dc.contributor.author | Ng, Shu Kay | |
dc.contributor.author | Byrnes, Joshua | |
dc.contributor.author | Scuffham, Paul | |
dc.date.accessioned | 2019-08-26T04:37:53Z | |
dc.date.available | 2019-08-26T04:37:53Z | |
dc.date.issued | 2019 | |
dc.identifier.issn | 0895-4356 | |
dc.identifier.doi | 10.1016/j.jclinepi.2019.07.013 | |
dc.identifier.uri | http://hdl.handle.net/10072/386680 | |
dc.description.abstract | OBECTIVE: 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.peerreviewed | Yes | |
dc.language | English | |
dc.language.iso | eng | |
dc.publisher | Elsevier | |
dc.relation.ispartofpagefrom | 125 | |
dc.relation.ispartofpageto | 132 | |
dc.relation.ispartofjournal | Journal of Clinical Epidemiology | |
dc.relation.ispartofvolume | 115 | |
dc.subject.fieldofresearch | Health economics | |
dc.subject.fieldofresearch | Epidemiology | |
dc.subject.fieldofresearchcode | 380108 | |
dc.subject.fieldofresearchcode | 4202 | |
dc.subject.keywords | Non-compliance | |
dc.subject.keywords | health coaching | |
dc.subject.keywords | nearest-neighbour matching | |
dc.subject.keywords | randomised controlled trial | |
dc.subject.keywords | selection bias | |
dc.title | Identifying compliant participants through data matching improved estimation of intervention efficacy: randomized trials with opt-in/opt-out | |
dc.type | Journal article | |
dc.type.description | C1 - Articles | |
dcterms.bibliographicCitation | Ng, 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.dateAccepted | 2019-07-17 | |
dcterms.license | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.date.updated | 2019-08-26T04:21:52Z | |
dc.description.version | Accepted 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.hasfulltext | Full Text | |
gro.griffith.author | Ng, Shu Kay Angus | |
gro.griffith.author | Byrnes, Joshua M. | |
gro.griffith.author | Scuffham, Paul A. | |