight percent of patients had stage I-II disease, 31% had stage III-IV, and the stage was unknown for 21% of patients. Extranodal disease was absent in 60% of patients, present in 26%, and unknown in 14%.

Histologies were as follows:

  • 38.1% of patients had PTCL-not otherwise specified (PTCL-NOS)
  • 24.2% had anaplastic large-cell lymphoma (ALCL)
  • 12.7% had angioimmunoblastic T-cell lymphoma (AITL)
  • 9.3% had adult T-cell leukemia/lymphoma (ATLL)
  • 6.9% had extranodal NK/T-cell lymphoma (ENKTL)
  • 3.2% had T-cell-prolymphocytic leukemia(T-PLL)
  • 2.5% had T-cell large granular lymphocytic leukemia (T-LGL)
  • 1.2% had subcutaneous panniculitis-like T-cell lymphoma (SCPTCL)
  • 1.1% had enteropathy-associated T-cell lymphoma (EATL)
  • 0.6% had hepatosplenic T-cell lymphoma (HSTL).

Prognostic factors revealed

The researchers performed univariate and multivariate analyses to determine the importance of the aforementioned factors on OS.

“We decided, since we have a large number of patients, to use a very stringent P value,” Dr Petrich said. “Only those that are less than 0.0001 were considered significant.”

In univariate analysis, age, race, disease stage, extranodal disease, use of radiation, and histology all significantly impacted OS. But in multivariate analysis, only race, age, histology, and disease stage retained significance.

“Extranodal disease is associated with protection from overall survival, but that P value did not reach significance (P=0.009),” Dr Petrich said.

Likewise, patients diagnosed from 2009 to 2010 had better OS than patients diagnosed from 2000 to 2008, but this did not meet the significance criterion (P=0.0002).

On the other hand, OS was significantly worse for black patients compared to white patients. And compared to patients aged 20-24, those 55 years of age and older had a significantly increased risk of death.

Compared to patients with PTCL-NOS, those with EATL, ENKTL, and T-LGL all had significantly worse OS. And patients with advanced-stage disease had significantly worse OS.

The researchers also looked at the use of radiation and found that it had a significant impact on survival.

 

 

“Of course, this isn’t a pre-treatment variable, but we did add it as sort of an exploratory analysis,” Dr Petrich said. “And regardless of disease stage, [radiation] seems to be associated with improved survival. But when we include it in a multivariate analysis, it’s also highly associated with protection from 5-year mortality (P<0.0001).”

Creating, validating the prognostic model

Dr Petrich and his colleagues created a prognostic model based on some of the aforementioned factors. They assigned points according to hazard ratios (HRs).

Patients received 1 point for each of the following factors: age 55 or older (HR 1.51), black race (HR 1.43), distant-stage disease (HR 1.79), PTCL-NOS (reference), AITL (HR 1.19), ALCL (HR 0.88), and ATLL (HR 1.34).

Patients received 2 points for each of the following histologies: HSTL (HR 1.76), EATL (HR 2.32), ENKTL (HR 1.50), and T-PLL (HR couldn’t be calculated). And they received 0 points for SCPTL (HR 0.71) and T-LGL (HR 0.43).

The researchers then applied the model to the population of 8802 patients and evaluated survival. The median OS was more than 120 months for patients with a score of 0-1, 36 months for those with a score of 2, 14 months for those with a score of 3, and 9 months for those with score of 4 or 5.

“We have good discrimination of outcome based on this scoring system, with patients with the most favorable prognosis having median survival that’s out over 10 years,” Dr Petrich said.

The researchers also obtained good discrimination when they tested the model in a validation cohort of 112 patients, Dr Petrich said. He noted, however, that validating the model with a larger patient population would provide better results.

He also pointed out that this study had its limitations, such as missing data and a lack of uniformity with regard to treatment. But the research does reveal factors that are likely important prognostic indicators in PTCL.

SAN FRANCISCO—Unlike its predecessors, a new prognostic model suggests race and histology are important predictors of outcome in patients with peripheral T-cell lymphoma (PTCL).

Researchers analyzed nearly 9000 patients diagnosed with PTCL in the US and found evidence to suggest that patient age and race, as well as histology and disease stage can be used to predict overall survival (OS).

The group’s findings also suggested the use of radiation is associated with improved OS. And later diagnosis may be associated with favorable outcome.

