Dhruv Khullar1,2,3, William L Schpero1, Amelia M Bond1, Yuting Qian1, Lawrence P Casalino1. 1. Division of Health Policy and Economics, Department of Population Health Sciences, Weill Cornell Medical College, New York, New York. 2. Division of General Internal Medicine, Department of Medicine, Weill Cornell Medical College, New York, New York. 3. NewYork-Presbyterian Hospital, New York, New York.
Abstract
Importance: The US Merit-based Incentive Payment System (MIPS) is a major Medicare value-based payment program aimed at improving quality and reducing costs. Little is known about how physicians' performance varies by social risk of their patients. Objective: To determine the relationship between patient social risk and physicians' scores in the first year of MIPS. Design, Setting, and Participants: Cross-sectional study of physicians participating in MIPS in 2017. Exposures: Physicians in the highest quintile of proportion of dually eligible patients served; physicians in the 3 middle quintiles; and physicians in the lowest quintile. Main Outcomes and Measures: The primary outcome was the 2017 composite MIPS score (range, 0-100; higher scores indicate better performance). Payment rates were adjusted -4% to 4% based on scores. Results: The final sample included 284 544 physicians (76.1% men, 60.1% with ≥20 years in practice, 11.9% in rural location, 26.8% hospital-based, and 24.6% in primary care). The mean composite MIPS score was 73.3. Physicians in the highest risk quintile cared for 52.0% of dually eligible patients; those in the 3 middle risk quintiles, 21.8%; and those in the lowest risk quintile, 6.6%. After adjusting for medical complexity, the mean MIPS score for physicians in the highest risk quintile (64.7) was lower relative to scores for physicians in the middle 3 (75.4) and lowest (75.9) risk quintiles (difference for highest vs middle 3, -10.7 [95% CI, -11.0 to -10.4]; highest vs lowest, -11.2 [95% CI, -11.6 to -10.8]; P < .001). This relationship was found across specialties except psychiatry. Compared with physicians in the lowest risk quintile, physicians in the highest risk quintile were more likely to work in rural areas (12.7% vs 6.4%; difference, 6.3 percentage points [95% CI, 6.0 to 6.7]; P < .001) but less likely to care for more than 1000 Medicare beneficiaries (9.4% vs 17.8%; difference, -8.3 percentage points [95% CI, -8.7 to -8.0]; P < .001) or to have more than 20 years in practice (56.7% vs 70.6%; difference, -13.9 percentage points [95% CI, -14.4 to -13.3]; P < .001). For physicians in the highest risk quintile, several characteristics were associated with higher MIPS scores, including practicing in a larger group (mean score, 82.4 for more than 50 physicians vs 46.1 for 1-5 physicians; difference, 36.2 [95% CI, 35.3 to 37.2]; P < .001) and reporting through an alternative payment model (mean score, 79.5 for alternative payment model vs 59.9 for reporting as individual; difference, 19.7 [95% CI, 18.9 to 20.4]; P < .001). Conclusions and Relevance: In this cross-sectional analysis of physicians who participated in the first year of the Medicare MIPS program, physicians with the highest proportion of patients dually eligible for Medicare and Medicaid had significantly lower MIPS scores compared with other physicians. Further research is needed to understand the reasons underlying the differences in physician MIPS scores by levels of patient social risk.
