Upcoding in a National Health Service: the evidence from Portugal

Barros, Pedro Pita; Braun, Gisele

doi:10.1002/hec.3335

Cited by 42 publications

(46 citation statements)

References 18 publications

(36 reference statements)

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“…Those findings, along with the results of this study, suggest that the association between the payment levels and the quality of services may not be strong. On the other hand, the evidence of DRG‐specific volume effects and upcoding has been consistently documented in existing studies (Barros & Braun, ; Dafny, ; Januleviciute et al, ; Silverman & Skinner, ). This study adds to this body of literature by exploiting area‐specific price shocks and thereby, isolating the effects of windfall price increases on hospital behavior.…”

Section: Resultsmentioning

confidence: 64%

“…Another possible response is that hospitals simply change their coding practices by shifting patients to more profitable DRG codes, a phenomenon called “upcoding” (Barros & Braun, ; Dafny, ; Januleviciute, Askildsen, Kaarboe, Siciliani, & Sutton, ). To examine this possibility, I closely follow Dafny (), who exploits the “paired” grouping system of the DRG codes.…”

Section: Other Behavioral Responsesmentioning

confidence: 99%

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Hospital responses to price shocks under the prospective payment system

Shin

2018

Health Economics

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Under the prospective payment system (PPS), hospitals receive a bundled payment for an entire episode of treatment based on diagnosis‐related groups (DRG). Although there is ample evidence regarding the impact of the introduction of the PPS, there is little research on the effects of the ensuing changes in payment levels under the PPS. In 2005, the Medicare PPS changed its definition of payment areas from the Metropolitan Statistical Areas to the Core‐Based Statistical Areas, generating substantial area‐specific price shocks. Using these exogenous price variations, this study examines hospital responses to price changes under the PPS. The results demonstrate that, while the average payment amount significantly increases in the affected areas, no parallel trend is observed in admission volume, treatment intensity, and quality of services. Conversely, hospitals facing a price increase are more liable to the perverse incentives that the PPS is known to encourage, namely, selecting or shifting patients into higher‐paying DRGs. These results suggest that paying a higher price for a given service may not induce hospitals to offer services of better quality, but can rather prompt even higher payments through other behavioral responses.

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Section: Resultsmentioning

confidence: 64%

Section: Other Behavioral Responsesmentioning

confidence: 99%

Hospital responses to price shocks under the prospective payment system

Shin

2018

Health Economics

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“…Early studies have already pointed to the unintended consequences of introducing DRG-based payment systems, 4 namely, the attempt by hospitals to increase revenues through fraudulent coding practices (e.g., Barros & Braun, 2017;Carter et al, 1990;Dafny, 2005;Januleviciute, Askildsen, Kaarboe, Siciliani, & Sutton, 2016;Silverman & Skinner, 2004). First, we complement empirical research on DRG upcoding in health care markets.…”

Section: Contribution To the Literaturementioning

confidence: 99%

Dishonesty in health care practice: A behavioral experiment on upcoding in neonatology

2018

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Dishonest behavior significantly increases the cost of medical care provision. Upcoding of patients is a common form of fraud to attract higher reimbursements. Imposing audit mechanisms including fines to curtail upcoding is widely discussed among health care policy‐makers. How audits and fines affect individual health care providers' behavior is empirically not well understood. To provide new evidence on fraudulent behavior in health care, we analyze the effect of a random audit including fines on individuals' honesty by means of a novel controlled behavioral experiment framed in a neonatal care context. Prevalent dishonest behavior declines significantly when audits and fines are introduced. The effect is driven by a reduction in upcoding when being detectable. Yet upcoding increases when not being detectable as fraudulent. We find evidence that individual characteristics (gender, medical background, and integrity) are related to dishonest behavior. Policy implications are discussed.

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“…FFS is used as control group to capture real changes in diagnoses that can be subtracted from the combined nominal and real changes in the MA diagnoses, after accounting for risk selection between MA and FFS. Using this approach, Kronick and Welch (2014) (Barros and Braun, 2016;Januleviciute et al, 2016). Sacarny (2016) evaluates hospitals' responses to a 2008 reform that increased Medicare payments for claims that had detailed codes describing the patients' type of heart failure.…”

Section: Notes: Based On 10% Sample Of Claims Submitted By Health Insmentioning

confidence: 99%

Plan responses to diagnosis-based payment: Evidence from Germany’s morbidity-based risk adjustment

Bauhoff

Fischer²,

Göpffarth

et al. 2017

Journal of Health Economics

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Many competitive health insurance markets adjust payments to participating health plans according to their enrollees' risk -including based on diagnostic information. We investigate responses of German health plans to the introduction of morbidity-based risk adjustment in the Statutory Health Insurance in 2009, which triggers payments based on "validated" diagnoses by providers. Using the regulator's data from office-based physicians, we estimate a difference-indifference analysis of the change in the share and number of validated diagnoses for ICD codes that are inside or outside the risk adjustment but are otherwise similar. We find a differential increase in the share of validated diagnoses of 2.6 and 3.6 percentage points (3-4%) between 2008 and 2013. This increase appears to originate from both a shift from not-validated toward validated diagnoses and an increase in the number of such diagnoses. Overall, our results indicate that plans were successful in influencing physicians' coding practices in a way that could lead to higher payments. Terms of use: Documents inJEL-Codes: H510, I100, I130, I180.

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Upcoding in a National Health Service: the evidence from Portugal

Cited by 42 publications

References 18 publications

Hospital responses to price shocks under the prospective payment system

Hospital responses to price shocks under the prospective payment system

Dishonesty in health care practice: A behavioral experiment on upcoding in neonatology

Plan responses to diagnosis-based payment: Evidence from Germany’s morbidity-based risk adjustment

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