Adam M. Petrich, MD, of Northwestern University in Chicago, presented this research at the 6th Annual T-cell Lymphoma Forum, which took place January 23-25. Dr Petrich was 1 of 2 speakers to receive a Young Investigator Award for his presentation.

Dr Petrich noted that at least 5 models have been used to predict outcomes in patients with newly diagnosed PTCL—the International Prognostic Index (IPI), the Prognostic Index for PTCL (PIT), the International PTCL Project model (IPTCLP), the modified Prognostic Index for T-cell Lymphoma (mPIT), and the Extranodal Natural Killer/T Cell Lymphoma (ENKTL) model.

But these models have limitations, including small patient numbers and issues with applicability. So Dr Petrich and his colleagues wanted to take a closer look at prognostic factors in PTCL, to determine which factors from previously published models remain relevant.

Patient characteristics

The researchers used data from the SEER database, which included 20 state and local registries and captured 28% of the US population. There were 8802 cases of PTCL diagnosed between 2000 and 2010.

Patients ranged in age from 20 to 85 years, and 59% were male. With regard to race, 77% of patients were white, 13% were black, 9% were classified as “other,” and 1% were of unknown race.

Forty-eight percent of patients had stage I-II disease, 31% had stage III-IV, and the stage was unknown for 21% of patients. Extranodal disease was absent in 60% of patients, present in 26%, and unknown in 14%.

Histologies were as follows:

  • 38.1% of patients had PTCL-not otherwise specified (PTCL-NOS)
  • 24.2% had anaplastic large-cell lymphoma (ALCL)
  • 12.7% had angioimmunoblastic T-cell lymphoma (AITL)
  • 9.3% had adult T-cell leukemia/lymphoma (ATLL)
  • 6.9% had extranodal NK/T-cell lymphoma (ENKTL)
  • 3.2% had T-cell-prolymphocytic leukemia(T-PLL)
  • 2.5% had T-cell large granular lymphocytic leukemia (T-LGL)
  • 1.2% had subcutaneous panniculitis-like T-cell lymphoma (SCPTCL)
  • 1.1% had enteropathy-associated T-cell lymphoma (EATL)
  • 0.6% had hepatosplenic T-cell lymphoma (HSTL).

Prognostic factors revealed

The researchers performed univariate and multivariate analyses to determine the importance of the aforementioned factors on OS.

“We decided, since we have a large number of patients, to use a very stringent P value,” Dr Petrich said. “Only those that are less than 0.0001 were considered significant.”

In univariate analysis, age, race, disease stage, extranodal disease, use of radiation, and histology all significantly impacted OS. But in multivariate analysis, only race, age, histology, and disease stage retained significance.

“Extranodal disease is associated with protection from overall survival, but that P value did not reach significance (P=0.009),” Dr Petrich said.

Likewise, patients diagnosed from 2009 to 2010 had better OS than patients diagnosed from 2000 to 2008, but this did not meet the significance criterion (P=0.0002).

On the other hand, OS was significantly worse for black patients compared to white patients. And compared to patients aged 20-24, those 55 years of age and older had a significantly increased risk of death.

Compared to patients with PTCL-NOS, those with EATL, ENKTL, and T-LGL all had significantly worse OS. And patients with advanced-stage disease had significantly worse OS.

The researchers also looked at the use of radiation and found that it had a significant impact on survival.

 

 

“Of course, this isn’t a pre-treatment variable, but we did add it as sort of an exploratory analysis,” Dr Petrich said. “And regardless of disease stage, [radiation] seems to be associated with improved survival. But when we include it in a multivariate analysis, it’s also highly associated with protection from 5-year mortality (P<0.0001).”

Creating, validating the prognostic model

Dr Petrich and his colleagues created a prognostic model based on some of the aforementioned factors. They assigned points according to hazard ratios (HRs).

Patients received 1 point for each of the following factors: age 55 or older (HR 1.51), black race (HR 1.43), distant-stage disease (HR 1.79), PTCL-NOS (reference), AITL (HR 1.19), ALCL (HR 0.88), and ATLL (HR 1.34).

Patients received 2 points for each of the following histologies: HSTL (HR 1.76), EATL (HR 2.32), ENKTL (HR 1.50), and T-PLL (HR couldn’t be calculated). And they received 0 points for SCPTL (HR 0.71) and T-LGL (HR 0.43).

