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• W2963157400 abstract "Objectives We propose a data-matching approach to estimate intervention efficacy for randomized controlled trials (RCTs) when there is noncompliance to the allocated treatment with induced selection bias. Study Design and Setting We considered a large RCT to compare health care costs and hospital length of stay 12 months after randomization. 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-neighbor”-matched data, we identified compliant participants in both arms to estimate intervention efficacy. Results were compared with intention-to-treat (ITT), instrumental-variable–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." @default.
• W2963157400 created "2019-07-30" @default.
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• W2963157400 date "2019-11-01" @default.
• W2963157400 modified "2023-09-26" @default.
• W2963157400 title "Identifying compliant participants through data matching improved estimation of intervention efficacy: randomized trials with opt-in/opt-out strategies" @default.
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• W2963157400 doi "https://doi.org/10.1016/j.jclinepi.2019.07.013" @default.
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