Letters RESEARCH LETTER
Quality Measures Based on Presenting Signs and Symptoms of Patients Health care reform efforts, such as accountable care organizations, focus on improving value partly through controlling use of services, including diagnostic tests. Some have expressed concern that these efforts may result in delayed diagnosis and subsequent Supplemental content at jama.com patient harm. 1 Publicly reported quality measures that evaluate care provided prior to arriving at a diagnosis could prevent financial incentives from producing harm. The Institute of Medicine (IOM) previously developed a conceptual framework for categorizing process quality measures.2 The IOM framework includes criteria related to prevention, screening, evaluation/diagnosis, management, and follow-up.2 The National Quality Forum (NQF) currently serves as the consensus-based quality-measure–endorsement entity called for in the Affordable Care Act. Measures are submitted to the NQF by professional societies, government agencies, health
systems, nonprofit organizations, and industry. Multistakeholder expert committees assess proposed measures using specific evaluation criteria. Endorsed measures are often adopted by the Centers for Medicare & Medicaid Services in payment and public reporting programs.3 We determined how NQF-endorsed process measures match the entire IOM framework and concentrated on quality measures that evaluate the prediagnostic care of patients presenting with signs or symptoms. We then compared these sign/symptom-based quality measures with the most common reasons people seek care. Methods | Based on predefined criteria (eAppendix in the Supplement), 3 of the authors categorized each NQFendorsed process measure into 1 of the 5 IOM groups. We then subclassified the evaluation/diagnosis- and managementrelated measures by their NQF-designated denominator and numerator. The NQF denominator indicates the characteristic or population to which the quality measure applies. We grouped denominator statements by sign/symptom (eg, chest pain), established diagnosis (eg, diabetes), procedure (eg, coronary artery bypass grafting), medication (eg, lithium), diagnostic test (eg, carotid imaging study), or other. The numera-
Table 1. Process Measures Endorsed by the National Quality Forum (NQF) Listed by Institute of Medicine (IOM) Category and Population to Which Each Measure Applies Population to Which Measure Applies IOM Category
NQF Denominator
NQF Numerator
Percentage of live newborns that receive hepatitis B vaccination before discharge at each hospital or birthing facility during given period (1 year)
Screening
The percentage of adolescents aged 18 y who are screened for depression using a standardized tool
Diagnosis/ evaluation
Sign/symptom
Medical imaging
Percentage of pregnant patients who present to the emergency department with a chief concern of abdominal pain and/or vaginal bleeding (denominator) who receive a transabdominal or transvaginal ultrasound (numerator)
Diagnosis/ evaluation
Established diagnosis
In vitro diagnosticsa
Percentage of adult patients (aged ≥18 y) with invasive breast cancer (denominator) who receive human epidermal growth factor receptor 2 testing (numerator)
Management
Sign/symptom
Otherb
Percentage of patients aged 65 y or older at long-stay nursing homes who have a new balance problem (denominator) and receive physical therapy, nursing rehabilitation, or restorative care (numerator)
Management
Established diagnosis
In vitro diagnosticsa
Percentage of pediatric patients aged 5-17 y with diabetes (denominator) who receive a test for hemoglobin A1c during the measurement year (numerator)
Management
Procedure
Otherb
Percentage of patients aged 18 y or older undergoing isolated coronary artery bypass grafting (denominator) who are discharged while taking an antiplatelet medication (numerator)
Management
Medication
In vitro diagnosticsa
Percentage of patients taking lithium (denominator) who have at least 1 creatinine test after the earliest observed lithium prescription during the measurement year (numerator)
Follow-up
Screening and management
520
Example Measure
Prevention
Percentage of patients who are treated with a psychostimulant medication for the diagnosis of attention-deficit/hyperactivity disorder whose medical record contains documentation of a follow-up visit at least twice/y Otherb
Established diagnosis
Percentage of patients aged 18 y or older who are screened for unhealthy alcohol use at least once during the 2-year measurement period using a systematic screening method and who will receive brief counseling (numerator) if identified as an unhealthy alcohol user (denominator)
a
Includes blood, urine, and pathology tests.
b
All numerators not pertaining to in vitro diagnostics and medical imaging were considered other. The majority of these included treatments (eg, medication, counseling, and rehabilitation) or medical record documentation.
