Opinion
VIEWPOINT
Ashish K. Jha, MD, MPH Department of Health Policy and Management, Harvard School of Public Health, Boston, Massachusetts; and Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts. Alan M. Zaslavsky, PhD Department of Healthcare Policy, Harvard Medical School, Boston, Massachusetts.
Author Reading at jama.com
Corresponding Author: Ashish K. Jha, MD, MPH, Department of Health Policy and Management, Harvard School of Public Health, 677 Huntington Ave, Boston, MA 02115 ([email protected] .edu).
Quality Reporting That Addresses Disparities in Health Care More than a decade has passed since the landmark Institute of Medicine report Unequal Treatment documented the sizeable and pervasive disparities that affect the US health care system.1 Yet there has been little evidence of progress toward eliminating, or even reducing, these inequities in care. Furthermore, there is increasing concern that existing policy efforts designed to improve quality may, in fact, worsen disparities in care. Most recently, the Medicare pay-for-performance effort with the largest financial penalties, the Hospital Readmissions Reduction Program, was found to disproportionately penalize safety-net facilities that primarily care for disadvantaged and poor populations.2 Findings such as these have prompted national discussions about the possibility of adjusting quality-performance scores for the socioeconomic status (SES) of patient populations.3 In principle, adjustment serves to distinguish quality of patient care from the effects of patient characteristics that are not under the control of the clinician. Using statistical methods such as regression or weighting, adjustment
income may suggest tacit acceptance of a lower quality of care for socially disadvantaged patients. Adjustment may also serve to excuse those who provide lower-quality care to these populations, making it difficult to identify disparitiesorholdcliniciansandhealthcareorganizationsaccountable for rectifying them.
Practical Implications of Adjusting for SES
Although this debate is timely and relevant, it needs a more nuanced approach that considers the different implications of within- and between-unit quality disparities, as well as the variety of purposes that performance scores are asked to serve. To illustrate the practical implications of adjustment, the following example demonstrates how accounting for SES (dichotomized as poor, nonpoor) affects performance scores on the delivery of an essential process-of-care measure in 2 hypothetical scenarios (Table). In these scenarios, hospital A (a safety-net hospital) serves a higher proportion of poor patients (50%) than hospital B (5%). The adjustment is performed by calculating a weighted mean of performance rates for poor and Conversely, critics of this position argue nonpoor patients corresponding with the national proportions, 20% poor and that adjustment of SES codifies a soft 80% nonpoor, eligible for the measure bigotry of low expectations. Adjusting (direct standardization). In scenario 1, there is no perforfor patient characteristics such as mance difference between poor and nonincome may suggest tacit acceptance of poorpatientsateitherhospital,andasarea lower quality of care for socially sult, adjustment has no effect on final hospital scores. Put differently, there is no disadvantaged patients. within-hospital disparity between poor and nonpoor patients. However, poor paaims to estimate and compare the performance of health tients disproportionately obtain care at hospital A, which careunits(hospitals,healthplans,physiciangroups)asthey has lower quality performance than hospital B for both pawould be if every unit served patients with the same mix tient groups. Thus, the inequity in care is entirely due to of characteristics. Adjustment for patient characteristics differences in overall performance between the 2 hospiwith clear clinical consequences, such as age and comor- tals. In scenario 2, the 2 hospitals deliver the same quality bidity, is not controversial; however, adjustment for social of care to their poor patients (60%) and their nonpoor pacharacteristics is. tients(80%),whichreflectsawithin-hospitaldisparity.The AdvocatesofadjustmentforSEShavearguedthatcar- unadjusted gap is driven by the larger proportion of poor ing for poor patients may be more challenging due to the patients in hospital A. Adjustment in this scenario results numerous nonclinical barriers to accessing care, fewer re- inidenticalperformancescoresbecausethehospitalshave sourcesfordiseasemanagement,andlowerlevelsofsocial identical performance for both their poor and their nonsupportforlow-incomeindividuals.Furthermore,thetrain- poor patients. ing and socialization of medical professionals might not These scenarios illustrate how disparities can arise equip them to provide equitable, high-quality care to poor from both within- and between-hospital differences. In andunderservedpopulations.Therefore,thesamelevelof neither case does reporting of either unadjusted or adclinician effort and expertise may generate lower-quality justed performance scores reveal, explain, or conceal disscoresforthesepatients.Conversely,criticsofthisposition parities in the absence of additional information. For exargue that adjustment of SES codifies a soft bigotry of low ample, unadjusted scores for hospital A are the same in expectations. Adjusting for patient characteristics such as both scenarios; however, the sources of disparities, and
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225
Opinion Viewpoint
Table. Hypothetical Scenarios Illustrating the Effects of Accounting for Socioeconomic Status in Quality-Performance Measures Hospital Aa
Hospital Ba Stratified Results, % of Patients
Stratified Results, % of Patients
b
Score Unadjusted
Adjusted
70
70
70
76
Scoreb
Difference in Score, %
Unadjusted
Adjusted
Unadjusted
Adjusted
80
80
10
10
79
76
9
0
Scenario 1 Poor
70
Nonpoor
70
Poor
80
Nonpoor
80
Poor
60
Nonpoor
80
Scenario 2
a
Poor
60
Nonpoor
80
Hospital A is a safety-net facility, treating 50% poor patients; only 5% of patients treated at hospital B are poor.
