Does Merit-based Incentive Payment System Performance Differ Based on Orthopaedic Surgeon Gender?

BACKGROUND

Value-based care payment and delivery models such as the recently implemented Merit-based Incentive Payment System (MIPS) aim to both provide better care for patients and reduce costs of care. Gender disparities across orthopaedic surgery, encompassing reimbursement, industry payments, referrals, and patient perception, have been thoroughly studied over the years, with numerous disparities identified. However, differences in MIPS performance based on orthopaedic surgeon gender have not been comprehensively evaluated.

QUESTIONS/PURPOSES: After controlling for potentially confounding variables such as experience, geography, group size, and Medicare beneficiary characteristics, does MIPS performance differ between men and women orthopaedic surgeons?

METHODS

The Medicare Physician and Other Practitioners and the Physician Compare databases were queried for years 2017, the first year MIPS was incorporated, and 2021, the most recent year with MIPS data published, to identify all physicians with a self-reported specialty of orthopaedic surgery. Together, these databases include all physicians who submitted at least 11 Medicare claims each year. Physician gender, US census region, years in practice, group practice size, billing practices, and patient demographic characteristics were collected for each surgeon. The MIPS Performance database was used to extract an overall MIPS performance score for each surgeon for each year. Payment adjustments, which are determined based on overall MIPS performance score, were derived for each surgeon based on the thresholds published by the Centers for Medicare & Medicaid Services. Payment adjustments include a negative adjustment, neutral adjustment, positive adjustment, or exceptional performance bonus and are associated with different thresholds each year. Statistical differences based on surgeon gender were assessed utilizing chi-square tests for categorical data, Student t-test for parametric continuous data, and Wilcoxon signed-rank test for nonparametric continuous data. Univariable and multivariable analyses were performed to analyze the relationship between surgeon gender and MIPS performance.

RESULTS

After controlling for other patient and surgeon variables, woman gender was associated with a slightly increased MIPS performance score in 2021 (β 1.5 [95% confidence interval (CI) 0.02 to 3.00]; p = 0.047). However, this finding was statistically fragile, with the lower bound 95% CI being very close to the line of no difference. No association between surgeon gender and MIPS performance score was found in 2017 (β 2.2 [95% CI -0.5 to 4.9]; p = 0.11). Additionally, no relationship was found between gender and receiving either an exceptional performance MIPS bonus or a MIPS penalty in either year.

CONCLUSION

Women orthopaedic surgeons scored slightly higher on the MIPS in 2021, after controlling for surgeon and patient variables, despite providing care for a higher percentage of dual Medicare-Medicaid eligible patients and more medically complex patients. However, this finding was statistically fragile, with a small effect size, a 95% CI close to 0, and no consistent association in MIPS performance in 2017. Additionally, with no differences in MIPS performance bonuses or penalties, the clinical monetary impact of this difference may be minimal.

CLINICAL RELEVANCE

The observed association between surgeon gender and MIPS performance scores in 2021, with women orthopaedic surgeons achieving slightly higher scores, raises interesting questions about potential differences in practice behaviors, communication styles, care quality, or other unmeasured variables. These findings may reflect true differences in how care is delivered or documented as scored by the MIPS. However, given the small effect size, statistical fragility, and inconsistency across years, there is a chance that this finding may be spurious. That being so, future research should aim to validate or refute these findings by examining a broader range of variables including documentation practices, practice behaviors, institutional differences, potential systemic biases in scoring methodologies, and patient outcomes. Understanding whether these differences are true is important to ensure that performance metrics like MIPS accurately and equitably reflect care quality.