JAMA February 3, 2015 Volume 313, Number 5 (Reprinted)
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Letters
Table 2. Most Common Signs and Symptoms for Which Patients Seek Care in Hospital-Affiliated Outpatient and Emergency Department Settingsa Most Common Signs/Symptoms for Seeking Care
Frequency in Millions (Percentage of Total Visits)
Corresponding Sign/Symptom-Based NQF-Endorsed Measures
Outpatient Settingb Cough
2.3 (2.2)
Stomach and abdominal pain, cramps, and spasms
1.7 (1.6)
None None
Symptoms referable to the throat
1.6 (1.6)
None
Earache
1.2 (1.2)c
None
Knee symptoms
1.2 (1.1)
None
Back symptoms
1.0 (1.0)
The percentage of members with a primary diagnosis of low back pain who did not have an imaging study (plain x-ray, MRI, CT scan) within 28 d of the diagnosis
Rash
0.9 (0.9)
None
Headache, pain in head
0.9 (0.9)
None
Fever
0.9 (0.9)
None
Emergency Department Setting Stomach and abdominal pain, cramps, and spasms
10.4 (8.0)
Percentage of pregnant patients who present with a chief concern of abdominal pain and/or vaginal bleeding and who receive a transabdominal or transvaginal ultrasound Median time from arrival to electrocardiogram (performed prior to transfer to another department) for AMI or chest pain (probable cardiac chest pain)
Chest pain and related symptoms (not referable to body systems)
Percentage of patients with AMI or chest pain (probable cardiac chest pain) without aspirin contraindications who received aspirin within 24 h before arrival or prior to transfer to another department
7.0 (5.4)
Percentage of patients aged 40 y or older with a discharge diagnosis of nontraumatic chest pain who had an electrocardiogram performed Fever
5.0 (3.8)
Headache, pain in head
4.0 (3.1)
None
Back symptoms
3.5 (2.7)
Percentage of members with a primary diagnosis of low back pain who did not have an imaging study (plain x-ray, MRI, CT scan) within 28 d of the diagnosis
Shortness of breath
3.5 (2.7)
None
Cough
3.4 (2.7)
None
Pain (site not referable to specific body system)
3.2 (2.4)
None
Vomiting
2.5 (1.9)
None
Symptoms referable to throat
2.4 (1.8)
Abbreviations: AMI, acute myocardial infarction; CT, computed tomographic; MRI, magnetic resonance imaging; NQF, National Quality Forum. a
None
None b
Refers to hospital outpatient departments.
c
Estimate includes visits for ear infections.
Based on data from the National Hospital Ambulatory Medical Care Survey 2010 Hospital-Affiliated Outpatient and Emergency Department Summary Tables.4,5
tor is the action taken by a clinician. We grouped numerator statements into use of in vitro diagnostics (IVD), which include blood, urine, and pathology tests; medical imaging; or other, which most often described a treatment (Table 1). We used 2010 National (Hospital) Ambulatory Medical Care Survey data to compare the sign/symptom-based measures with the most common reasons people seek care.4,5 Results | Of 372 process quality measures listed on the NQF website as of June 4, 2014, 360 were coded into a unique IOM category, 11 into 2 categories, and 1 into 3 categories, resulting in 385 codings. Approximately two-thirds (n = 267) targeted disease management and 12% (n = 46) targeted evaluation/ diagnosis. The remaining were evenly distributed among prevention, screening, and follow-up. Of 313 measures pertaining to evaluation/diagnosis or management, 211 (67%) began with an established diagnosis, whereas 14 (4.5%) started with a sign/symptom. The
sign/symptom-based measures focused on geriatric care (eg, memory loss, falls, urine leakage) or emergency department care (eg, chest pain). In contrast, many common reasons for which patients seek care, including fever, cough, headache, shortness of breath, earache, rash, and throat symptoms, were not reflected by the quality measures (Table 2).4,5 The performance of an IVD or medical imaging study was the action required by 59 of 313 (19%) endorsed quality measures; many others required actions related to medication prescribing. Discussion | Existing NQF-endorsed process measures focus predominantly on management of patients with established diagnoses. The prediagnostic care of patients is rarely assessed, and the 14 sign/symptom-based measures infrequently reflect the most common reasons patients seek care. Even though we used defined coding criteria, our work is limited by subjective categorization of the measures and our
jama.com
(Reprinted) JAMA February 3, 2015 Volume 313, Number 5
Copyright 2015 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a J H Quillen College User on 05/31/2015
521
Letters
