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

Gabrio, A; Mason, A; Baio, G; (2017) Handling Missing Data in Within-Trial Cost-Effectiveness Analysis: a Review with Future Guidelines. PharmacoEconomics - Open pp. 1-19. 10.1007/s41669-017-0015-6. Green open access

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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.

Type: Article
Title: Handling Missing Data in Within-Trial Cost-Effectiveness Analysis: a Review with Future Guidelines
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s41669-017-0015-6
Publisher version: http://dx.doi.org/ 10.1007/s41669-017-0015-6
Language: English
Additional information: © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/1506029
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