An Educational Review About Using Cost Data for the Purpose of Cost-Effectiveness Analysis

Abstract

This paper provides an educational review covering the consideration of costs for cost-effectiveness analysis (CEA), summarising relevant methods and research from the published literature. Cost data are typically generated by applying appropriate unit costs to healthcare resource-use data for patients. Trial-based evaluations and decision analytic modelling represent the two main vehicles for CEA. The costs to consider will depend on the perspective taken, with conflicting recommendations ranging from focusing solely on healthcare to the broader 'societal' perspective. Alternative sources of resource-use are available, including medical records and forms completed by researchers or patients. Different methods are available for the statistical analysis of cost data, although consideration needs to be given to the appropriate methods, given cost data are typically non-normal with a mass point at zero and a long right-hand tail. The choice of covariates for inclusion in econometric models also needs careful consideration, focusing on those that are influential and that will improve balance and precision. Where data are missing, it is important to consider the type of missingness and then apply appropriate analytical methods, such as imputation. Uncertainty around costs should also be reflected to allow for consideration on the impacts of the CEA results on decision uncertainty. Costs should be discounted to account for differential timing, and are typically inflated to a common cost year. The choice of methods and sources of information used when accounting for cost information within CEA will have an effect on the subsequent costeffectiveness results and how information is presented to decision makers. It is important that the most appropriate methods are used as overlooking the complicated nature of cost data could lead to inaccurate information being given to decision makers.Not appropriately controlling for the nature of cost data and the uncertainty around subsequent cost estimates used in cost-effectiveness analysis (CEA) could lead to inaccurate information being given to decision makers.Although checklists exist for use alongside CEA to aid transparency in the methods used, there is still poor reporting and rationalisation of statistical methods and covariate adjustments when using cost data.It is difficult to suggest a 'one size fits all' methodology when estimating and analysing cost data for CEA; therefore, it is down to the researcher to assess the nature of the cost data to determine which methods to use.

Conducting Value for Money Analyses for Non-randomised Interventional Studies Including Service Evaluations: An Educational Review with Recommendations

“…There are multiple forms of economic evaluation. However, all are VfM analyses, with 'costs' representing an integral aspect of the evaluation process owing to the resultant opportunity costs (Appendix S1 of the ESM) from resources not being available for other purposes [27][28][29]. Traditionally, at the local level, there has been very little use of economic evaluation evidence, although there is suggestion this has increased overtime particularly in the UK [30,31].…”

“…The costs to include in a VfM analysis are dependent on what question needs to be answered for the decision context being informed [26,28,62]. Fundamentally, when a care service introduces an intervention or delivery model, the evaluation should include the direct costs of this aspect referred to as 'intervention costs' (Appendix S1 of the ESM).…”

“…7). Cost data for VfM analyses are estimated based on care resource-use data to which unit costs are attached (Appendix S1 of the ESM) [28]. There are self-reported and routinely collected resource-use data methods as described by Franklin and Thorn [68], noting their (and our) examples are based on routine data sources in England.…”

“…Such data could be used for service evaluations, albeit with a variety of time, monetary, technical and information governance restrictions [68]. As such, routine data are recommended but often difficult to utilise [28,68,75].…”

“…There are specific statistical considerations pertinent to VfM analyses that need to be accounted for alongside the non-randomised nature of the data. Two educational reviews already describe the use of utility data for CUA [98] and costs for CEA [28], both of which describe statistical considerations such as: assessing cost and consequence (utility) data and its distribution; baseline covariate adjustments; and dealing with missing data. We do not wish to repeat these educational reviews.…”