focus on process measures as opposed to outcome measures. Nevertheless, we believe that using a comprehensive set of endorsed sign/symptom-based measures could help patients receive timely care as payment models are changed and may prevent financial incentives from resulting in underuse of necessary care. Efforts to develop valid sign/symptom-based quality measures will be challenging; however, as cost pressures increase, they may be necessary to maintain and improve the accuracy of patient diagnosis upon which all subsequent care depends. Hemal K. Kanzaria, MD, MSHPM Soeren Mattke, MD, DSc, MPH Alissa A. Detz, MD, MSHPM Robert H. Brook, MD, ScD Author Affiliations: Veterans Affairs/Robert Wood Johnson Clinical Scholars Program, University of California, Los Angeles (Kanzaria); RAND Corporation, Boston, Massachusetts (Mattke); Department of Medicine, University of California, Los Angeles (Detz); Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles (Brook). Corresponding Author: Hemal K. Kanzaria, MD, MSHPM, Veterans Affairs/ Robert Wood Johnson Clinical Scholars Program, University of California, Los Angeles, 10940 Wilshire Blvd, Los Angeles, CA 90024 ([email protected]). Author Contributions: Dr Kanzaria had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors reviewed the National Quality Forum categorization. Study concept and design: All authors. Acquisition, analysis, or interpretation of data: All authors. Drafting of the manuscript: Kanzaria. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: All authors. Administrative, technical, or material support: All authors. Study supervision: Mattke, Brook. Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. Funding/Support: This work was supported by the Robert Wood Johnson Clinical Scholars program, the US Department of Veterans Affairs, grant T32-HP19001 (UCLA Institutional National Research Service Award) from the Health Resources and Services Administration, and funding from the RAND Corporation. Role of the Funder/Sponsor: The funders/sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Additional Contributions: We are grateful to Mary Vaiana, PhD (RAND Corporation), for her careful review of an earlier draft of this manuscript, for which she received compensation. 1. Goitein L. The argument against reimbursing physicians for value. JAMA Intern Med. 2014;174(6):845-846. 2. Institute of Medicine. Development of Methodology for Evaluation of Neighborhood Health Centers. Washington, DC: National Academy of Sciences; 1972. 3. National Quality Forum. Providing a road map for better care. http://www .qualityforum.org/Home.aspx. Accessed June 16, 2014. 4. US Centers for Disease Control and Prevention. Table 7: Twenty leading principal reasons for outpatient department visits: United States, 2010. http: //www.cdc.gov/nchs/data/ahcd/nhamcs_outpatient/2010_opd_web_tables.pdf. Accessed August 4, 2014. 5. US Centers for Disease Control and Prevention. Table 10: Ten leading principal reasons for emergency department visits, by patient age and sex: United States, 2010. http://www.cdc.gov/nchs/data/ahcd/nhamcs_emergency /2010_ed_web_tables.pdf. Accessed August 4, 2014. 522
COMMENT & RESPONSE
Age Cutoffs for Bioprosthetic vs Mechanical Aortic Valve Replacement To the Editor Mr Chiang and colleagues1 reported that patients aged 50 to 69 years who underwent aortic valve replacement had comparable 15-year survival with implantation of a bioprosthesis or a mechanical prosthesis, suggesting that bioprosthetic valves “may be a reasonable choice” in patients aged 50 years or older. We recognize that, in part because of the advent of transcatheter aortic valve implantation and the possibility of placing a transcatheter heart valve in bioprosthetic valves with structural valve deterioration,2 bioprostheses are becoming a more attractive alternative to mechanical prostheses.3 However, additional data are required before lowering the age cutoff for implanting bioprostheses can be justified. Younger patients with a bioprosthetic valve have a higher rate of structural valve deterioration than older patients; in 1 study4 with more than 10 years of follow-up, structural valve deterioration was 6% in patients aged 61 to 70 years and 18% in those aged 51 to 60 years. As a result, the hazard ratio for death after implantation of mechanical vs bioprosthetic valves can vary significantly in different age categories, with the highest mortality benefit using a mechanical valve in younger patients.5 Therefore, the authors should perform a subgroup analysis according to age tertiles to ensure that their findings are consistent across age groups. In the study by Chiang