The researchers then applied the model to the population of 8802 patients and evaluated survival. The median OS was more than 120 months for patients with a score of 0-1, 36 months for those with a score of 2, 14 months for those with a score of 3, and 9 months for those with score of 4 or 5.

“We have good discrimination of outcome based on this scoring system, with patients with the most favorable prognosis having median survival that’s out over 10 years,” Dr Petrich said.

The researchers also obtained good discrimination when they tested the model in a validation cohort of 112 patients, Dr Petrich said. He noted, however, that validating the model with a larger patient population would provide better results.

He also pointed out that this study had its limitations, such as missing data and a lack of uniformity with regard to treatment. But the research does reveal factors that are likely important prognostic indicators in PTCL.

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Estrogen promotes HSC activity

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HSCs in the bone marrow

Scientists have long thought that hematopoietic stem cells (HSCs) are regulated similarly in males and females.

But research conducted in mice has shown that HSCs exhibit sex differences in cell-cycle regulation.

The researchers discovered that HSCs in female mice divided significantly more frequently than HSCs in male mice, and this appeared to be driven by estrogen.

Sean Morrison, PhD, of UT Southwestern Medical Center in Dallas, and his colleagues detailed these discoveries in a letter to Nature.

The research suggested that differences in HSC division depend on the ovaries and not the testes. When the investigators administered estradiol, a hormone produced mainly in the ovaries, to male and female mice, HSC division increased in both sexes.

And experiments in pregnant mice highlighted the importance of estrogen in HSC activity. Estrogen levels increased during pregnancy, which increased HSC division, HSC frequency, cellularity, and erythropoiesis in the spleen.

“Elevated estrogen levels that are sustained during pregnancy induce stem cell mobilization and red cell production in the spleen, which serves as a reserve site for additional red blood cell production,” Dr Morrison said.

He and his colleagues also found that HSCs expressed high levels of estrogen receptor-alpha. And deleting the receptor reduced HSC division in female mice but not in males.

In pregnant mice, deleting the receptor attenuated the previously observed increases in HSC division, HSC frequency, and erythropoiesis.

These results suggest estrogen acts directly on HSCs to increase their proliferation and the number of red blood cells they generate.

“If estrogen has the same effect on stem cells in humans as in mice, then this effect raises a number of possibilities that could change the way we treat people with diseases of blood cell formation,” Dr Morrison said.

“Can we promote regeneration in the blood-forming system by administering estrogen? Can we reduce the toxicity of chemotherapy to the blood-forming system by taking into account estrogen levels in female patients? Does estrogen promote the growth of some blood cancers? There are numerous clinical opportunities to pursue.”

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HSCs in the bone marrow

Scientists have long thought that hematopoietic stem cells (HSCs) are regulated similarly in males and females.

But research conducted in mice has shown that HSCs exhibit sex differences in cell-cycle regulation.

The researchers discovered that HSCs in female mice divided significantly more frequently than HSCs in male mice, and this appeared to be driven by estrogen.

Sean Morrison, PhD, of UT Southwestern Medical Center in Dallas, and his colleagues detailed these discoveries in a letter to Nature.

The research suggested that differences in HSC division depend on the ovaries and not the testes. When the investigators administered estradiol, a hormone produced mainly in the ovaries, to male and female mice, HSC division increased in both sexes.

And experiments in pregnant mice highlighted the importance of estrogen in HSC activity. Estrogen levels increased during pregnancy, which increased HSC division, HSC frequency, cellularity, and erythropoiesis in the spleen.

“Elevated estrogen levels that are sustained during pregnancy induce stem cell mobilization and red cell production in the spleen, which serves as a reserve site for additional red blood cell production,” Dr Morrison said.

He and his colleagues also found that HSCs expressed high levels of estrogen receptor-alpha. And deleting the receptor reduced HSC division in female mice but not in males.

In pregnant mice, deleting the receptor attenuated the previously observed increases in HSC division, HSC frequency, and erythropoiesis.

These results suggest estrogen acts directly on HSCs to increase their proliferation and the number of red blood cells they generate.

“If estrogen has the same effect on stem cells in humans as in mice, then this effect raises a number of possibilities that could change the way we treat people with diseases of blood cell formation,” Dr Morrison said.

“Can we promote regeneration in the blood-forming system by administering estrogen? Can we reduce the toxicity of chemotherapy to the blood-forming system by taking into account estrogen levels in female patients? Does estrogen promote the growth of some blood cancers? There are numerous clinical opportunities to pursue.”

