Evidence of Upcoding in Pay-for-Performance Programs
Autor: | Hamsa Bastani, Mohsen Bayati, Joel Goh |
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Rok vydání: | 2019 |
Předmět: |
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050208 finance Actuarial science Strategy and Management media_common.quotation_subject 05 social sciences virus diseases Legislation Medical classification Pay for performance Management Science and Operations Research Information asymmetry Incentive 0502 economics and business Quality (business) Business 050207 economics Health policy Reimbursement media_common |
Zdroj: | Management Science. 65:1042-1060 |
ISSN: | 1526-5501 0025-1909 |
Popis: | Recent Medicare legislation seeks to improve patient care quality by financially penalizing providers for hospital-acquired infections (HAIs). However, Medicare cannot directly monitor HAI rates and instead relies on providers accurately self-reporting HAIs in claims to correctly assess penalties. Consequently, the incentives for providers to improve service quality may disappear if providers upcode, i.e., misreport HAIs (possibly unintentionally) in a manner that increases reimbursement or avoids financial penalties. Identifying upcoding in claims data is challenging because of unobservable confounders (e.g., patient risk). We leverage state-level variations in adverse event reporting regulations and instrumental variables to discover contradictions in HAI and present-on-admission (POA) infection reporting rates that are strongly suggestive of upcoding. We conservatively estimate that 10,000 out of 60,000 annual reimbursed claims for POA infections (18.5%) were upcoded HAIs, costing Medicare $200 million. Our findings suggest that self-reported quality metrics are unreliable and, thus, that recent legislation may result in unintended consequences. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2996 . This paper was accepted by Vishal Gaur, operations management. |
Databáze: | OpenAIRE |
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