et al,1 patients with a bioprosthesis required higher rates of reoperation, whereas the rate of major bleeding was higher with mechanical valves. However, major bleeding included relatively minor events of hematuria and hemoptysis, as well as more severe events of intracranial hemorrhage, cardiac tamponade, and gastrointestinal hemorrhage. Without further data on the severity of bleeding (number of packed red blood cell transfusions, length of hospitalization, and decrease in hemoglobin level), the effect of bleeding on quality of life remains unclear. In contrast to bleeding events that have a short-term effect on quality of life, the problem of structural valve deterioration is a gradual process affecting quality of life over a longer period. Moreover, multiple reoperations may be required as life expectancy increases, which can be associated with additional risks of complications and reduced quality of life. Lowering the age cutoff to implant bioprosthetic valves therefore seems counterintuitive. For these reasons, randomized trials need to be performed to allow estimation of an individual patient’s riskbenefit ratio based on mortality, reoperation, bleeding, and quality of life. Until then, we do not believe the available evidence supports lowering the age cutoff for bioprosthetic valves. Stuart J. Head, PhD Ruben L. Osnabrugge, MSc A. Pieter Kappetein, MD, PhD Author Affiliations: Department of Cardiothoracic Surgery, Erasmus University Medical Center, Rotterdam, the Netherlands. Corresponding Author: A. Pieter Kappetein, MD, PhD, Department of Cardiothoracic Surgery, Erasmus University Medical Center, PO Box 2040, 3000 CA Rotterdam, the Netherlands ([email protected]).
JAMA February 3, 2015 Volume 313, Number 5 (Reprinted)
Copyright 2015 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a J H Quillen College User on 05/31/2015
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Quality Measures Based on Presenting Signs and Symptoms of Patients Health care reform efforts, such as accountable care organizations, focus on improving value partly through controlling use of services, including diagnostic tests. Some have expressed concern that these efforts may result in delayed diagnosis and subsequent Supplemental content at jama.com patient harm. 1 Publicly reported quality measures that evaluate care provided prior to arriving at a diagnosis could prevent financial incentives from producing harm. The Institute of Medicine (IOM) previously developed a conceptual framework for categorizing process quality measures.2 The IOM framework includes criteria related to prevention, screening, evaluation/diagnosis, management, and follow-up.2 The National Quality Forum (NQF) currently serves as the consensus-based quality-measure–endorsement entity called for in the Affordable Care Act. Measures are submitted to the NQF by professional societies, government agencies, health
systems, nonprofit organizations, and industry. Multistakeholder expert committees assess proposed measures using specific evaluation criteria. Endorsed measures are often adopted by the Centers for Medicare & Medicaid Services in payment and public reporting programs.3 We determined how NQF-endorsed process measures match the entire IOM framework and concentrated on quality measures that evaluate the prediagnostic care of patients presenting with signs or symptoms. We then compared these sign/symptom-based quality measures with the most common reasons people seek care. Methods | Based on predefined criteria (eAppendix in the Supplement), 3 of the authors categorized each NQFendorsed process measure into 1 of the 5 IOM groups. We then subclassified the evaluation/diagnosis- and managementrelated measures by their NQF-designated denominator and numerator. The NQF denominator indicates the characteristic or population to which the quality measure applies. We grouped denominator statements by sign/symptom (eg, chest pain), established diagnosis (eg, diabetes), procedure (eg, coronary artery bypass grafting), medication (eg, lithium), diagnostic test (eg, carotid imaging study), or other. The numera-
Table 1. Process Measures Endorsed by the National Quality Forum (NQF) Listed by Institute of Medicine (IOM) Category and Population to Which Each Measure Applies Population to Which Measure Applies IOM Category
NQF Denominator
NQF Numerator
Percentage of live newborns that receive hepatitis B vaccination before discharge at each hospital or birthing facility during given period (1 year)
Screening
The percentage of adolescents aged 18 y who are screened for depression using a standardized tool