HSCs in the bone marrow

Scientists have long thought that hematopoietic stem cells (HSCs) are regulated similarly in males and females.

But research conducted in mice has shown that HSCs exhibit sex differences in cell-cycle regulation.

The researchers discovered that HSCs in female mice divided significantly more frequently than HSCs in male mice, and this appeared to be driven by estrogen.

Sean Morrison, PhD, of UT Southwestern Medical Center in Dallas, and his colleagues detailed these discoveries in a letter to Nature.

The research suggested that differences in HSC division depend on the ovaries and not the testes. When the investigators administered estradiol, a hormone produced mainly in the ovaries, to male and female mice, HSC division increased in both sexes.

And experiments in pregnant mice highlighted the importance of estrogen in HSC activity. Estrogen levels increased during pregnancy, which increased HSC division, HSC frequency, cellularity, and erythropoiesis in the spleen.

“Elevated estrogen levels that are sustained during pregnancy induce stem cell mobilization and red cell production in the spleen, which serves as a reserve site for additional red blood cell production,” Dr Morrison said.

He and his colleagues also found that HSCs expressed high levels of estrogen receptor-alpha. And deleting the receptor reduced HSC division in female mice but not in males.

In pregnant mice, deleting the receptor attenuated the previously observed increases in HSC division, HSC frequency, and erythropoiesis.

These results suggest estrogen acts directly on HSCs to increase their proliferation and the number of red blood cells they generate.

“If estrogen has the same effect on stem cells in humans as in mice, then this effect raises a number of possibilities that could change the way we treat people with diseases of blood cell formation,” Dr Morrison said.

“Can we promote regeneration in the blood-forming system by administering estrogen? Can we reduce the toxicity of chemotherapy to the blood-forming system by taking into account estrogen levels in female patients? Does estrogen promote the growth of some blood cancers? There are numerous clinical opportunities to pursue.”

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Cancer doesn’t increase a child’s risk of PTSD

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Cancer patient

Credit: Bill Branson

Childhood cancer patients are no more likely than their healthy peers to develop post-traumatic stress disorder (PTSD), according to research published in the Journal of Clinical Oncology.

“A cancer diagnosis is a highly significant and challenging event, but this study highlights the impressive capacity of children to adjust to changes in their lives and, in most cases, do just fine or even thrive emotionally as a result,” said study author Sean Phipps, PhD, of St Jude Children’s Research Hospital in Memphis.

PTSD is a treatable anxiety disorder that can develop following terrifying events that result in real or potential physical harm. The diagnosis is based on patient reports of certain symptoms, including persistent frightening thoughts, flashbacks, numbness, detachment, and sleep disturbances.

For this study, researchers used 3 established PTSD screening methods on 255 pediatric cancer patients (aged 8 to 17 at diagnosis) and 101 of their healthy, demographically matched peers.

This included a symptom check list and a structured diagnostic interview about the event in a child’s life he or she identified as the most traumatic. The researchers also interviewed parents about PTSD symptoms in themselves and their children.

Based on self-reported symptoms, 2.8% of cancer patients (n=7) met the criteria for a diagnosis of PTSD, either when the study was conducted or in the past.

The PTSD was cancer-related in 2 of these patients. In the other 5 patients, the disorder was linked to a drive-by shooting, Hurricane Katrina, or other stressful events.

By diagnostic interview, 0.4% of the cancer patients met PTSD criteria. According to parents’ reports, 1.6% of the cancer patients met criteria for current PTSD, and 5.9% met lifetime criteria.

These rates of PTSD were not significantly different from the rates reported in the healthy control subjects (all P values were greater than 0.1).

Unlike many previous studies of PTSD in cancer patients, researchers initially refrained from asking patients specifically about their diagnosis. Investigators wanted to avoid suggesting to patients that their cancer diagnoses were traumatic.

“We know such suggestions, called ‘focusing illusions,’ prime individuals to think about their cancer experience as traumatic and leaves them prone to exaggerating its impact in subjective reports,” Dr Phipps said.

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Cancer patient

Credit: Bill Branson

Childhood cancer patients are no more likely than their healthy peers to develop post-traumatic stress disorder (PTSD), according to research published in the Journal of Clinical Oncology.