Importance: The US Merit-based Incentive Payment System (MIPS) is a major Medicare value-based payment program aimed at improving quality and reducing costs. Little is known about how physicians' performance varies by social risk of their patients. Objective: To determine the relationship between patient social risk and physicians' scores in the first year of MIPS. Design, Setting, and Participants: Cross-sectional study of physicians participating in MIPS in 2017. Exposures: Physicians in the highest quintile of proportion of dually eligible patients served; physicians in the 3 middle quintiles; and physicians in the lowest quintile. Main Outcomes and Measures: The primary outcome was the 2017 composite MIPS score (range, 0-100; higher scores indicate better performance). Payment rates were adjusted -4% to 4% based on scores. Results: The final sample included 284 544 physicians (76.1% men, 60.1% with ≥20 years in practice, 11.9% in rural location, 26.8% hospital-based, and 24.6% in primary care). The mean composite MIPS score was 73.3. Physicians in the highest risk quintile cared for 52.0% of dually eligible patients; those in the 3 middle risk quintiles, 21.8%; and those in the lowest risk quintile, 6.6%. After adjusting for medical complexity, the mean MIPS score for physicians in the highest risk quintile (64.7) was lower relative to scores for physicians in the middle 3 (75.4) and lowest (75.9) risk quintiles (difference for highest vs middle 3, -10.7 [95% CI, -11.0 to -10.4]; highest vs lowest, -11.2 [95% CI, -11.6 to -10.8]; P < .001). This relationship was found across specialties except psychiatry. Compared with physicians in the lowest risk quintile, physicians in the highest risk quintile were more likely to work in rural areas (12.7% vs 6.4%; difference, 6.3 percentage points [95% CI, 6.0 to 6.7]; P < .001) but less likely to care for more than 1000 Medicare beneficiaries (9.4% vs 17.8%; difference, -8.3 percentage points [95% CI, -8.7 to -8.0]; P < .001) or to have more than 20 years in practice (56.7% vs 70.6%; difference, -13.9 percentage points [95% CI, -14.4 to -13.3]; P < .001). For physicians in the highest risk quintile, several characteristics were associated with higher MIPS scores, including practicing in a larger group (mean score, 82.4 for more than 50 physicians vs 46.1 for 1-5 physicians; difference, 36.2 [95% CI, 35.3 to 37.2]; P < .001) and reporting through an alternative payment model (mean score, 79.5 for alternative payment model vs 59.9 for reporting as individual; difference, 19.7 [95% CI, 18.9 to 20.4]; P < .001). Conclusions and Relevance: In this cross-sectional analysis of physicians who participated in the first year of the Medicare MIPS program, physicians with the highest proportion of patients dually eligible for Medicare and Medicaid had significantly lower MIPS scores compared with other physicians. Further research is needed to understand the reasons underlying the differences in physician MIPS scores by levels of patient social risk.
Authors: Alyna T Chien; Kristen Wroblewski; Cheryl Damberg; Thomas R Williams; Dolores Yanagihara; Yelena Yakunina; Lawrence P Casalino Journal: J Gen Intern Med Date: 2011-12-13 Impact factor: 5.128
Authors: Karen E Joynt; Nancy De Lew; Steven H Sheingold; Patrick H Conway; Kate Goodrich; Arnold M Epstein Journal: N Engl J Med Date: 2016-12-28 Impact factor: 91.245
Authors: Grace M Lee; Ken Kleinman; Stephen B Soumerai; Alison Tse; David Cole; Scott K Fridkin; Teresa Horan; Richard Platt; Charlene Gay; William Kassler; Donald A Goldmann; John Jernigan; Ashish K Jha Journal: N Engl J Med Date: 2012-10-11 Impact factor: 91.245
Authors: Cameron J Gettel; Christopher R Han; Maureen E Canavan; Susannah M Bernheim; Elizabeth E Drye; Reena Duseja; Arjun K Venkatesh Journal: Med Care Date: 2022-02-01 Impact factor: 2.983
Authors: Anders Chen; Arnab Ghosh; Kendrick B Gwynn; Celeste Newby; Tracey L Henry; Jackson Pearce; Marshall Fleurant; Stacie Schmidt; Jennifer Bracey; Elizabeth A Jacobs Journal: J Gen Intern Med Date: 2022-06-29 Impact factor: 6.473
Authors: Thomas B Cwalina; Tarun K Jella; Alexander J Acuña; Linsen T Samuel; Atul F Kamath Journal: Clin Orthop Relat Res Date: 2022-01-01 Impact factor: 4.755
Authors: Frederick Isasi; Mary D Naylor; David Skorton; David C Grabowski; Sandra Hernández; Valerie Montgomery Rice Journal: NAM Perspect Date: 2021-11-29
Authors: Dhruv Khullar; Amelia M Bond; Yuting Qian; Eloise O'Donnell; David N Gans; Lawrence P Casalino Journal: J Gen Intern Med Date: 2021-04-09 Impact factor: 5.128