Diagnosis/ evaluation
Sign/symptom
Medical imaging
Percentage of pregnant patients who present to the emergency department with a chief concern of abdominal pain and/or vaginal bleeding (denominator) who receive a transabdominal or transvaginal ultrasound (numerator)
Diagnosis/ evaluation
Established diagnosis
In vitro diagnosticsa
Percentage of adult patients (aged ≥18 y) with invasive breast cancer (denominator) who receive human epidermal growth factor receptor 2 testing (numerator)
Management
Sign/symptom
Otherb
Percentage of patients aged 65 y or older at long-stay nursing homes who have a new balance problem (denominator) and receive physical therapy, nursing rehabilitation, or restorative care (numerator)
Management
Established diagnosis
In vitro diagnosticsa
Percentage of pediatric patients aged 5-17 y with diabetes (denominator) who receive a test for hemoglobin A1c during the measurement year (numerator)
Management
Procedure
Otherb
Percentage of patients aged 18 y or older undergoing isolated coronary artery bypass grafting (denominator) who are discharged while taking an antiplatelet medication (numerator)
Management
Medication
In vitro diagnosticsa
Percentage of patients taking lithium (denominator) who have at least 1 creatinine test after the earliest observed lithium prescription during the measurement year (numerator)
Follow-up
Screening and management
520
Example Measure
Prevention
Percentage of patients who are treated with a psychostimulant medication for the diagnosis of attention-deficit/hyperactivity disorder whose medical record contains documentation of a follow-up visit at least twice/y Otherb
Established diagnosis
Percentage of patients aged 18 y or older who are screened for unhealthy alcohol use at least once during the 2-year measurement period using a systematic screening method and who will receive brief counseling (numerator) if identified as an unhealthy alcohol user (denominator)
a
Includes blood, urine, and pathology tests.
b
All numerators not pertaining to in vitro diagnostics and medical imaging were considered other. The majority of these included treatments (eg, medication, counseling, and rehabilitation) or medical record documentation.
JAMA February 3, 2015 Volume 313, Number 5 (Reprinted)
Copyright 2015 American Medical Association. All rights reserved.
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Letters
Table 2. Most Common Signs and Symptoms for Which Patients Seek Care in Hospital-Affiliated Outpatient and Emergency Department Settingsa Most Common Signs/Symptoms for Seeking Care
Frequency in Millions (Percentage of Total Visits)
Corresponding Sign/Symptom-Based NQF-Endorsed Measures
Outpatient Settingb Cough
2.3 (2.2)
Stomach and abdominal pain, cramps, and spasms
1.7 (1.6)
None None
Symptoms referable to the throat
1.6 (1.6)
None
Earache
1.2 (1.2)c
None
Knee symptoms
1.2 (1.1)
None
Back symptoms
1.0 (1.0)
The percentage of members with a primary diagnosis of low back pain who did not have an imaging study (plain x-ray, MRI, CT scan) within 28 d of the diagnosis
Rash
0.9 (0.9)
None
Headache, pain in head
0.9 (0.9)
None
Fever
0.9 (0.9)
None
Emergency Department Setting Stomach and abdominal pain, cramps, and spasms
10.4 (8.0)
Percentage of pregnant patients who present with a chief concern of abdominal pain and/or vaginal bleeding and who receive a transabdominal or transvaginal ultrasound Median time from arrival to electrocardiogram (performed prior to transfer to another department) for AMI or chest pain (probable cardiac chest pain)
Chest pain and related symptoms (not referable to body systems)
Percentage of patients with AMI or chest pain (probable cardiac chest pain) without aspirin contraindications who received aspirin within 24 h before arrival or prior to transfer to another department
7.0 (5.4)
Percentage of patients aged 40 y or older with a discharge diagnosis of nontraumatic chest pain who had an electrocardiogram performed Fever
5.0 (3.8)
Headache, pain in head
4.0 (3.1)
None
Back symptoms
3.5 (2.7)
Percentage of members with a primary diagnosis of low back pain who did not have an imaging study (plain x-ray, MRI, CT scan) within 28 d of the diagnosis
Shortness of breath
3.5 (2.7)
None
Cough
3.4 (2.7)
None
Pain (site not referable to specific body system)
3.2 (2.4)
None
Vomiting
2.5 (1.9)
None
Symptoms referable to throat
2.4 (1.8)
Abbreviations: AMI, acute myocardial infarction; CT, computed tomographic; MRI, magnetic resonance imaging; NQF, National Quality Forum. a
None
None b
Refers to hospital outpatient departments.
c
Estimate includes visits for ear infections.
