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Oncologist Participation and Performance in the Merit-Based Incentive Payment System
Vishal R Patel1, Thomas B Cwalina2, Arjun Gupta3
1Dell Medical School, The University of Texas at Austin, Austin, TX, USA.
Oncologist participation in the Merit-based Incentive Payment System (MIPS) was lower than other specialties. Higher MIPS scores were linked to alternative payment models, while greater patient complexity was associated with lower scores.
Area of Science:
- Health Services Research
- Oncology
- Health Policy
Background:
- The Merit-based Incentive Payment System (MIPS) is a value-based payment model by the Centers for Medicare & Medicaid Services (CMS).
- MIPS aims to enhance healthcare value through performance-based adjustments to Medicare reimbursements.
- Understanding oncologist participation and performance in MIPS is crucial for optimizing value-based care initiatives.
Purpose of the Study:
- To examine the participation rates of oncologists in the 2019 MIPS.
- To analyze the factors influencing MIPS performance among oncologists.
- To identify areas for improvement in MIPS engagement and scoring for oncology practices.
Main Methods:
- A cross-sectional study design was employed.
- Data on oncologist participation and performance in the 2019 MIPS were analyzed.
- Statistical adjustments were made for practice characteristics and patient complexity.
Main Results:
- Oncologist participation in MIPS was 86%, lower than the 97% all-specialty participation rate.
- Oncologists utilizing alternative payment models (APMs) achieved higher MIPS scores (mean 91) compared to individual filers (mean 77.6).
- Increased patient complexity was associated with slightly lower MIPS scores, suggesting a need for improved risk adjustment.
Conclusions:
- Oncologist engagement in MIPS requires attention, particularly regarding participation rates.
- Alternative payment models may facilitate better MIPS performance, highlighting the role of organizational resources.
- CMS should consider refining risk-adjustment methodologies to better account for patient complexity in MIPS.
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