“A cancer diagnosis is a highly significant and challenging event, but this study highlights the impressive capacity of children to adjust to changes in their lives and, in most cases, do just fine or even thrive emotionally as a result,” said study author Sean Phipps, PhD, of St Jude Children’s Research Hospital in Memphis.

PTSD is a treatable anxiety disorder that can develop following terrifying events that result in real or potential physical harm. The diagnosis is based on patient reports of certain symptoms, including persistent frightening thoughts, flashbacks, numbness, detachment, and sleep disturbances.

For this study, researchers used 3 established PTSD screening methods on 255 pediatric cancer patients (aged 8 to 17 at diagnosis) and 101 of their healthy, demographically matched peers.

This included a symptom check list and a structured diagnostic interview about the event in a child’s life he or she identified as the most traumatic. The researchers also interviewed parents about PTSD symptoms in themselves and their children.

Based on self-reported symptoms, 2.8% of cancer patients (n=7) met the criteria for a diagnosis of PTSD, either when the study was conducted or in the past.

The PTSD was cancer-related in 2 of these patients. In the other 5 patients, the disorder was linked to a drive-by shooting, Hurricane Katrina, or other stressful events.

By diagnostic interview, 0.4% of the cancer patients met PTSD criteria. According to parents’ reports, 1.6% of the cancer patients met criteria for current PTSD, and 5.9% met lifetime criteria.

These rates of PTSD were not significantly different from the rates reported in the healthy control subjects (all P values were greater than 0.1).

Unlike many previous studies of PTSD in cancer patients, researchers initially refrained from asking patients specifically about their diagnosis. Investigators wanted to avoid suggesting to patients that their cancer diagnoses were traumatic.

“We know such suggestions, called ‘focusing illusions,’ prime individuals to think about their cancer experience as traumatic and leaves them prone to exaggerating its impact in subjective reports,” Dr Phipps said.

Cancer patient

Credit: Bill Branson

Childhood cancer patients are no more likely than their healthy peers to develop post-traumatic stress disorder (PTSD), according to research published in the Journal of Clinical Oncology.

“A cancer diagnosis is a highly significant and challenging event, but this study highlights the impressive capacity of children to adjust to changes in their lives and, in most cases, do just fine or even thrive emotionally as a result,” said study author Sean Phipps, PhD, of St Jude Children’s Research Hospital in Memphis.

PTSD is a treatable anxiety disorder that can develop following terrifying events that result in real or potential physical harm. The diagnosis is based on patient reports of certain symptoms, including persistent frightening thoughts, flashbacks, numbness, detachment, and sleep disturbances.

For this study, researchers used 3 established PTSD screening methods on 255 pediatric cancer patients (aged 8 to 17 at diagnosis) and 101 of their healthy, demographically matched peers.

This included a symptom check list and a structured diagnostic interview about the event in a child’s life he or she identified as the most traumatic. The researchers also interviewed parents about PTSD symptoms in themselves and their children.

Based on self-reported symptoms, 2.8% of cancer patients (n=7) met the criteria for a diagnosis of PTSD, either when the study was conducted or in the past.

The PTSD was cancer-related in 2 of these patients. In the other 5 patients, the disorder was linked to a drive-by shooting, Hurricane Katrina, or other stressful events.

By diagnostic interview, 0.4% of the cancer patients met PTSD criteria. According to parents’ reports, 1.6% of the cancer patients met criteria for current PTSD, and 5.9% met lifetime criteria.

These rates of PTSD were not significantly different from the rates reported in the healthy control subjects (all P values were greater than 0.1).

Unlike many previous studies of PTSD in cancer patients, researchers initially refrained from asking patients specifically about their diagnosis. Investigators wanted to avoid suggesting to patients that their cancer diagnoses were traumatic.

“We know such suggestions, called ‘focusing illusions,’ prime individuals to think about their cancer experience as traumatic and leaves them prone to exaggerating its impact in subjective reports,” Dr Phipps said.

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Mandatory disclosures may make docs avoid COIs

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Doctor consults with a family

Credit: Rhoda Baer

Previous research has indicated that requiring conflict of interest (COI) disclosures may lead advisers to give more biased advice.

However, virtually all of the prior studies questioned the effectiveness of COI disclosures that advisers were unable to avoid.

With a new study, researchers examined situations in which advisers have the ability to avoid COIs—such as doctors who can decide whether to accept gifts or payments from pharmaceutical companies.

And the results showed that when COIs can be avoided, disclosure successfully deters advisers from accepting COIs, so they have nothing to disclose except the absence of conflicts.

