A Bayesian modelling framework for health care resource use and costs in trial-based economic evaluations
we propose a novel Bayesian framework for the modelling of HRU data in trial-based economic evaluations, …
Economic Evaluations, Missing Data, Bayesian statistics
Abstract
Individual-level data are routinely used in trial-based economic evaluations to obtain an assessment of the effectiveness and costs associated with a given intervention. While effectiveness measures are often expressed via utility scores derived from health-related quality of life instruments (EQ-5D questionnaires), information on different types of healthcare resource use (HRU) measures (number and types of services) may be collected to compute the costs. Partially-complete HRU data, particularly in the case of self-reported questionnaires, are handled using “ad-hoc” methods, implicitly relying on some assumptions (fill-in a zero) which are typically hard to justify without external knowledge. Although methods have been proposed to account for the uncertainty surrounding missing data, particularly in the form of multiple imputation or Bayesian methods, these have been mostly implemented at the level of costs at different times or over the entire study period, while little attention has been given to how missing values at the level of HRUs should be addressed and their implications on the final analysis. We present a general Bayesian framework for the analysis of partially observed HRUs in trial-based economic evaluations, which can accommodate the typical complexities of the data (excess zeros, skewness, missingness) and quantify the impact of missingness uncertainty at HRU level on the statistical and economic results. We show the benefits of our approach with a motivating example and compare the results to those from traditional analyses focussed on the modelling of cost variables after adopting some ad-hoc imputation strategy for HRU data. This paper highlights the importance of adopting a comprehensive modelling approach to handle partially-observed HRU data in economic evaluations and the strategic advantages of building these models within a Bayesian framework.
Citation
@online{gabrio2025,
author = {Gabrio, Andrea},
title = {A {Bayesian} Modelling Framework for Health Care Resource Use
and Costs in Trial-Based Economic Evaluations},
volume = {2},
number = {1},
date = {2025-09-16},
url = {https://journals.sagepub.com/doi/full/10.1177/0272989X251376026},
doi = {10.1177/0272989X251376026},
langid = {en},
abstract = {{[}we propose a novel Bayesian framework for the modelling
of HRU data in trial-based economic evaluations,
...{]}\{style=“font-size: 85\%”\}}
}