{'fraction_non_alphanumeric': 0.023076923076923078, 'fraction_numerical': 0.005594405594405594, 'mean_word_length': 5.8798076923076925, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Evidence of Upcoding in Pay-for-Performance Programs

Recent Medicare legislation has been directed at improving patient care quality by penalizing providers for hospital-acquired infections (HAIs). However, asymmetric information prevents Medicare from directly monitoring HAI rates. Thus, these policies assume that providers correctly distinguish HAIs from present-on-admission (POA) infections in claims data despite opposing financial incentives. In particular, these policies may be undermined if providers engage in upcoding, a practice where HAIs are mis-reported (possibly unintentionally) to increase reimbursement or avoid financial penalties. Identifying upcoding behavior from claims data is challenging due to unobservable confounders. Our approach leverages state-level variations in adverse event reporting regulations and instrumental variable techniques to discover contradictions between HAI and POA reporting rates that are strongly suggestive of upcoding. We estimate that there are over 10,000 upcoded infections a year, resulting in an added cost burden of $200 million. Our findings suggest that, contrary to widely-held beliefs, increasing financial penalties alone may not reduce HAI incidence and may even exacerbate the problem. We make several policy recommendations based on our results, including a new measure for targeted HAI auditing and suggestions for effective adverse event reporting systems.