2017
DOI: 10.1007/s41669-017-0015-6
|View full text |Cite|
|
Sign up to set email alerts
|

Handling Missing Data in Within-Trial Cost-Effectiveness Analysis: A Review with Future Recommendations

Abstract: Cost-effectiveness analyses (CEAs) alongside randomised controlled trials (RCTs) are increasingly 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 … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
54
0
3

Year Published

2017
2017
2022
2022

Publication Types

Select...
9

Relationship

3
6

Authors

Journals

citations
Cited by 46 publications
(64 citation statements)
references
References 198 publications
0
54
0
3
Order By: Relevance
“…l Missing data in baseline resource use, quality of life and other covariates were handled with multiple imputation using chained equations, using guidelines from Gabrio et al 68 In line with primary outcomes analysis, the base case was a complete-case analysis.…”
Section: Health Economic Analysesmentioning
confidence: 99%
“…l Missing data in baseline resource use, quality of life and other covariates were handled with multiple imputation using chained equations, using guidelines from Gabrio et al 68 In line with primary outcomes analysis, the base case was a complete-case analysis.…”
Section: Health Economic Analysesmentioning
confidence: 99%
“…Both cost‐utility and cost‐effectiveness analyses were repeated using a societal perspective. To test the robustness of the assumption that data were ‘missing at random’ as required for multiple imputation and recommended for the reference assumption, cost‐utility was also estimated for complete cases only (no missing cost (MBS and PBS) or outcome data (SF6D)). One‐way sensitivity analyses were performed using costs associated with emergency department presentations and hospital admissions, which comprise the largest proportion of healthcare costs, with modification of this component (+10% and −10%) to assess the impact on cost‐utility estimates.…”
Section: Methodsmentioning
confidence: 99%
“…The appropriate method for dealing with missing cost data was dependent on the number of missing data and the likely mechanism of missingness. 50 Costs relating to hospitalisations were primarily sourced from PLICS data. If PLICS data were not available or missing, the use of hospital services was based on entries in CRFs, or otherwise from participants' resource use questionnaires.…”
Section: Analytic Approachmentioning
confidence: 99%