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Did clinicians affiliated with health systems composed of hospitals and multispecialty group practices have better performance ratings than their peers under the Centers for Medicare & Medicaid Services Merit-based Incentive Payment System (MIPS)?
In this cross-sectional study of 636 552 clinicians with MIPS data for 2019 (based on clinician performance in 2017), those with health system affiliations compared with clinicians without such affiliations had a mean MIPS performance score of 79 vs 60 on a scale of 0 to 100, with higher scores intended to represent better performance. This difference was statistically significant.
Clinician affiliation with a health system was associated with significantly better 2019 MIPS performance ratings, but whether this reflects a difference in quality of care is unknown.
Integration of physician practices into health systems composed of hospitals and multispecialty practices is increasing in the era of value-based payment. It is unknown how clinicians who affiliate with such health systems perform under the new mandatory Centers for Medicare & Medicaid Services Merit-based Incentive Payment System (MIPS) relative to their peers.
To assess the relationship between the health system affiliations of clinicians and their performance scores and value-based reimbursement under the 2019 MIPS.
Design, Setting, and Participants
Publicly reported data on 636 552 clinicians working at outpatient clinics across the US were used to assess the association of the affiliation status of clinicians within the 609 health systems with their 2019 final MIPS performance score and value-based reimbursement (both based on clinician performance in 2017), adjusting for clinician, patient, and practice area characteristics.
Health system affiliation vs no affiliation.
Main Outcomes and Measures
The primary outcome was final MIPS performance score (range, 0-100; higher scores intended to represent better performance). The secondary outcome was MIPS payment adjustment, including negative (penalty) payment adjustment, positive payment adjustment, and bonus payment adjustment.
The final sample included 636 552 clinicians (41% female, 83% physicians, 50% in primary care, 17% in rural areas), including 48.6% who were affiliated with a health system. Compared with unaffiliated clinicians, system-affiliated clinicians were significantly more likely to be female (46% vs 37%), primary care physicians (36% vs 30%), and classified as safety net clinicians (12% vs 10%) and significantly less likely to be specialists (44% vs 55%) (P < .001 for each). The mean final MIPS performance score for system-affiliated clinicians was 79.0 vs 60.3 for unaffiliated clinicians (absolute mean difference, 18.7 [95% CI, 18.5 to 18.8]). The percentage receiving a negative (penalty) payment adjustment was 2.8% for system-affiliated clinicians vs 13.7% for unaffiliated clinicians (absolute difference, −10.9% [95% CI, −11.0% to −10.7%]), 97.1% vs 82.6%, respectively, for those receiving a positive payment adjustment (absolute difference, 14.5% [95% CI, 14.3% to 14.6%]), and 73.9% vs 55.1% for those receiving a bonus payment adjustment (absolute difference, 18.9% [95% CI, 18.6% to 19.1%]).
Conclusions and Relevance
Clinician affiliation with a health system was associated with significantly better 2019 MIPS performance scores. Whether this represents differences in quality of care or other factors requires additional research.
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CME Disclosure Statement: Unless noted, all individuals in control of content reported no relevant financial relationships. If applicable, all relevant financial relationships have been mitigated.
Corresponding Author: Kenton J. Johnston, PhD, Department of Health Management and Policy, College for Public Health and Social Justice, St Louis University, 3545 Lafayette Ave, Salus Center, Room 362, St Louis, MO 63104 (email@example.com).
Accepted for Publication: July 6, 2020.
Author Contributions: Dr Johnston 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.
Concept and design: Johnston, Wiemken, Figueroa, Joynt Maddox.
Acquisition, analysis, or interpretation of data: Johnston, Wiemken, Hockenberry, Joynt Maddox.
Drafting of the manuscript: Johnston, Wiemken, Joynt Maddox.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Johnston, Wiemken, Hockenberry.
Administrative, technical, or material support: Johnston, Wiemken.
Supervision: Johnston, Wiemken, Joynt Maddox.
Conflict of Interest Disclosures: Dr Joynt Maddox reported previously performing contract work for the US Department of Health and Human Services. No other disclosures were reported.
Funding/Support: St Louis University purchased and provided access to the data servers and statistical software used to analyze data in this study. Dr Joynt Maddox receives research support from the National Heart, Lung, and Blood Institute (grant R01HL143421) and the National Institute on Aging (grant R01AG060935).
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.
Disclaimer: Dr Joynt Maddox is Associate Editor of JAMA, but she was not involved in any of the decisions regarding review of the manuscript or its acceptance.
Additional Contributions: We thank Ameya Kotwal, BS (St Louis University), for providing assistance on the literature review as part of his paid work as a graduate research assistant.
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