The research was published in Psychological Science.

“Prior research has cast doubt as to the effectiveness of disclosure for managing conflicts of interest, particularly when consumers have the burden of interpreting and reacting to the information,” said study author Sunita Sah, PhD, MB ChB, of Georgetown University in Washington, DC.

“Our findings suggest that disclosure can become a successful intervention to managing some conflicts of interest if it motivates professionals or providers to avoid such conflicts.”

For this study, the researchers conducted 3 experiments to determine how COIs influence advisers. In the first experiment, 97 adviser–advisee pairs participated in an online game with Amazon.com gift cards at stake.

Advisers informed the advisees regarding the number of filled dots on a grid. The estimators were paid based on their accuracy, but advisers had a conflict. They were paid more if advisees gave an estimate that was higher than the true value.

The set up—with advisees only seeing a small subset of the complete grid—was designed to simulate a situation in which a consumer receives advice from a better-informed but conflicted professional. The results replicated previous research and showed that disclosure led advisers to give higher (and more biased) recommendations than nondisclosure.

In the second experiment, the researchers again randomly assigned pairs of advisees and advisers to conditions in which the conflict was either disclosed or not disclosed.

There was, however, an important change from the first study. Advisers were given a choice of whether to accept or reject the COI.

Without disclosure, a majority of advisers (63%) chose the incentives that created a COI. But with disclosure, a minority (33%) accepted the conflict.

Advice was higher (and more biased) for those who chose incentives with conflicts than for those who did not, and advisers in the disclosure condition gave significantly less biased advice than those in the nondisclosure condition.

Finally, in a study with 248 participants, the researchers added a third condition to the second experiment: voluntary disclosure. In this third condition, advisers decided both whether to choose incentives that entailed a conflict and whether to disclose if they had a conflict.

Similar to mandatory disclosure, voluntary disclosure led advisers to avoid COIs and then disclose their freedom from conflicts to advisees.

“Disclosure doesn’t seem to be much good when conflicts are unavoidable, but it does seem to help when advisers have a choice about whether to subject themselves to conflicts,” said study author George Loewenstein, PhD, of Carnegie Mellon University in Pittsburgh.

“A nice feature of disclosure is that it is, in effect, ‘self-calibrating.’ Doctors, for example, are unlikely to find it worth it to accept small gifts such as pens or calendars if the gifts are going to be disclosed. Although larger gifts would be more tempting, doctors are likely to be deterred from accepting them because disclosure of large gifts would be more damaging to their reputations.”

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Doctor consults with a family

Credit: Rhoda Baer

Previous research has indicated that requiring conflict of interest (COI) disclosures may lead advisers to give more biased advice.

However, virtually all of the prior studies questioned the effectiveness of COI disclosures that advisers were unable to avoid.

With a new study, researchers examined situations in which advisers have the ability to avoid COIs—such as doctors who can decide whether to accept gifts or payments from pharmaceutical companies.

And the results showed that when COIs can be avoided, disclosure successfully deters advisers from accepting COIs, so they have nothing to disclose except the absence of conflicts.

The research was published in Psychological Science.

“Prior research has cast doubt as to the effectiveness of disclosure for managing conflicts of interest, particularly when consumers have the burden of interpreting and reacting to the information,” said study author Sunita Sah, PhD, MB ChB, of Georgetown University in Washington, DC.

“Our findings suggest that disclosure can become a successful intervention to managing some conflicts of interest if it motivates professionals or providers to avoid such conflicts.”

For this study, the researchers conducted 3 experiments to determine how COIs influence advisers. In the first experiment, 97 adviser–advisee pairs participated in an online game with Amazon.com gift cards at stake.

Advisers informed the advisees regarding the number of filled dots on a grid. The estimators were paid based on their accuracy, but advisers had a conflict. They were paid more if advisees gave an estimate that was higher than the true value.

The set up—with advisees only seeing a small subset of the complete grid—was designed to simulate a situation in which a consumer receives advice from a better-informed but conflicted professional. The results replicated previous research and showed that disclosure led advisers to give higher (and more biased) recommendations than nondisclosure.

In the second experiment, the researchers again randomly assigned pairs of advisees and advisers to conditions in which the conflict was either disclosed or not disclosed.

There was, however, an important change from the first study. Advisers were given a choice of whether to accept or reject the COI.

