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Measuring engagement in a collaborative learning health system: The case of ImproveCareNow

BACKGROUND: Collaborative learning health systems have demonstrated improved outcomes for a range of different chronic conditions. Patient and healthcare provider engagement in these systems is thought to be associated with improved outcomes. We have adapted an observational framework to measure, an...

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Autores principales: Hartley, David M., Keck, Christian, Havens, Mary, Margolis, Peter A., Seid, Michael
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/PMC8051351/
https://www.ncbi.nlm.nih.gov/pubmed/33889734
http://dx.doi.org/10.1002/lrh2.10225
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author Hartley, David M.
Keck, Christian
Havens, Mary
Margolis, Peter A.
Seid, Michael
author_facet Hartley, David M.
Keck, Christian
Havens, Mary
Margolis, Peter A.
Seid, Michael
author_sort Hartley, David M.
collection PubMed
description BACKGROUND: Collaborative learning health systems have demonstrated improved outcomes for a range of different chronic conditions. Patient and healthcare provider engagement in these systems is thought to be associated with improved outcomes. We have adapted an observational framework to measure, and track over time, engagement in ImproveCareNow, a collaborative learning health system for children with inflammatory bowel disease. INTRODUCTION: We developed a categorical classification scheme for engagement in ImproveCareNow. Each tier is defined in terms of observable individual behaviors. When an individual completes one or more qualifying behavior, s/he is classified as engaged at that tier. Individuals are entered into a database, which is accessible to care centers throughout the ImproveCareNow network. Database records include fields for individual name, behavior type, time, place, and level of engagement. RESULTS: The resulting system is employed at 79 ImproveCareNow care centers in the United States. The system recognizes four levels of engagement. Behaviors are recorded in a managed vocabulary and recorded in an online database. The database is queried weekly for individual engagement behaviors, which are tracked longitudinally. Center‐ and network‐level statistics are generated and disseminated to stakeholders. CONCLUSION: It is possible to monitor longitudinal engagement in a collaborative learning health system, thereby charting progress toward engagement goals and enabling quantitative evaluation of interventions aimed at increasing engagement.
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spelling pubmed-80513512021-04-21 Measuring engagement in a collaborative learning health system: The case of ImproveCareNow Hartley, David M. Keck, Christian Havens, Mary Margolis, Peter A. Seid, Michael Learn Health Syst Experience Reports BACKGROUND: Collaborative learning health systems have demonstrated improved outcomes for a range of different chronic conditions. Patient and healthcare provider engagement in these systems is thought to be associated with improved outcomes. We have adapted an observational framework to measure, and track over time, engagement in ImproveCareNow, a collaborative learning health system for children with inflammatory bowel disease. INTRODUCTION: We developed a categorical classification scheme for engagement in ImproveCareNow. Each tier is defined in terms of observable individual behaviors. When an individual completes one or more qualifying behavior, s/he is classified as engaged at that tier. Individuals are entered into a database, which is accessible to care centers throughout the ImproveCareNow network. Database records include fields for individual name, behavior type, time, place, and level of engagement. RESULTS: The resulting system is employed at 79 ImproveCareNow care centers in the United States. The system recognizes four levels of engagement. Behaviors are recorded in a managed vocabulary and recorded in an online database. The database is queried weekly for individual engagement behaviors, which are tracked longitudinally. Center‐ and network‐level statistics are generated and disseminated to stakeholders. CONCLUSION: It is possible to monitor longitudinal engagement in a collaborative learning health system, thereby charting progress toward engagement goals and enabling quantitative evaluation of interventions aimed at increasing engagement. John Wiley and Sons Inc. 2020-04-06 /pmc/articles/PMC8051351/ /pubmed/33889734 http://dx.doi.org/10.1002/lrh2.10225 Text en © 2020 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of the University of Michigan. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Experience Reports
Hartley, David M.
Keck, Christian
Havens, Mary
Margolis, Peter A.
Seid, Michael
Measuring engagement in a collaborative learning health system: The case of ImproveCareNow
title Measuring engagement in a collaborative learning health system: The case of ImproveCareNow
title_full Measuring engagement in a collaborative learning health system: The case of ImproveCareNow
title_fullStr Measuring engagement in a collaborative learning health system: The case of ImproveCareNow
title_full_unstemmed Measuring engagement in a collaborative learning health system: The case of ImproveCareNow
title_short Measuring engagement in a collaborative learning health system: The case of ImproveCareNow
title_sort measuring engagement in a collaborative learning health system: the case of improvecarenow
topic Experience Reports
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8051351/
https://www.ncbi.nlm.nih.gov/pubmed/33889734
http://dx.doi.org/10.1002/lrh2.10225
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