Values represent performance measures on a scale of 0 to 100.
hence the implications for quality improvement, are quite different. This within vs between distinction does not determine whether differences in care are clinically reasonable or socially acceptable but it does help explain why such differences may occur. This distinction also helps in understanding which disparities can be identified from overall hospital scores and which can only be identified by individual-level analysis of associations of measures with important patient characteristics such as SES.
its actual patient population. If quality is suboptimal, the hospital should take steps toward quality improvement regardless of whether performance deficits are attributable to patient demographics. However, unadjusted results are not enough to enable hospitals to target quality-improvement efforts. Supplementing unadjusted measures with stratified results would provide the information necessary to target improvement efforts toward patients experiencing the worst outcomes.
Proposed Guideline for SES Adjustment in Quality Reporting
Determining Financial Incentives for Performance Improvement
The decision to adjust for SES is situation dependent and may be different for 3 key uses of performance scores: informing patient choice, motivatingqualityimprovement,anddeterminingfinancialincentives. These recommendations are based not only on the immediate use of data for relevant stakeholders but also on the need to inform future quality-improvement activities and mitigate further disparities.
When determining financial incentives for performance improvement, measures should be adjusted to minimize the potential for penalizing or rewarding hospitals based on their patient population. The central goal of financial incentives is to reward hospitals for providing better care, not for having healthier or wealthier patients. Adjustment limits the potential for incentives to systematically penalize hospitals with larger shares of disadvantaged patients, thereby further undermining their care.
Informing Patient Choice
To inform patient choice, stratified performance data are ideal because they support comparison of likely experiences of a particular patient. However, given the practical limitations, such as small sample sizes and the potential for information overload, adjusted summary measures are reasonable alternatives. Not only do they offer concise presentation and accessibility for patients, they also predict the relative quality that would be experienced by the same patient at different institutions. In these instances, stratified data might best be presented as detailed supplementary information to public reports. Motivating Quality Improvement
To motivate quality improvement, unadjusted measures may be best suited because they reflect each hospital’s performance based on ARTICLE INFORMATION Conflict of Interest Disclosures: Both authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. REFERENCES 1. Institute of Medicine. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC: National Academies Press; 2003.
226
b
Conclusions Health care disparities have proven to be persistent and current efforts at quality improvement may worsen these inequities. Recognizing the role of patient SES is immensely important in ensuring that hospitals are not only aware of their performance among different patient groups, but are also able to respond adequately to calls for improvement. Stratified, unadjusted, and adjusted measures each have a role in relation to the various objectives of performance measurement. Appropriate quality reporting, combined with welldesigned incentives, can drive improvements in care without penalizing hospitals that disproportionately care for the poor. If the approach is nuanced and flexible, progress can be made toward ensuring high-quality care for all patients.
2. Joynt KE, Jha AK. Characteristics of hospitals receiving penalties under the Hospital Readmissions Reduction Program. JAMA. 2013;309 (4):342-343. 3. National Quality Forum. Risk adjustment for socioeconomic status or other sociodemographic factors—draft technical report for review, March 18, 2014. National Quality Forum website. http://www .qualityforum.org/Risk_Adjustment_SES.aspx. April 30, 2014.
4. Medicare Payment Advisory Committee. Chapter 4: Refining the hospital readmissions reduction program. In: Medicare Payment Advisory Committee. Report to the Congress: Medicare and the Health Care Delivery System. Washington, DC: MPAC; 2013:91-116.