Without disclosure, a majority of advisers (63%) chose the incentives that created a COI. But with disclosure, a minority (33%) accepted the conflict.

Advice was higher (and more biased) for those who chose incentives with conflicts than for those who did not, and advisers in the disclosure condition gave significantly less biased advice than those in the nondisclosure condition.

Finally, in a study with 248 participants, the researchers added a third condition to the second experiment: voluntary disclosure. In this third condition, advisers decided both whether to choose incentives that entailed a conflict and whether to disclose if they had a conflict.

Similar to mandatory disclosure, voluntary disclosure led advisers to avoid COIs and then disclose their freedom from conflicts to advisees.

“Disclosure doesn’t seem to be much good when conflicts are unavoidable, but it does seem to help when advisers have a choice about whether to subject themselves to conflicts,” said study author George Loewenstein, PhD, of Carnegie Mellon University in Pittsburgh.

“A nice feature of disclosure is that it is, in effect, ‘self-calibrating.’ Doctors, for example, are unlikely to find it worth it to accept small gifts such as pens or calendars if the gifts are going to be disclosed. Although larger gifts would be more tempting, doctors are likely to be deterred from accepting them because disclosure of large gifts would be more damaging to their reputations.”

Doctor consults with a family

Credit: Rhoda Baer

Previous research has indicated that requiring conflict of interest (COI) disclosures may lead advisers to give more biased advice.

However, virtually all of the prior studies questioned the effectiveness of COI disclosures that advisers were unable to avoid.

With a new study, researchers examined situations in which advisers have the ability to avoid COIs—such as doctors who can decide whether to accept gifts or payments from pharmaceutical companies.

And the results showed that when COIs can be avoided, disclosure successfully deters advisers from accepting COIs, so they have nothing to disclose except the absence of conflicts.

The research was published in Psychological Science.

“Prior research has cast doubt as to the effectiveness of disclosure for managing conflicts of interest, particularly when consumers have the burden of interpreting and reacting to the information,” said study author Sunita Sah, PhD, MB ChB, of Georgetown University in Washington, DC.

“Our findings suggest that disclosure can become a successful intervention to managing some conflicts of interest if it motivates professionals or providers to avoid such conflicts.”

For this study, the researchers conducted 3 experiments to determine how COIs influence advisers. In the first experiment, 97 adviser–advisee pairs participated in an online game with Amazon.com gift cards at stake.

Advisers informed the advisees regarding the number of filled dots on a grid. The estimators were paid based on their accuracy, but advisers had a conflict. They were paid more if advisees gave an estimate that was higher than the true value.

The set up—with advisees only seeing a small subset of the complete grid—was designed to simulate a situation in which a consumer receives advice from a better-informed but conflicted professional. The results replicated previous research and showed that disclosure led advisers to give higher (and more biased) recommendations than nondisclosure.

In the second experiment, the researchers again randomly assigned pairs of advisees and advisers to conditions in which the conflict was either disclosed or not disclosed.

There was, however, an important change from the first study. Advisers were given a choice of whether to accept or reject the COI.

Without disclosure, a majority of advisers (63%) chose the incentives that created a COI. But with disclosure, a minority (33%) accepted the conflict.

Advice was higher (and more biased) for those who chose incentives with conflicts than for those who did not, and advisers in the disclosure condition gave significantly less biased advice than those in the nondisclosure condition.

Finally, in a study with 248 participants, the researchers added a third condition to the second experiment: voluntary disclosure. In this third condition, advisers decided both whether to choose incentives that entailed a conflict and whether to disclose if they had a conflict.

Similar to mandatory disclosure, voluntary disclosure led advisers to avoid COIs and then disclose their freedom from conflicts to advisees.

“Disclosure doesn’t seem to be much good when conflicts are unavoidable, but it does seem to help when advisers have a choice about whether to subject themselves to conflicts,” said study author George Loewenstein, PhD, of Carnegie Mellon University in Pittsburgh.

“A nice feature of disclosure is that it is, in effect, ‘self-calibrating.’ Doctors, for example, are unlikely to find it worth it to accept small gifts such as pens or calendars if the gifts are going to be disclosed. Although larger gifts would be more tempting, doctors are likely to be deterred from accepting them because disclosure of large gifts would be more damaging to their reputations.”

