Publication | Closed Access
Evidence of Upcoding in Pay-for-Performance Programs
60
Citations
30
References
2018
Year
Vishal GaurHealth Insurance DesignHealth Care AccountingLawFinancial ProtectionHealth Care FinanceHealth LawHai RatesAdverse EventRemuneration PracticeEconomic AnalysisManaged CarePublic HealthInsurance RegulationsHealth Services ResearchEconomicsHealth PolicyHealth InsuranceOutcomes ResearchRecent Medicare LegislationHealth ReimbursementHealthcare ValueEpidemiologyHealth Care DeliveryPublic FinancePay-for-performance ProgramsHealth EconomicsMedical MalpracticeIncentive MechanismHealth Care ReimbursementPatient SafetyBusinessHealth Care Cost
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.
| Year | Citations | |
|---|---|---|
Page 1
Page 1