MODELING THE BIDIRECTIONAL RELATIONSHIP BETWEEN SHARED-PATIENT PHYSICIAN NETWORKS AND PATIENT LONGITUDINAL TREATMENT PATTERNS: APPLICATION TO PHYSICIAN RISKY-PRESCRIBING

Risky-prescribing is a pressing public health concern in the United States. Opioids, benzodiazepines, and non-benzodiazepine sedative-hypnotics (sedative-hypnotics) are three commonly-prescribed but potentially risky drug groups, prescribed alone or in combination. Physician shared-patient networks provide a unique perspective in studying physician network characteristics and structures, as well as their association with the delivery of health care. Understanding how physician shared-patient networks are related to their prescribing may inform network-based interventions targeting risky-prescribing, which is yet to be fully studied.We investigated patient receipt of risky prescriptions and physician risky-prescribing intensity through the scope of shared-patient networks. We used retrospective Medicare insurance claims data to 1) model patient longitudinal prescription fills as transitions between prescription states; 2) study the association of physician structural prominence in a shared-patient physician network with patient receipt of risky drug combinations; 3) develop heuristic algorithms to identify the responsible deprescribing physician and quantify physician prescribing and deprescribing behaviors through a variety of measures; 4) study physician homophily effects of risky-prescribing and deprescribing in a shared-patient physician network; 5) decompose peer effects into directional components with the help of directed shared-patient networks and study the diffusion of risky-prescribing in the networks. Our studies highlight the potential of network-based interventions to improving prescribing quality.