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Miscoding: a threat to the hospital care system. How to detect it?
W H Aelvoet1, N Terryn, F Windey
1Federal Service of Health, Food Chain Safety and Environment, Directorate General for the Organisation of Health Care Establishments, Eurostation Bloc II, Brussels, Belgium. willem.aelvoet@health.fgov.be
Revue D'Epidemiologie Et De Sante Publique
|April 21, 2009
Summary
Hospital case mix miscoding can distort data and impact care quality assessments. Fraud-directed audits effectively identify coding errors and improve administrative database quality for epidemiology and care evaluation.
Area of Science:
- Health Services Research
- Medical Informatics
- Public Health
Background:
- Artificial manipulation of hospital case mix (up-coding or under-coding) can negatively affect healthcare systems.
- Miscoding can disrupt epidemiological data and inaccurately assess hospital care quality using administrative data.
Purpose of the Study:
- To assess deviant coding behavior at the hospital level using fixed effects models.
- To develop and test a methodology for identifying fraudulent coding practices by comparing hospital-level data with national trends.
Main Methods:
- Utilized fixed effects models to analyze the linear evolution of hospital characteristics over time.
- Developed a method comparing individual hospital trends to national trends, using an interaction term.
- Conducted both random and fraud-directed audits to validate the methodology.
Main Results:
- Identified significant inter-hospital variations in coding practices, including improvements, up-coding, and fraudulent under-coding.
- Random audits revealed coding errors leading to wrongful gains, while fraud-directed audits uncovered substantially larger discrepancies.
Conclusions:
- Fraud-directed audits are valuable for quality assurance of administrative databases.
- This approach enhances the utility of administrative data for epidemiological studies and healthcare quality assessment.
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