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Connecting community‐delivered evidence‐based programs and the healthcare system: Piloting a learning “wellcare” system

INTRODUCTION: Many evidence‐based programs (EBPs) have been determined in randomized controlled trials to be effective, but few studies explore the real‐world effectiveness of EBPs implemented in the natural community setting. Our study evaluated whether a novel linked infrastructure would enable su...

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Autores principales: Redmond, Sarah, Leppin, Aaron L., Fischer, Karen, Hanson, Gregory, Doubeni, Chyke, Takahashi, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8512735/
https://www.ncbi.nlm.nih.gov/pubmed/34667870
http://dx.doi.org/10.1002/lrh2.10240
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author Redmond, Sarah
Leppin, Aaron L.
Fischer, Karen
Hanson, Gregory
Doubeni, Chyke
Takahashi, Paul
author_facet Redmond, Sarah
Leppin, Aaron L.
Fischer, Karen
Hanson, Gregory
Doubeni, Chyke
Takahashi, Paul
author_sort Redmond, Sarah
collection PubMed
description INTRODUCTION: Many evidence‐based programs (EBPs) have been determined in randomized controlled trials to be effective, but few studies explore the real‐world effectiveness of EBPs implemented in the natural community setting. Our study evaluated whether a novel linked infrastructure would enable such insights and continuous improvement as part of a learning healthcare‐community bridged “wellcare” ecosystem. METHODS: We created a secure, web‐based data entry and storage platform with a network of Minnesota community‐based organizations to record EBP participants' demographics and attendance, and program details. We then linked participant's information to their Rochester Epidemiology Project (REP) medical records. With this infrastructure, we conducted a proof of concept, retrospective cohort study by matching EBP participants to REP controls and comparing medical record‐documented outcomes over 1 year follow‐up. RESULTS: We successfully linked EBP participant records with medical records in 77.6% of cases, and the infrastructure proved feasible and scalable. Still, key challenges remain in obtaining participant consent for data sharing. Upfront resource investments and the availability of REP‐like warehouses limit generalizability. Optimal learning will be improved by enhancements that better track program fidelity. Our pilot study established a proof‐of‐concept, but sample sizes (n = 99 for falls prevention and n = 97 chronic disease/pain management EBP completers) were too small to detect significant differences in hospital admittance as compared to matched controls for either EBP group, (OR = 0.66[0.36, 1.19]) and (OR = 0.81[0.43, 1.54]), respectively. Events were too rare to gather meaningful information about effects on fall rates. CONCLUSIONS: Our pilot demonstrates the feasibility of developing an online infrastructure that connects information from community leaders with medical record documented health outcomes, bridging the knowledge gap between community programs and the health care system. Insights gleaned from our infrastructure can be used to continuously shape community program delivery to reduce the need for formal health care services.
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spelling pubmed-85127352021-10-18 Connecting community‐delivered evidence‐based programs and the healthcare system: Piloting a learning “wellcare” system Redmond, Sarah Leppin, Aaron L. Fischer, Karen Hanson, Gregory Doubeni, Chyke Takahashi, Paul Learn Health Syst Research Reports INTRODUCTION: Many evidence‐based programs (EBPs) have been determined in randomized controlled trials to be effective, but few studies explore the real‐world effectiveness of EBPs implemented in the natural community setting. Our study evaluated whether a novel linked infrastructure would enable such insights and continuous improvement as part of a learning healthcare‐community bridged “wellcare” ecosystem. METHODS: We created a secure, web‐based data entry and storage platform with a network of Minnesota community‐based organizations to record EBP participants' demographics and attendance, and program details. We then linked participant's information to their Rochester Epidemiology Project (REP) medical records. With this infrastructure, we conducted a proof of concept, retrospective cohort study by matching EBP participants to REP controls and comparing medical record‐documented outcomes over 1 year follow‐up. RESULTS: We successfully linked EBP participant records with medical records in 77.6% of cases, and the infrastructure proved feasible and scalable. Still, key challenges remain in obtaining participant consent for data sharing. Upfront resource investments and the availability of REP‐like warehouses limit generalizability. Optimal learning will be improved by enhancements that better track program fidelity. Our pilot study established a proof‐of‐concept, but sample sizes (n = 99 for falls prevention and n = 97 chronic disease/pain management EBP completers) were too small to detect significant differences in hospital admittance as compared to matched controls for either EBP group, (OR = 0.66[0.36, 1.19]) and (OR = 0.81[0.43, 1.54]), respectively. Events were too rare to gather meaningful information about effects on fall rates. CONCLUSIONS: Our pilot demonstrates the feasibility of developing an online infrastructure that connects information from community leaders with medical record documented health outcomes, bridging the knowledge gap between community programs and the health care system. Insights gleaned from our infrastructure can be used to continuously shape community program delivery to reduce the need for formal health care services. John Wiley and Sons Inc. 2020-08-18 /pmc/articles/PMC8512735/ /pubmed/34667870 http://dx.doi.org/10.1002/lrh2.10240 Text en © 2020 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of University of Michigan. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Reports
Redmond, Sarah
Leppin, Aaron L.
Fischer, Karen
Hanson, Gregory
Doubeni, Chyke
Takahashi, Paul
Connecting community‐delivered evidence‐based programs and the healthcare system: Piloting a learning “wellcare” system
title Connecting community‐delivered evidence‐based programs and the healthcare system: Piloting a learning “wellcare” system
title_full Connecting community‐delivered evidence‐based programs and the healthcare system: Piloting a learning “wellcare” system
title_fullStr Connecting community‐delivered evidence‐based programs and the healthcare system: Piloting a learning “wellcare” system
title_full_unstemmed Connecting community‐delivered evidence‐based programs and the healthcare system: Piloting a learning “wellcare” system
title_short Connecting community‐delivered evidence‐based programs and the healthcare system: Piloting a learning “wellcare” system
title_sort connecting community‐delivered evidence‐based programs and the healthcare system: piloting a learning “wellcare” system
topic Research Reports
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8512735/
https://www.ncbi.nlm.nih.gov/pubmed/34667870
http://dx.doi.org/10.1002/lrh2.10240
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