Based on data from the National Hospital Ambulatory Medical Care Survey 2010 Hospital-Affiliated Outpatient and Emergency Department Summary Tables.4,5
tor is the action taken by a clinician. We grouped numerator statements into use of in vitro diagnostics (IVD), which include blood, urine, and pathology tests; medical imaging; or other, which most often described a treatment (Table 1). We used 2010 National (Hospital) Ambulatory Medical Care Survey data to compare the sign/symptom-based measures with the most common reasons people seek care.4,5 Results | Of 372 process quality measures listed on the NQF website as of June 4, 2014, 360 were coded into a unique IOM category, 11 into 2 categories, and 1 into 3 categories, resulting in 385 codings. Approximately two-thirds (n = 267) targeted disease management and 12% (n = 46) targeted evaluation/ diagnosis. The remaining were evenly distributed among prevention, screening, and follow-up. Of 313 measures pertaining to evaluation/diagnosis or management, 211 (67%) began with an established diagnosis, whereas 14 (4.5%) started with a sign/symptom. The
sign/symptom-based measures focused on geriatric care (eg, memory loss, falls, urine leakage) or emergency department care (eg, chest pain). In contrast, many common reasons for which patients seek care, including fever, cough, headache, shortness of breath, earache, rash, and throat symptoms, were not reflected by the quality measures (Table 2).4,5 The performance of an IVD or medical imaging study was the action required by 59 of 313 (19%) endorsed quality measures; many others required actions related to medication prescribing. Discussion | Existing NQF-endorsed process measures focus predominantly on management of patients with established diagnoses. The prediagnostic care of patients is rarely assessed, and the 14 sign/symptom-based measures infrequently reflect the most common reasons patients seek care. Even though we used defined coding criteria, our work is limited by subjective categorization of the measures and our
jama.com
(Reprinted) JAMA February 3, 2015 Volume 313, Number 5
Copyright 2015 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a J H Quillen College User on 05/31/2015
521
Letters
focus on process measures as opposed to outcome measures. Nevertheless, we believe that using a comprehensive set of endorsed sign/symptom-based measures could help patients receive timely care as payment models are changed and may prevent financial incentives from resulting in underuse of necessary care. Efforts to develop valid sign/symptom-based quality measures will be challenging; however, as cost pressures increase, they may be necessary to maintain and improve the accuracy of patient diagnosis upon which all subsequent care depends. Hemal K. Kanzaria, MD, MSHPM Soeren Mattke, MD, DSc, MPH Alissa A. Detz, MD, MSHPM Robert H. Brook, MD, ScD Author Affiliations: Veterans Affairs/Robert Wood Johnson Clinical Scholars Program, University of California, Los Angeles (Kanzaria); RAND Corporation, Boston, Massachusetts (Mattke); Department of Medicine, University of California, Los Angeles (Detz); Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles (Brook). Corresponding Author: Hemal K. Kanzaria, MD, MSHPM, Veterans Affairs/ Robert Wood Johnson Clinical Scholars Program, University of California, Los Angeles, 10940 Wilshire Blvd, Los Angeles, CA 90024 ([email protected]). Author Contributions: Dr Kanzaria had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors reviewed the National Quality Forum categorization. Study concept and design: All authors. Acquisition, analysis, or interpretation of data: All authors. Drafting of the manuscript: Kanzaria. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: All authors. Administrative, technical, or material support: All authors. Study supervision: Mattke, Brook. Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. Funding/Support: This work was supported by the Robert Wood Johnson Clinical Scholars program, the US Department of Veterans Affairs, grant T32-HP19001 (UCLA Institutional National Research Service Award) from the Health Resources and Services Administration, and funding from the RAND Corporation. Role of the Funder/Sponsor: The funders/sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Additional Contributions: We are grateful to Mary Vaiana, PhD (RAND Corporation), for her careful review of an earlier draft of this manuscript, for which she received compensation. 