Date of Award
Department or Program
Quantitative Biomedical Sciences
A. James O’Malley
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.
Ran, Xin, "MODELING THE BIDIRECTIONAL RELATIONSHIP BETWEEN SHARED-PATIENT PHYSICIAN NETWORKS AND PATIENT LONGITUDINAL TREATMENT PATTERNS: APPLICATION TO PHYSICIAN RISKY-PRESCRIBING" (2023). Dartmouth College Ph.D Dissertations. 134.
Available for download on Friday, February 16, 2024
Biostatistics Commons, Data Science Commons, Health Services Research Commons, Longitudinal Data Analysis and Time Series Commons, Pharmacy Administration, Policy and Regulation Commons, Research Methods in Life Sciences Commons, Statistical Methodology Commons, Statistical Models Commons