Variation in coding influence across the USA: Risk and reward in reimbursement optimization

Daniel P. Lorence; Michael Richards

doi:10.1108/02689230210450981

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Journal of Management in Medicine

ISSN: 0268-9235
Currently published as: Journal of Health Organization and Management
Incorporates: Health Manpower Management

Online from: 1986

Subject Area: Health Care Management/Healthcare

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Variation in coding influence across the USA: Risk and reward in reimbursement optimization

Document Information:
Title:	Variation in coding influence across the USA: Risk and reward in reimbursement optimization
Author(s):	Daniel P. Lorence, (Department of Health Policy and Administration, The Pennsylvania State University, State College, Pennsylvania, USA), Michael Richards, (Community Development Services, Chicago, Illinois, USA)
Citation:	Daniel P. Lorence, Michael Richards, (2002) "Variation in coding influence across the USA: Risk and reward in reimbursement optimization", Journal of Management in Medicine, Vol. 16 Iss: 6, pp.422 - 435
Keywords:	Classification, Coding, Evidence, Fraud, Health care, Legislation
Article type:	Conceptual Paper
DOI:	10.1108/02689230210450981 (Permanent URL)
Publisher:	MCB UP Ltd
Abstract:	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.