1. Goitein L. The argument against reimbursing physicians for value. JAMA Intern Med. 2014;174(6):845-846. 2. Institute of Medicine. Development of Methodology for Evaluation of Neighborhood Health Centers. Washington, DC: National Academy of Sciences; 1972. 3. National Quality Forum. Providing a road map for better care. http://www .qualityforum.org/Home.aspx. Accessed June 16, 2014. 4. US Centers for Disease Control and Prevention. Table 7: Twenty leading principal reasons for outpatient department visits: United States, 2010. http: //www.cdc.gov/nchs/data/ahcd/nhamcs_outpatient/2010_opd_web_tables.pdf. Accessed August 4, 2014. 5. US Centers for Disease Control and Prevention. Table 10: Ten leading principal reasons for emergency department visits, by patient age and sex: United States, 2010. http://www.cdc.gov/nchs/data/ahcd/nhamcs_emergency /2010_ed_web_tables.pdf. Accessed August 4, 2014. 522
COMMENT & RESPONSE
Age Cutoffs for Bioprosthetic vs Mechanical Aortic Valve Replacement To the Editor Mr Chiang and colleagues1 reported that patients aged 50 to 69 years who underwent aortic valve replacement had comparable 15-year survival with implantation of a bioprosthesis or a mechanical prosthesis, suggesting that bioprosthetic valves “may be a reasonable choice” in patients aged 50 years or older. We recognize that, in part because of the advent of transcatheter aortic valve implantation and the possibility of placing a transcatheter heart valve in bioprosthetic valves with structural valve deterioration,2 bioprostheses are becoming a more attractive alternative to mechanical prostheses.3 However, additional data are required before lowering the age cutoff for implanting bioprostheses can be justified. Younger patients with a bioprosthetic valve have a higher rate of structural valve deterioration than older patients; in 1 study4 with more than 10 years of follow-up, structural valve deterioration was 6% in patients aged 61 to 70 years and 18% in those aged 51 to 60 years. As a result, the hazard ratio for death after implantation of mechanical vs bioprosthetic valves can vary significantly in different age categories, with the highest mortality benefit using a mechanical valve in younger patients.5 Therefore, the authors should perform a subgroup analysis according to age tertiles to ensure that their findings are consistent across age groups. In the study by Chiang et al,1 patients with a bioprosthesis required higher rates of reoperation, whereas the rate of major bleeding was higher with mechanical valves. However, major bleeding included relatively minor events of hematuria and hemoptysis, as well as more severe events of intracranial hemorrhage, cardiac tamponade, and gastrointestinal hemorrhage. Without further data on the severity of bleeding (number of packed red blood cell transfusions, length of hospitalization, and decrease in hemoglobin level), the effect of bleeding on quality of life remains unclear. In contrast to bleeding events that have a short-term effect on quality of life, the problem of structural valve deterioration is a gradual process affecting quality of life over a longer period. Moreover, multiple reoperations may be required as life expectancy increases, which can be associated with additional risks of complications and reduced quality of life. Lowering the age cutoff to implant bioprosthetic valves therefore seems counterintuitive. For these reasons, randomized trials need to be performed to allow estimation of an individual patient’s riskbenefit ratio based on mortality, reoperation, bleeding, and quality of life. Until then, we do not believe the available evidence supports lowering the age cutoff for bioprosthetic valves. Stuart J. Head, PhD Ruben L. Osnabrugge, MSc A. Pieter Kappetein, MD, PhD Author Affiliations: Department of Cardiothoracic Surgery, Erasmus University Medical Center, Rotterdam, the Netherlands. Corresponding Author: A. Pieter Kappetein, MD, PhD, Department of Cardiothoracic Surgery, Erasmus University Medical Center, PO Box 2040, 3000 CA Rotterdam, the Netherlands ([email protected]).
JAMA February 3, 2015 Volume 313, Number 5 (Reprinted)
Copyright 2015 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a J H Quillen College User on 05/31/2015
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