Medicare upcoding and hospital ownership

Silverman, Elaine; Skinner, Jonathan

doi:10.1016/j.jhealeco.2003.09.007

Cited by 291 publications

(233 citation statements)

References 31 publications

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“…Concerning upcoding, we can start from the contributions provided by Dafny (2005) and Silverman and Skinner (2004). Dafny (2005) adopts the following proxy to compute upcoding: she considers all the DRG pairs with and without complications and defines upcoding as the ratio of hospitals' discharges in the DRGs with complications over the total number of discharges in the DRG pair (i.e.…”

Section: The Upcoding Indexmentioning

confidence: 99%

“…If the health status of the population becomes worse, hospitals may register a higher number of patients with complications. Silverman and Skinner (2004) do consider the patient's health status, but do not disentangle it from the proxy they propose for upcoding. They study only four DRGs concerning general respiratory ailments, one of which has a DRG weight much higher than the others because of the presence of complications.…”

Section: The Upcoding Indexmentioning

confidence: 99%

“…In order to take into account the patient's sickness status, Silverman and Skinner (2004) compare the difference in the hospitals' trends for upcoding and patients' health status, using as a proxy the Charlson Comorbidity Index.…”

Section: The Upcoding Indexmentioning

confidence: 99%

“…Silverman and Skinner (2004) In medicine comorbidity describes the presence in a patient of other diseases in ad-4 trend increase in the readmission rate in the US after the introduction of the PPS. Our contribution extends his analysis by computing the readmission rate for all the possible DRGs, and by proposing a refinement of the readmission's proxy.…”

Section: Introductionmentioning

confidence: 99%

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The effects of upcoding, cream skimming and readmissions on the Italian hospitals efficiency: A population-based investigation

et al. 2010

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In this paper we analyze the effects of some distortions induced by prospective payment system, i.e. Upcoding, Cream Skimming and Readmissions on hospitals' technical efficiency. We estimate a production function using a population-based dataset composed by all active hospitals in an Italian region, Lombardy, during the period 1998-2007. We show that cream skimming and upcoding have a negative impact on hospitals' technical efficiency, while readmissions have a positive effect. Moreover, we find that private hospitals are more engaged in cream skimming than public and not-for-profit ones, while we observe no ownership differences regarding upcoding. Not-for-profit hospitals have the highest readmission index. Last, not-for-profit and public hospitals have the same efficiency levels, while private hospitals have the lowest technical efficiency.

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Section: The Upcoding Indexmentioning

confidence: 99%

Section: The Upcoding Indexmentioning

confidence: 99%

Section: The Upcoding Indexmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The effects of upcoding, cream skimming and readmissions on the Italian hospitals efficiency: A population-based investigation

et al. 2010

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“…Early studies (Carter et al (1990)) find little evidence of upcoding, while more recent studies (Silverman and Skinner (2004), Dafny (2005)) demonstrate that hospitals did engage in upcoding for selective DRGs where such behavior is profitable. They show that for-profit hospitals engage in these activities more actively than non-profit or government hospitals.…”

Section: Hospital Reimbursement and Drg Codesmentioning

confidence: 99%

Physician Workload and Hospital Reimbursement: Overworked Physicians Generate Less Revenue per Patient

Powell

Savin

Savva

2012

M&SOM

116

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We study the impact of physician workload on hospital reimbursement utilizing a detailed data set from the trauma department of a major urban hospital. We find that the proportion of patients assigned a "highseverity" status for reimbursement purposes, which maps, on average, to a 47.8% higher payment for the hospital, is substantially reduced as the workload of the discharging physician increases. This effect persists after we control for a number of systematic differences in patient characteristics, condition and time of discharge. Furthermore, we show that it is unlikely to be caused by selection bias or endogeneity in either discharge timing or allocation of discharges to physicians. We attribute this phenomenon to a workloadinduced reduction in diligence of paperwork execution. We estimate the associated monetary loss to be approximately 1.1% (95% Confidence Interval 0.4% − 1.9%) of the department's annual revenue.

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Total Knee Arthroplasty Volume, Utilization, and Outcomes Among Medicare Beneficiaries, 1991-2010

Cram

Lü²,

Kates³

et al. 2012

JAMA

820

522

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Medicare upcoding and hospital ownership

Cited by 291 publications

References 31 publications

The effects of upcoding, cream skimming and readmissions on the Italian hospitals efficiency: A population-based investigation

The effects of upcoding, cream skimming and readmissions on the Italian hospitals efficiency: A population-based investigation

Physician Workload and Hospital Reimbursement: Overworked Physicians Generate Less Revenue per Patient

Total Knee Arthroplasty Volume, Utilization, and Outcomes Among Medicare Beneficiaries, 1991-2010

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