Association of Practice-Level Social and Medical Risk With Performance in the Medicare Physician Value-Based Payment Modifier Program

Chen, Lena M.; Epstein, Arnold M.; Orav, E. John; Filice, Clara E.; Samson, Lok Wong; Maddox, Karen E. Joynt

doi:10.1001/jama.2017.9643

Cited by 67 publications

(72 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Regardless of on which side of the debate one sits, it is inarguable that this decision has real consequences: Current policies, not only in the HRRP but also other value-based payment programs in Medicare, are disproportionately penalizing providers that serve the poor and disabled. 28,[37][38][39][40][41][42][43][44] Our findings are consistent with prior studies demonstrating a relationship between claims-based measures of social risk and…”

Section: Discussionsupporting

confidence: 90%

“…In fact, even with adjustment, safety‐net hospitals had somewhat worse performance than wealthier hospitals; whether this represents true differences in the quality of care delivered by each hospital, or residual confounding by factors beyond hospitals’ control, is unknown. Regardless of on which side of the debate one sits, it is inarguable that this decision has real consequences: Current policies, not only in the HRRP but also other value‐based payment programs in Medicare, are disproportionately penalizing providers that serve the poor and disabled …”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Adjusting for social risk factors impacts performance and penalties in the hospital readmissions reduction program

Maddox

Reidhead

et al. 2019

Health Services Research

Self Cite

165

118

View full text Add to dashboard Cite

Objective Medicare's Hospital Readmissions Reduction Program (HRRP) does not account for social risk factors in risk adjustment, and this may lead the program to unfairly penalize safety‐net hospitals. Our objective was to determine the impact of adjusting for social risk factors on HRRP penalties. Study Design Retrospective cohort study. Data Sources/Study Setting Claims data for 2 952 605 fee‐for‐service Medicare beneficiaries with acute myocardial infarction (AMI), congestive heart failure (CHF) or pneumonia from December 2012 to November 2015. Principal Findings Poverty, disability, housing instability, residence in a disadvantaged neighborhood, and hospital population from a disadvantaged neighborhood were associated with higher readmission rates. Under current program specifications, safety‐net hospitals had higher readmission ratios (AMI, 1.020 vs 0.986 for the most affluent hospitals; pneumonia, 1.031 vs 0.984; and CHF, 1.037 vs 0.977). Adding social factors to risk adjustment cut these differences in half. Over half the safety‐net hospitals saw their penalty decline; 4‐7.5 percent went from having a penalty to having no penalty. These changes translated into a $17 million reduction in penalties to safety‐net hospitals. Conclusions Accounting for social risk can have a major financial impact on safety‐net hospitals. Adjustment for these factors could reduce negative unintended consequences of the HRRP.

show abstract

Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Adjusting for social risk factors impacts performance and penalties in the hospital readmissions reduction program

Maddox

Reidhead

et al. 2019

Health Services Research

Self Cite

165

118

View full text Add to dashboard Cite

show abstract

“…2 Before 2017, star ratings were not adjusted for any enrollee characteristics, 3 though plans serving larger proportions of sociodemographically disadvantaged enrollees might have had lower performance on these measures. 4,5 …”

mentioning

confidence: 99%

Impact Of Risk Adjustment For Socioeconomic Status On Medicare Advantage Plan Quality Rankings

et al. 2018

View full text Add to dashboard Cite

Sociodemographically disadvantaged patients have worse outcomes on some quality measures that inform Medicare Advantage plan ratings. Performance measurement that does not adjust for sociodemographic factors may penalize plans that disproportionately serve disadvantaged populations. We assessed the impact of adjusting for socioeconomic and demographic factors (sex, race/ethnicity, dual eligibility, disability, rurality, and neighborhood disadvantage) on Medicare Advantage plan rankings for blood pressure, diabetes, and cholesterol control. After adjustment, 20.3 percent, 19.5 percent, and 11.4 percent of Medicare Advantage plans improved by one or more quintiles in rank on the diabetes, cholesterol, and blood pressure measures, respectively. Plans that improved in ranking after adjustment enrolled higher proportions of disadvantaged enrollees. Adjusting quality measures for socioeconomic factors is important for equitable payment and quality reporting. Our study suggests that plans serving disadvantaged populations would have improved relative rankings for three important outcome measures if socioeconomic factors were included in risk-adjustment models.

show abstract

“…We used monthly Medicare‐Medicaid dual eligibility codes in linked administrative data to identify beneficiaries receiving ≥1 month of full Medicaid in the study year, whom we defined as dual enrollees (Appendix ). We focused on Medicare beneficiaries receiving full Medicaid, since most risk‐adjustment methods treat full Medicaid enrollment as a marker of social and clinical risk . Moreover, full‐benefit duals account for 72 percent of Medicaid enrollment in the Medicare population and a disproportionate share of Medicare spending .…”

Section: Methodsmentioning

confidence: 99%

“…We focused on Medicare beneficiaries receiving full Medicaid, since most risk-adjustment methods treat full Medicaid enrollment as a marker of social and clinical risk. 8,[25][26][27][28] Moreover, full-benefit duals account for 72 percent of Medicaid enrollment in the Medicare population and a disproportionate share of Medicare spending. 12 We measured income relative to the FPL using…”

Section: Analysis Populationmentioning

confidence: 99%

State variation in the characteristics of Medicare‐Medicaid dual enrollees: Implications for risk adjustment

Roberts

Mellor

McInerney

et al. 2019

Health Services Research

View full text Add to dashboard Cite

Objective To examine between‐state differences in the socioeconomic and health characteristics of Medicare beneficiaries dually enrolled in Medicaid, focusing on characteristics not observable to or used by policy makers for risk adjustment. Data Source 2010‐2013 Medicare Current Beneficiary Survey. Study Design Retrospective analyses of survey‐reported health and socioeconomic status (SES) measures among low‐income Medicare beneficiaries and low‐income dual enrollees. We used hierarchical linear regression models with state random effects to estimate the between‐state variation in respondent characteristics and linear models to compare the characteristics of dual enrollees by state Medicaid policies. Principal Findings Between‐state differences in health and socioeconomic risk among low‐income Medicare beneficiaries, as measured by the coefficient of variation, ranged from 17.5 percent for an index of socioeconomic risk to 20.3 percent for an index of health risk. Between‐state differences were comparable among the subset of low‐income beneficiaries dually enrolled in Medicare and Medicaid. Dual enrollees with incomes below the Federal Poverty Level were in better health and had higher SES in states that offered Medicaid to individuals with relatively higher incomes. Duals' average incomes were higher in states with Medically Needy programs. Conclusions Characteristics of dual enrollees differ substantially across states, reflecting differences in states' low‐income Medicare populations and Medicaid policies. Risk‐adjustment methods using dual enrollment to proxy for poor health and low SES should account for this state‐level heterogeneity.

show abstract

Association of Practice-Level Social and Medical Risk With Performance in the Medicare Physician Value-Based Payment Modifier Program

Abstract: During the first year of the Medicare Physician Value-Based Payment Modifier Program, physician practices that served more socially high-risk patients had lower quality and lower costs, and practices that served more medically high-risk patients had lower quality and higher costs.

Cited by 67 publications

References 34 publications

Adjusting for social risk factors impacts performance and penalties in the hospital readmissions reduction program

Adjusting for social risk factors impacts performance and penalties in the hospital readmissions reduction program

Impact Of Risk Adjustment For Socioeconomic Status On Medicare Advantage Plan Quality Rankings

State variation in the characteristics of Medicare‐Medicaid dual enrollees: Implications for risk adjustment

Contact Info

Product

Resources

About