Does Merit-based Incentive Payment System Performance Differ Based on Orthopaedic Surgeon Gender?
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.
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?
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.
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.
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.
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.
Gill VS
，Lin E
，Holle A
，Haglin JM
，Clarke HD
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Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.
Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided.
(1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS?
Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses.
Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS.
Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments.
Level III, diagnostic study.
Lee CC
，Chen CW
，Yen HK
，Lin YP
，Lai CY
，Wang JL
，Groot OQ
，Janssen SJ
，Schwab JH
，Hsu FM
，Lin WH
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ResearchGate
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钛学术
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