Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1287/mnsc.2017.2996 | MANAGEMENT SCIENCE |
Keywords | DocType | Volume |
Medicare,pay-for-performance,upcoding,asymmetric information,quality control,detection | Journal | 65 |
Issue | ISSN | Citations |
3 | 0025-1909 | 0 |
PageRank | References | Authors |
0.34 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hamsa Bastani | 1 | 0 | 0.34 |
| Joel Goh | 2 | 164 | 9.07 |
| Mohsen Bayati | 3 | 678 | 44.93 |