Recent anti‐fraud enforcement policies across the US health‐care system have led to widespread speculation about the effectiveness of increased penalties for overcharging practices adopted by health‐care service organizations. Severe penalties, including imprisonment, suggest that fraudulent billing, and related misclassification of services provided to patients, would be greatly reduced or eliminated as a result of increased government investigation and reprisal. This study sought to measure the extent to which health information managers reported being influenced by superiors to manipulate coding and classification of patient data. Findings from a nationwide survey of managers suggest that such practices are still pervasive, despite recent counter‐fraud legislation and highly visible prosecution of fraudulent behaviors. Examining variation in influences exerted from both within and external to specific service delivery settings, results suggest that pressure to alter classification codes occurred both within and external to the provider setting. We also examine how optimization influences vary across demographic, practice setting, and market characteristics, and find significant variation in influence across practice settings and market types. Implications for reimbursement programs and evidence‐based health care are discussed.
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1 December 2002
This article was originally published in
Journal of Management in Medicine
Conceptual Paper|
December 01 2002
Variation in coding influence across the USA: Risk and reward in reimbursement optimization
Daniel P. Lorence;
Daniel P. Lorence
Department of Health Policy and Administration, The Pennsylvania State University, State College, Pennsylvania, USA
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Michael Richards
Michael Richards
Community Development Services, Chicago, Illinois, USA
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Publisher: Emerald Publishing
Online ISSN: 1758-7441
Print ISSN: 0268-9235
© MCB UP Limited
2002
J Manag Med (2002) 16 (6): 422–435.
Citation
Lorence DP, Richards M (2002), "Variation in coding influence across the USA: Risk and reward in reimbursement optimization ". J Manag Med, Vol. 16 No. 6 pp. 422–435, doi: https://doi.org/10.1108/02689230210450981
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