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dc.contributor.authorNg, Shu Kay
dc.contributor.authorByrnes, Joshua
dc.contributor.authorScuffham, Paul
dc.date.accessioned2019-08-26T04:37:53Z
dc.date.available2019-08-26T04:37:53Z
dc.date.issued2019
dc.identifier.issn0895-4356
dc.identifier.doi10.1016/j.jclinepi.2019.07.013
dc.identifier.urihttp://hdl.handle.net/10072/386680
dc.description.abstractOBECTIVE: We propose a data-matching approach to estimate intervention efficacy for randomised controlled trials (RCTs) when there is non-compliance to the allocated treatment with induced selection bias. STUDY DESIGN: and Settings: We considered a large RCT to compare healthcare costs and hospital length-of-stay 12 months post randomisation. Participants allocated to the intervention group were eligible to receive health-coaching and disease-management services. An opt-out approach was adopted for recruitment. Control-group participants received usual care but were allowed to opt-in to receive the intervention. Using "nearest-neighbour"-matched data, we identified compliant participants in both arms to estimate intervention efficacy. Results were compared with intention-to-treat (ITT), instrumental-variable (IV)-adjusted ITT, per-protocol (PP), and as-treated (AT) analyses. RESULTS: The ITT estimated an intervention effect of a 1.5% reduction in cost, but 56.7% of intervention-group participants did not receive health-coaching. The PP and AT found an increase in cost of 9.4% and 17.1%, respectively. The matching method estimated a 12.3% reduction in cost. After adjustment for baseline covariates, the intervention group had lower same-day admission cost (13.6%; 95% CI: 7.3%-20.0%; p<0.001) and shorter hospital stay (11.2%; 95% CI: 2.6%-19.9%; p=0.021). CONCLUSION: Opt-in/opt-out strategies in RCTs misled intervention comparisons and the matching approach improved estimation of intervention efficacy.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofpagefrom125
dc.relation.ispartofpageto132
dc.relation.ispartofjournalJournal of Clinical Epidemiology
dc.relation.ispartofvolume115
dc.subject.fieldofresearchHealth economics
dc.subject.fieldofresearchEpidemiology
dc.subject.fieldofresearchcode380108
dc.subject.fieldofresearchcode4202
dc.subject.keywordsNon-compliance
dc.subject.keywordshealth coaching
dc.subject.keywordsnearest-neighbour matching
dc.subject.keywordsrandomised controlled trial
dc.subject.keywordsselection bias
dc.titleIdentifying compliant participants through data matching improved estimation of intervention efficacy: randomized trials with opt-in/opt-out
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationNg, SK; Byrnes, J; Scuffham, P, Identifying compliant participants through data-matching improved estimation of intervention efficacy: Randomised trials with opt-in/opt-out strategies., Journal of Clinical Epidemiology, 2019, 115, pp. 125-132
dcterms.dateAccepted2019-07-17
dcterms.licensehttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.date.updated2019-08-26T04:21:52Z
dc.description.versionAccepted Manuscript (AM)
gro.rights.copyright© 2019 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorNg, Shu Kay Angus
gro.griffith.authorByrnes, Joshua M.
gro.griffith.authorScuffham, Paul A.


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