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COMPARISON OF HOSPITAL COSTING METHODS IN AN ECONOMIC EVALUATION OF A MULTINATIONAL CLINICAL TRIAL

  • Shelby D. Reed (a1), Joëlle Y. Friedman (a1), Ari Gnanasakthy (a2) and Kevin A. Schulman (a1)

Abstract

Objectives: To develop and evaluate strategies for estimating hospitalization costs in multinational clinical trials.

Methods: Hospital cost estimates for eleven diagnoses were collected from twelve countries participating in a trial of therapies for congestive heart failure. Estimates were combined with U.S.-based diagnosis-related group weights to compute country-specific unit cost estimates for all reasons for hospitalization. Variations of hospital costing methods were developed. The unit cost method assigns a country-specific unit cost estimate to each hospitalization. The other methods adjust for length of stay using a daily cost (DC) estimate for each diagnosis, based on either the mean length of stay (DC-mean method) or the median length of stay (DC-median method) for each diagnosis in each country. Additional modifications were explored through adjustment of the distribution of daily costs incurred during a hospital stay.

Results: The mean cost for all hospitalizations was $10,242 (SD, 10,042) using the unit cost method, $10,242 (SD, 12,760) using the standard DC-mean method, and $13,967 (SD, 18,762) using the standard DC-median method. In comparisons of costs for all 5,486 hospitalizations incurred by a subset of 2,352 patients in the trial, the unit cost method provided 92% power to detect a $1,000 cost difference. The standard DC-mean method provided 76% power, and the standard DC-median method provided 44% power.

Conclusions: Hospital costing methods that adjust for differences in length of stay require a significantly larger sample to attain comparable statistical power as methods that assign unadjusted unit cost estimates to hospitalization events.

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COMPARISON OF HOSPITAL COSTING METHODS IN AN ECONOMIC EVALUATION OF A MULTINATIONAL CLINICAL TRIAL

  • Shelby D. Reed (a1), Joëlle Y. Friedman (a1), Ari Gnanasakthy (a2) and Kevin A. Schulman (a1)

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