Handling Missing Data in Within-Trial Cost-Effectiveness Analysis: a Review with Future Guidelines

TL;DR

This review examines how missing data in cost-effectiveness analyses from RCTs are handled, highlighting deficiencies in current practices and proposing guidelines to improve reporting and methodology for better healthcare decision-making.

Contribution

It provides a comprehensive review of missing data handling in RCT-based CEAs and offers future guidelines for better reporting and methodological choices.

Findings

Missing data are often inadequately handled in CEAs.

Reporting on missing data methods is frequently unsatisfactory.

Guidelines for improved handling and reporting are proposed.

Abstract

Cost-Effectiveness Analyses (CEAs) alongside randomised controlled trials (RCTs) are increasingly often designed to collect resource use and preference-based health status data for the purpose of healthcare technology assessment. However, because of the way these measures are collected, they are prone to missing data, which can ultimately affect the decision of whether an intervention is good value for money. We examine how missing cost and effect outcome data are handled in RCT-based CEAs, complementing a previous review (covering 2003-2009, 88 articles) with a new systematic review (2009-2015, 81 articles) focussing on two different perspectives. First, we review the description of the missing data, the statistical methods used to deal with them, and the quality of the judgement underpinning the choice of these methods. Second, we provide guidelines on how the information about missingness and related methods should be presented to improve the reporting and handling of missing data. Our review shows that missing data in within-RCT CEAs are still often inadequately handled and the overall level of information provided to support the chosen methods is rarely satisfactory.