Statistics in Medicine

Modeling peer effect modification by network strength: The diffusion of implantable cardioverter defibrillators in the US hospital network

Statistics in Medicine

A. James O'Malley, Erika L. Moen, Julie P. W. Bynum, Andrea M. Austin, Jonathan S. Skinner

We develop methodology that allows peer effects (also referred to as social influ- ence and contagion) to be modified by the structural importance of the focal actor's position in the network. The methodology is first developed for a sin- gle peer effect and then extended to simultaneously model multiple peer-effects and their modifications by the structural importance of the focal actor. This work is motivated by the diffusion of implantable cardioverter defibrillators (ICDs) in patients with congestive heart failure across a cardiovascular dis- ease patient-sharing network of United States hospitals. We apply the general methodology to estimate peer effects for the adoption of capability to implant ICDs, the number of ICD implants performed by hospitals that are capable, and the number of patients referred to other hospitals by noncapable hospi- tals. Applying our novel methodology to study ICD diffusion across hospitals, we find evidence that exposure to ICD-capable peer hospitals is strongly asso- ciated with the chance a hospital becomes ICD-capable and that the direction and magnitude of the association is extensively modified by the strength of that hospital's position in the network, even after controlling for effects of geography. Therefore, interhospital networks, rather than geography per se, may explain key patterns of regional variations in healthcare utilization.

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