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Balancing reality in embedded research and evaluation: Low vs high embeddedness
Embedding research and evaluation into organizations is one way to generate “practice‐based” evidence needed to accelerate implementation of evidence‐based innovations within learning health systems. Organizations and researchers/evaluators vary greatly in how they structure and operationalize these...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9006533/ https://www.ncbi.nlm.nih.gov/pubmed/35434356 http://dx.doi.org/10.1002/lrh2.10294 |
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author | Jackson, George L. Damschroder, Laura J. White, Brandolyn S. Henderson, Blake Vega, Ryan J. Kilbourne, Amy M. Cutrona, Sarah L. |
author_facet | Jackson, George L. Damschroder, Laura J. White, Brandolyn S. Henderson, Blake Vega, Ryan J. Kilbourne, Amy M. Cutrona, Sarah L. |
author_sort | Jackson, George L. |
collection | PubMed |
description | Embedding research and evaluation into organizations is one way to generate “practice‐based” evidence needed to accelerate implementation of evidence‐based innovations within learning health systems. Organizations and researchers/evaluators vary greatly in how they structure and operationalize these collaborations. One key aspect is the degree of embeddedness: from low embeddedness where researchers/evaluators are located outside organizations (eg, outside evaluation consultants) to high embeddedness where researchers/evaluators are employed by organizations and thus more deeply involved in program evolution and operations. Pros and cons related to the degree of embeddedness (low vs high) must be balanced when developing these relationships. We reflect on this process within the context of an embedded, mixed‐methods evaluation of the Veterans Health Administration (VHA) Diffusion of Excellence (DoE) program. Considerations that must be balanced include: (a) low vs high alignment of goals; (b) low vs high involvement in strategic planning; (c) observing what is happening vs being integrally involved with programmatic activities; (d) reporting findings at the project's end vs providing iterative findings and recommendations that contribute to program evolution; and (e) adhering to predetermined aims vs adapting aims in response to evolving partner needs. |
format | Online Article Text |
id | pubmed-9006533 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90065332022-04-15 Balancing reality in embedded research and evaluation: Low vs high embeddedness Jackson, George L. Damschroder, Laura J. White, Brandolyn S. Henderson, Blake Vega, Ryan J. Kilbourne, Amy M. Cutrona, Sarah L. Learn Health Syst Commentary Embedding research and evaluation into organizations is one way to generate “practice‐based” evidence needed to accelerate implementation of evidence‐based innovations within learning health systems. Organizations and researchers/evaluators vary greatly in how they structure and operationalize these collaborations. One key aspect is the degree of embeddedness: from low embeddedness where researchers/evaluators are located outside organizations (eg, outside evaluation consultants) to high embeddedness where researchers/evaluators are employed by organizations and thus more deeply involved in program evolution and operations. Pros and cons related to the degree of embeddedness (low vs high) must be balanced when developing these relationships. We reflect on this process within the context of an embedded, mixed‐methods evaluation of the Veterans Health Administration (VHA) Diffusion of Excellence (DoE) program. Considerations that must be balanced include: (a) low vs high alignment of goals; (b) low vs high involvement in strategic planning; (c) observing what is happening vs being integrally involved with programmatic activities; (d) reporting findings at the project's end vs providing iterative findings and recommendations that contribute to program evolution; and (e) adhering to predetermined aims vs adapting aims in response to evolving partner needs. John Wiley and Sons Inc. 2021-11-03 /pmc/articles/PMC9006533/ /pubmed/35434356 http://dx.doi.org/10.1002/lrh2.10294 Text en Published 2021. This article is a U.S. Government work and is in the public domain in the USA. Learning Health Systems published by Wiley Periodicals LLC on behalf of University of Michigan. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Commentary Jackson, George L. Damschroder, Laura J. White, Brandolyn S. Henderson, Blake Vega, Ryan J. Kilbourne, Amy M. Cutrona, Sarah L. Balancing reality in embedded research and evaluation: Low vs high embeddedness |
title | Balancing reality in embedded research and evaluation: Low vs high embeddedness |
title_full | Balancing reality in embedded research and evaluation: Low vs high embeddedness |
title_fullStr | Balancing reality in embedded research and evaluation: Low vs high embeddedness |
title_full_unstemmed | Balancing reality in embedded research and evaluation: Low vs high embeddedness |
title_short | Balancing reality in embedded research and evaluation: Low vs high embeddedness |
title_sort | balancing reality in embedded research and evaluation: low vs high embeddedness |
topic | Commentary |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9006533/ https://www.ncbi.nlm.nih.gov/pubmed/35434356 http://dx.doi.org/10.1002/lrh2.10294 |
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