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Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

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The sensitivity of adverse event cost estimates to diagnostic coding error.

Gavin Wardle¹, Walter P Wodchis, Audrey Laporte

¹Department of Health Policy, Management and Evaluation, Faculty of Medicine, University of Toronto, 95 Bertmount Ave, Toronto, ON, M4M 2X8, Canada. gavin@preyrasolutions.com

Health Services Research

|November 19, 2011

Summary

Diagnostic coding errors significantly underestimate hospital costs for adverse events. This study found costs were underestimated by 16%, highlighting the need to account for coding inaccuracies in financial assessments.

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Area of Science:

Health Services Research
Medical Economics
Healthcare Informatics

Background:

Accurate estimation of hospital costs associated with adverse events is crucial for resource allocation and quality improvement initiatives.
Diagnostic coding errors can introduce bias into cost calculations, potentially leading to flawed financial and operational decisions.

Purpose of the Study:

To quantify the impact of diagnostic coding errors on the estimated hospital costs attributed to adverse events.
To assess the sensitivity of adverse event cost estimations to variations in diagnostic coding accuracy.

Main Methods:

Analysis of 9,670 complex medical and surgical admissions across 11 Ontario hospitals (2002-2004).
Utilized the Ontario Case Costing Initiative database for patient-specific costs.
Employed ICD10-CA codes for adverse event identification and applied propensity score matching and multivariate regression to analyze coding error impact.

Main Results:

Estimated costs for individual adverse events ranged from $16,008 to $30,176.
Diagnostic coding errors led to a 16% underestimation of total adverse event costs.
The influence of coding errors on cost estimates varied significantly among different hospital organizations.

Conclusions:

Adverse event cost estimations are highly sensitive to the accuracy of diagnostic coding.
Ignoring the potential for coding errors can result in substantial underestimation of the true financial burden of adverse events.