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Regression models for analyzing costs and their determinants in health care: an introductory review
Dario Gregori1, Michele Petrinco, Simona Bo
1Department of Environmental Medicine and Public Health, Via Loredan 18, 35121 Padova, Italy. dario.gregori@unipd.it
Objective:
This article aims to describe the various approaches in multivariable modelling of healthcare costs data and to synthesize the respective criticisms as proposed in the literature.
Methods:
We present regression methods suitable for the analysis of healthcare costs and then apply them to an experimental setting in cardiovascular treatment (COSTAMI study) and an observational setting in diabetes hospital care.
Results:
We show how methods can produce different results depending on the degree of matching between the underlying assumptions of each method and the specific characteristics of the healthcare problem.
Conclusions:
The matching of healthcare cost models to the analytic objectives and characteristics of the data available to a study requires caution. The study results and interpretation can be heavily dependent on the choice of model with a real risk of spurious results and conclusions.
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