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Causal Inference for Intervention Spillover in a Stepped Wedge Cluster-randomized Trial: Lessons from a Physician
A James O'Malley1,2, Carly A Bobak2,3, Amber E Barnato1
1The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth College, Street, Lebanon, 03756, NH, USA.
Abstract:
Often motivated by concerns about contamination of control subjects, stepped wedge cluster-randomized trial designs assign interventions to distinct clusters (e.g., hospitals) and protect against confounding by randomizing the timing of intervention delivery. However, when trial units are embedded in professional networks that span clusters, such designs cannot prevent spillover. In this study, we use longitudinal cluster-randomized trial data and contemporaneous physician networks to estimate the direct, indirect and direct-indirect interaction effects of an advance care planning (ACP) intervention. The direct effect reflects the intervention's impact in a counterfactual world absent contamination, the indirect effect captures spillover to control subjects, and the interaction effect assesses whether spillover modifies the intervention's effect, a phenomenon known as contamination. In addition, we exploit the staggered nature of the stepped-wedge design to test whether intervened peers impact the sustainment of the intervention over follow-up and, specifically, of whether spillover reinforces or attenuates the intervention. On a national provider organization's physician network, we find that accounting for spillover and contamination had a profound effect on the direct effect of the intervention. We also found evidence that physician spillover effects reinforced the intervention over follow-up. These findings suggest that the diffusion of the intervention's effect through the network was primarily driven by a large physician spillover effect that modified the direct effect at the time of intervention and subsequently over follow-up.
