Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention.

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 ("...

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Autores principales:	Stacy Tessler Lindau, Jennifer A Makelarski, Chaitanya Kaligotla, Emily M Abramsohn, David G Beiser, Chiahung Chou, Nicholson Collier, Elbert S Huang, Charles M Macal, Jonathan Ozik, Elizabeth L Tung
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/041fbc51e4df4b0a9adb8bb63162b61c
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spelling	oai:doaj.org-article:041fbc51e4df4b0a9adb8bb63162b61c2021-12-02T19:57:41ZBuilding and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention.1553-734X1553-735810.1371/journal.pcbi.1009471https://doaj.org/article/041fbc51e4df4b0a9adb8bb63162b61c2021-10-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009471https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358CommunityRx (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.Stacy Tessler LindauJennifer A MakelarskiChaitanya KaligotlaEmily M AbramsohnDavid G BeiserChiahung ChouNicholson CollierElbert S HuangCharles M MacalJonathan OzikElizabeth L TungPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 10, p e1009471 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Stacy Tessler Lindau Jennifer A Makelarski Chaitanya Kaligotla Emily M Abramsohn David G Beiser Chiahung Chou Nicholson Collier Elbert S Huang Charles M Macal Jonathan Ozik Elizabeth L Tung Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention.
description	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.
format	article
author	Stacy Tessler Lindau Jennifer A Makelarski Chaitanya Kaligotla Emily M Abramsohn David G Beiser Chiahung Chou Nicholson Collier Elbert S Huang Charles M Macal Jonathan Ozik Elizabeth L Tung
author_facet	Stacy Tessler Lindau Jennifer A Makelarski Chaitanya Kaligotla Emily M Abramsohn David G Beiser Chiahung Chou Nicholson Collier Elbert S Huang Charles M Macal Jonathan Ozik Elizabeth L Tung
author_sort	Stacy Tessler Lindau
title	Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention.
title_short	Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention.
title_full	Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention.
title_fullStr	Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention.
title_full_unstemmed	Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention.
title_sort	building and experimenting with an agent-based model to study the population-level impact of communityrx, a clinic-based community resource referral intervention.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/041fbc51e4df4b0a9adb8bb63162b61c
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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.

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