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Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention.
Lindau, Stacy Tessler; Makelarski, Jennifer A; Kaligotla, Chaitanya; Abramsohn, Emily M; Beiser, David G; Chou, Chiahung; Collier, Nicholson; Huang, Elbert S; Macal, Charles M; Ozik, Jonathan; Tung, Elizabeth L.
Afiliação
  • Lindau ST; Department of Obstetrics and Gynecology, University of Chicago, Chicago, Illinois, United States of America.
  • Makelarski JA; Comprehensive Cancer Center, University of Chicago, Chicago, Illinois, United States of America.
  • Kaligotla C; Department of Medicine, Section of Geriatrics & Palliative Medicine, University of Chicago, Chicago, Illinois, United States of America.
  • Abramsohn EM; Bucksbaum Institute for Clinical Excellence, University of Chicago, Chicago, Illinois, United States of America.
  • Beiser DG; Department of Obstetrics and Gynecology, University of Chicago, Chicago, Illinois, United States of America.
  • Chou C; Decision and Infrastructure Sciences Division, Argonne National Laboratory, Lemont, Illinois, United States of America.
  • Collier N; Beedie School of Business, Simon Fraser University, Burnaby, British Columbia, Canada.
  • Huang ES; Department of Obstetrics and Gynecology, University of Chicago, Chicago, Illinois, United States of America.
  • Macal CM; Section of Emergency Medicine, Department of Medicine, University of Chicago, Chicago, Illinois, United States of America.
  • Ozik J; Department of Health Outcomes Research and Policy, Auburn University, Auburn, Alabama, United States of America.
  • Tung EL; Decision and Infrastructure Sciences Division, Argonne National Laboratory, Lemont, Illinois, United States of America.
PLoS Comput Biol ; 17(10): e1009471, 2021 10.
Article em En | MEDLINE | ID: mdl-34695116
CommunityRx (CRx), an information technology intervention, provides patients with a personalized list of healthful community resources (HealtheRx). In repeated clinical studies, nearly half of those who received clinical "doses" of the HealtheRx shared their information with others ("social doses"). Clinical trial design cannot fully capture the impact of information diffusion, which can act as a force multiplier for the intervention. Furthermore, experimentation is needed to understand how intervention delivery can optimize social spread under varying circumstances. To study information diffusion from CRx under varying conditions, we built an agent-based model (ABM). This study describes the model building process and illustrates how an ABM provides insight about information diffusion through in silico experimentation. To build the ABM, we constructed a synthetic population ("agents") using publicly-available data sources. Using clinical trial data, we developed empirically-informed processes simulating agent activities, resource knowledge evolution and information sharing. Using RepastHPC and chiSIM software, we replicated the intervention in silico, simulated information diffusion processes, and generated emergent information diffusion networks. The CRx ABM was calibrated using empirical data to replicate the CRx intervention in silico. We used the ABM to quantify information spread via social versus clinical dosing then conducted information diffusion experiments, comparing the social dosing effect of the intervention when delivered by physicians, nurses or clinical clerks. The synthetic population (N = 802,191) exhibited diverse behavioral characteristics, including activity and knowledge evolution patterns. In silico delivery of the intervention was replicated with high fidelity. Large-scale information diffusion networks emerged among agents exchanging resource information. Varying the propensity for information exchange resulted in networks with different topological characteristics. Community resource information spread via social dosing was nearly 4 fold that from clinical dosing alone and did not vary by delivery mode. This study, using CRx as an example, demonstrates the process of building and experimenting with an ABM to study information diffusion from, and the population-level impact of, a clinical information-based intervention. While the focus of the CRx ABM is to recreate the CRx intervention in silico, the general process of model building, and computational experimentation presented is generalizable to other large-scale ABMs of information diffusion.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Encaminhamento e Consulta / Análise de Sistemas / Redes Comunitárias / Troca de Informação em Saúde Tipo de estudo: Prognostic_studies Limite: Adolescent / Adult / Aged / Aged80 / Humans / Male / Middle aged Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Encaminhamento e Consulta / Análise de Sistemas / Redes Comunitárias / Troca de Informação em Saúde Tipo de estudo: Prognostic_studies Limite: Adolescent / Adult / Aged / Aged80 / Humans / Male / Middle aged Idioma: En Ano de publicação: 2021 Tipo de documento: Article