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Challenges in Training: Open repair in 2020

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Since FDA approval of endovascular aneurysm repair in 1999, the management of abdominal aortic aneurysms has transformed. Only 5.2% of AAAs were repaired by EVAR in 2000 compared to 74% in 2010. While the volume of AAA cases has remained constant at about 45,000 cases annually, the increase in EVAR has led to a 34% drop in open AAA cases. This national decline in open AAA cases is paralleled by a 33% decline in open AAA cases completed by vascular trainees since 2001, as reported in national Accreditation Council for Graduate Medical Education case logs.

Dr. Desai

In conjunction with this decrease in open AAA repair volume, trainees are reporting low confidence in independently performing open aneurysm cases, with nearly 40% of 2014 graduating vascular trainees having expressed low confidence in their ability on a 3-point Likert scale (1 – not confident, 2 – somewhat confident, 3 – very confident).

Over the past decade, we have also seen a threefold increase in adjudicated cases against vascular surgeons due to complications arising from open AAA cases, along with an increase in litigation against vascular surgeons who have been in practice for fewer than 3 years.

Open AAA surgery volume will continue to decrease as branched and fenestrated technology improves, and as expanded utilization in patients with complex anatomy occurs with the next generation of endografts.

By 2020, based on prediction models, vascular trainees will complete only five open aneurysm cases during their training, This raises serious questions about how we will educate the next generation of vascular surgeons to safely and effectively manage patients who can be treated only by open repair.

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Since FDA approval of endovascular aneurysm repair in 1999, the management of abdominal aortic aneurysms has transformed. Only 5.2% of AAAs were repaired by EVAR in 2000 compared to 74% in 2010. While the volume of AAA cases has remained constant at about 45,000 cases annually, the increase in EVAR has led to a 34% drop in open AAA cases. This national decline in open AAA cases is paralleled by a 33% decline in open AAA cases completed by vascular trainees since 2001, as reported in national Accreditation Council for Graduate Medical Education case logs.

Dr. Desai

In conjunction with this decrease in open AAA repair volume, trainees are reporting low confidence in independently performing open aneurysm cases, with nearly 40% of 2014 graduating vascular trainees having expressed low confidence in their ability on a 3-point Likert scale (1 – not confident, 2 – somewhat confident, 3 – very confident).

Over the past decade, we have also seen a threefold increase in adjudicated cases against vascular surgeons due to complications arising from open AAA cases, along with an increase in litigation against vascular surgeons who have been in practice for fewer than 3 years.

Open AAA surgery volume will continue to decrease as branched and fenestrated technology improves, and as expanded utilization in patients with complex anatomy occurs with the next generation of endografts.

By 2020, based on prediction models, vascular trainees will complete only five open aneurysm cases during their training, This raises serious questions about how we will educate the next generation of vascular surgeons to safely and effectively manage patients who can be treated only by open repair.

Since FDA approval of endovascular aneurysm repair in 1999, the management of abdominal aortic aneurysms has transformed. Only 5.2% of AAAs were repaired by EVAR in 2000 compared to 74% in 2010. While the volume of AAA cases has remained constant at about 45,000 cases annually, the increase in EVAR has led to a 34% drop in open AAA cases. This national decline in open AAA cases is paralleled by a 33% decline in open AAA cases completed by vascular trainees since 2001, as reported in national Accreditation Council for Graduate Medical Education case logs.

Dr. Desai

In conjunction with this decrease in open AAA repair volume, trainees are reporting low confidence in independently performing open aneurysm cases, with nearly 40% of 2014 graduating vascular trainees having expressed low confidence in their ability on a 3-point Likert scale (1 – not confident, 2 – somewhat confident, 3 – very confident).

Over the past decade, we have also seen a threefold increase in adjudicated cases against vascular surgeons due to complications arising from open AAA cases, along with an increase in litigation against vascular surgeons who have been in practice for fewer than 3 years.

Open AAA surgery volume will continue to decrease as branched and fenestrated technology improves, and as expanded utilization in patients with complex anatomy occurs with the next generation of endografts.

By 2020, based on prediction models, vascular trainees will complete only five open aneurysm cases during their training, This raises serious questions about how we will educate the next generation of vascular surgeons to safely and effectively manage patients who can be treated only by open repair.

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Calcium Hydroxylapatite Filler Foreign Body Granulomas: A Case Report of a Rare Occurrence and Review of the Literature

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Laurel R. Schwartz, MD; Christina Thompson, BBA; Carmen Campanelli, MD

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