JAMA July 16, 2014 Volume 312, Number 3
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a Eastern Kentucky University User on 05/23/2015
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VIEWPOINT
Ashish K. Jha, MD, MPH Department of Health Policy and Management, Harvard School of Public Health, Boston, Massachusetts; and Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts. Alan M. Zaslavsky, PhD Department of Healthcare Policy, Harvard Medical School, Boston, Massachusetts.
Author Reading at jama.com
Corresponding Author: Ashish K. Jha, MD, MPH, Department of Health Policy and Management, Harvard School of Public Health, 677 Huntington Ave, Boston, MA 02115 ([email protected] .edu).
Quality Reporting That Addresses Disparities in Health Care More than a decade has passed since the landmark Institute of Medicine report Unequal Treatment documented the sizeable and pervasive disparities that affect the US health care system.1 Yet there has been little evidence of progress toward eliminating, or even reducing, these inequities in care. Furthermore, there is increasing concern that existing policy efforts designed to improve quality may, in fact, worsen disparities in care. Most recently, the Medicare pay-for-performance effort with the largest financial penalties, the Hospital Readmissions Reduction Program, was found to disproportionately penalize safety-net facilities that primarily care for disadvantaged and poor populations.2 Findings such as these have prompted national discussions about the possibility of adjusting quality-performance scores for the socioeconomic status (SES) of patient populations.3 In principle, adjustment serves to distinguish quality of patient care from the effects of patient characteristics that are not under the control of the clinician. Using statistical methods such as regression or weighting, adjustment
income may suggest tacit acceptance of a lower quality of care for socially disadvantaged patients. Adjustment may also serve to excuse those who provide lower-quality care to these populations, making it difficult to identify disparitiesorholdcliniciansandhealthcareorganizationsaccountable for rectifying them.
Practical Implications of Adjusting for SES
Although this debate is timely and relevant, it needs a more nuanced approach that considers the different implications of within- and between-unit quality disparities, as well as the variety of purposes that performance scores are asked to serve. To illustrate the practical implications of adjustment, the following example demonstrates how accounting for SES (dichotomized as poor, nonpoor) affects performance scores on the delivery of an essential process-of-care measure in 2 hypothetical scenarios (Table). In these scenarios, hospital A (a safety-net hospital) serves a higher proportion of poor patients (50%) than hospital B (5%). The adjustment is performed by calculating a weighted mean of performance rates for poor and Conversely, critics of this position argue nonpoor patients corresponding with the national proportions, 20% poor and that adjustment of SES codifies a soft 80% nonpoor, eligible for the measure bigotry of low expectations. Adjusting (direct standardization). In scenario 1, there is no perforfor patient characteristics such as mance difference between poor and nonincome may suggest tacit acceptance of poorpatientsateitherhospital,andasarea lower quality of care for socially sult, adjustment has no effect on final hospital scores. Put differently, there is no disadvantaged patients. within-hospital disparity between poor and nonpoor patients. However, poor paaims to estimate and compare the performance of health tients disproportionately obtain care at hospital A, which careunits(hospitals,healthplans,physiciangroups)asthey has lower quality performance than hospital B for both pawould be if every unit served patients with the same mix tient groups. Thus, the inequity in care is entirely due to of characteristics. Adjustment for patient characteristics differences in overall performance between the 2 hospiwith clear clinical consequences, such as age and comor- tals. In scenario 2, the 2 hospitals deliver the same quality bidity, is not controversial; however, adjustment for social of care to their poor patients (60%) and their nonpoor pacharacteristics is. tients(80%),whichreflectsawithin-hospitaldisparity.The AdvocatesofadjustmentforSEShavearguedthatcar- unadjusted gap is driven by the larger proportion of poor ing for poor patients may be more challenging due to the patients in hospital A. Adjustment in this scenario results numerous nonclinical barriers to accessing care, fewer re- inidenticalperformancescoresbecausethehospitalshave sourcesfordiseasemanagement,andlowerlevelsofsocial identical performance for both their poor and their nonsupportforlow-incomeindividuals.Furthermore,thetrain- poor patients. ing and socialization of medical professionals might not These scenarios illustrate how disparities can arise equip them to provide equitable, high-quality care to poor from both within- and between-hospital differences. In andunderservedpopulations.Therefore,thesamelevelof neither case does reporting of either unadjusted or adclinician effort and expertise may generate lower-quality justed performance scores reveal, explain, or conceal disscoresforthesepatients.Conversely,criticsofthisposition parities in the absence of additional information. For exargue that adjustment of SES codifies a soft bigotry of low ample, unadjusted scores for hospital A are the same in expectations. Adjusting for patient characteristics such as both scenarios; however, the sources of disparities, and
jama.com
JAMA July 16, 2014 Volume 312, Number 3
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a Eastern Kentucky University User on 05/23/2015
225
Opinion Viewpoint
Table. Hypothetical Scenarios Illustrating the Effects of Accounting for Socioeconomic Status in Quality-Performance Measures Hospital Aa
Hospital Ba Stratified Results, % of Patients
Stratified Results, % of Patients
b
Score Unadjusted
Adjusted
70
70
70
76
Scoreb
Difference in Score, %
Unadjusted
Adjusted
Unadjusted
Adjusted
80
80
10
10
79
76
9
0
Scenario 1 Poor
70
Nonpoor
70
Poor
80
Nonpoor
80
Poor
60
Nonpoor
80
Scenario 2
a
Poor
60
Nonpoor
80
Hospital A is a safety-net facility, treating 50% poor patients; only 5% of patients treated at hospital B are poor.
