Maximizing Performance in Medicare’s Merit Based Incentive Payment System: A Financial Model to Optimize Health Information Technology Resource Allocation
Document Type
Journal Article
Publication Date
1-1-2020
Journal
Inquiry (United States)
Volume
57
DOI
10.1177/0046958020971237
Keywords
health information technology; Medicare; MIPS; Promoting Interoperability; Quality Payment Programs
Abstract
© The Author(s) 2020. Participation in the Medicare Quality Payment Program’s Merit Based Incentive Payment System (MIPS) has forced many healthcare administrators to strategize how to achieve success under value-based payment systems. A financial model was constructed to determine the marginal utility of compliance with various MIPS measures. Solo, small, medium, large, and very large practices were modeled using available data and final rules published by the United States Department of Health and Human Services (HHS). The model analysis found that small groups were generally incentivized not to comply with MIPS measures. Conversely, larger organizations were found to have strong financial incentives to maximize pursuit of MIPS measures. Incentives to pursue interoperability investments were projected to be generally under $10 200 for small organizations but approximately $690 000 for very large practices whereas the health information technology (IT) resources necessary to pursue these measures may not have nearly the same range of costs. In light of these findings, small groups may be driven to join larger groups as large groups continue to capitalize on their larger incentives to pursue MIPS measures. As financial success under MIPS is dependent on scale, healthcare systems that pursue consolidation may achieve greater success under quality payment programs similar to MIPS which include the newly proposed MIPS Value Pathways (MVPs).
APA Citation
Kauffman, D., Borden, W., & Choi, B. (2020). Maximizing Performance in Medicare’s Merit Based Incentive Payment System: A Financial Model to Optimize Health Information Technology Resource Allocation. Inquiry (United States), 57 (). http://dx.doi.org/10.1177/0046958020971237