Values represent performance measures on a scale of 0 to 100.
hence the implications for quality improvement, are quite different. This within vs between distinction does not determine whether differences in care are clinically reasonable or socially acceptable but it does help explain why such differences may occur. This distinction also helps in understanding which disparities can be identified from overall hospital scores and which can only be identified by individual-level analysis of associations of measures with important patient characteristics such as SES.
its actual patient population. If quality is suboptimal, the hospital should take steps toward quality improvement regardless of whether performance deficits are attributable to patient demographics. However, unadjusted results are not enough to enable hospitals to target quality-improvement efforts. Supplementing unadjusted measures with stratified results would provide the information necessary to target improvement efforts toward patients experiencing the worst outcomes.
Proposed Guideline for SES Adjustment in Quality Reporting
Determining Financial Incentives for Performance Improvement
The decision to adjust for SES is situation dependent and may be different for 3 key uses of performance scores: informing patient choice, motivatingqualityimprovement,anddeterminingfinancialincentives. These recommendations are based not only on the immediate use of data for relevant stakeholders but also on the need to inform future quality-improvement activities and mitigate further disparities.
When determining financial incentives for performance improvement, measures should be adjusted to minimize the potential for penalizing or rewarding hospitals based on their patient population. The central goal of financial incentives is to reward hospitals for providing better care, not for having healthier or wealthier patients. Adjustment limits the potential for incentives to systematically penalize hospitals with larger shares of disadvantaged patients, thereby further undermining their care.
Informing Patient Choice
To inform patient choice, stratified performance data are ideal because they support comparison of likely experiences of a particular patient. However, given the practical limitations, such as small sample sizes and the potential for information overload, adjusted summary measures are reasonable alternatives. Not only do they offer concise presentation and accessibility for patients, they also predict the relative quality that would be experienced by the same patient at different institutions. In these instances, stratified data might best be presented as detailed supplementary information to public reports. Motivating Quality Improvement
To motivate quality improvement, unadjusted measures may be best suited because they reflect each hospital’s performance based on ARTICLE INFORMATION Conflict of Interest Disclosures: Both authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. REFERENCES 1. Institute of Medicine. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC: National Academies Press; 2003.
226
b
Conclusions Health care disparities have proven to be persistent and current efforts at quality improvement may worsen these inequities. Recognizing the role of patient SES is immensely important in ensuring that hospitals are not only aware of their performance among different patient groups, but are also able to respond adequately to calls for improvement. Stratified, unadjusted, and adjusted measures each have a role in relation to the various objectives of performance measurement. Appropriate quality reporting, combined with welldesigned incentives, can drive improvements in care without penalizing hospitals that disproportionately care for the poor. If the approach is nuanced and flexible, progress can be made toward ensuring high-quality care for all patients.
2. Joynt KE, Jha AK. Characteristics of hospitals receiving penalties under the Hospital Readmissions Reduction Program. JAMA. 2013;309 (4):342-343. 3. National Quality Forum. Risk adjustment for socioeconomic status or other sociodemographic factors—draft technical report for review, March 18, 2014. National Quality Forum website. http://www .qualityforum.org/Risk_Adjustment_SES.aspx. April 30, 2014.
4. Medicare Payment Advisory Committee. Chapter 4: Refining the hospital readmissions reduction program. In: Medicare Payment Advisory Committee. Report to the Congress: Medicare and the Health Care Delivery System. Washington, DC: MPAC; 2013:91-116.
JAMA July 16, 2014 Volume 312, Number 3
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a Eastern Kentucky University User on 05/23/2015
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