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A framework of evidence-based decision-making in health system management: a best-fit framework synthesis
BACKGROUND: Scientific evidence is the basis for improving public health; decision-making without sufficient attention to evidence may lead to unpleasant consequences. Despite efforts to create comprehensive guidelines and models for evidence-based decision-making (EBDM), there isn`t any to make the...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8961960/ https://www.ncbi.nlm.nih.gov/pubmed/35351210 http://dx.doi.org/10.1186/s13690-022-00843-0 |
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author | Shafaghat, Tahereh Bastani, Peivand Nasab, Mohammad Hasan Imani Bahrami, Mohammad Amin Montazer, Mahsa Roozrokh Arshadi Zarchi, Mohammad Kazem Rahimi Edirippulige, Sisira |
author_facet | Shafaghat, Tahereh Bastani, Peivand Nasab, Mohammad Hasan Imani Bahrami, Mohammad Amin Montazer, Mahsa Roozrokh Arshadi Zarchi, Mohammad Kazem Rahimi Edirippulige, Sisira |
author_sort | Shafaghat, Tahereh |
collection | PubMed |
description | BACKGROUND: Scientific evidence is the basis for improving public health; decision-making without sufficient attention to evidence may lead to unpleasant consequences. Despite efforts to create comprehensive guidelines and models for evidence-based decision-making (EBDM), there isn`t any to make the best decisions concerning scarce resources and unlimited needs. The present study aimed to develop a comprehensive applied framework for EBDM. METHODS: This was a Best-Fit Framework (BFF) synthesis conducted in 2020. A comprehensive systematic review was done via six main databases including PUBMED, Scopus, Web of Science, Science Direct, EMBASE, and ProQuest using related keywords. After the evidence quality appraisal, data were extracted and analyzed via thematic analysis. Results of the thematic analysis and the concepts generated by the research team were then synthesized to achieve the best-fit framework applying Carroll et al. (2013) approach. RESULTS: Four thousand six hundred thirteen studies were retrieved, and due to the full-text screening of the studies, 17 final articles were selected for extracting the components and steps of EBDM in Health System Management (HSM). After collecting, synthesizing, and categorizing key information, the framework of EBDM in HSM was developed in the form of four general scopes. These comprised inquiring, inspecting, implementing, and integrating, which included 10 main steps and 47 sub-steps. CONCLUSIONS: The present framework provided a comprehensive guideline that can be well adapted for implementing EBDM in health systems and related organizations especially in underdeveloped and developing countries where there is usually a lag in updating and applying evidence in their decision-making process. In addition, this framework by providing a complete, well-detailed, and the sequential process can be tested in the organizational decision-making process by developed countries to improve their EBDM cycle. |
format | Online Article Text |
id | pubmed-8961960 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-89619602022-03-30 A framework of evidence-based decision-making in health system management: a best-fit framework synthesis Shafaghat, Tahereh Bastani, Peivand Nasab, Mohammad Hasan Imani Bahrami, Mohammad Amin Montazer, Mahsa Roozrokh Arshadi Zarchi, Mohammad Kazem Rahimi Edirippulige, Sisira Arch Public Health Research BACKGROUND: Scientific evidence is the basis for improving public health; decision-making without sufficient attention to evidence may lead to unpleasant consequences. Despite efforts to create comprehensive guidelines and models for evidence-based decision-making (EBDM), there isn`t any to make the best decisions concerning scarce resources and unlimited needs. The present study aimed to develop a comprehensive applied framework for EBDM. METHODS: This was a Best-Fit Framework (BFF) synthesis conducted in 2020. A comprehensive systematic review was done via six main databases including PUBMED, Scopus, Web of Science, Science Direct, EMBASE, and ProQuest using related keywords. After the evidence quality appraisal, data were extracted and analyzed via thematic analysis. Results of the thematic analysis and the concepts generated by the research team were then synthesized to achieve the best-fit framework applying Carroll et al. (2013) approach. RESULTS: Four thousand six hundred thirteen studies were retrieved, and due to the full-text screening of the studies, 17 final articles were selected for extracting the components and steps of EBDM in Health System Management (HSM). After collecting, synthesizing, and categorizing key information, the framework of EBDM in HSM was developed in the form of four general scopes. These comprised inquiring, inspecting, implementing, and integrating, which included 10 main steps and 47 sub-steps. CONCLUSIONS: The present framework provided a comprehensive guideline that can be well adapted for implementing EBDM in health systems and related organizations especially in underdeveloped and developing countries where there is usually a lag in updating and applying evidence in their decision-making process. In addition, this framework by providing a complete, well-detailed, and the sequential process can be tested in the organizational decision-making process by developed countries to improve their EBDM cycle. BioMed Central 2022-03-29 /pmc/articles/PMC8961960/ /pubmed/35351210 http://dx.doi.org/10.1186/s13690-022-00843-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Shafaghat, Tahereh Bastani, Peivand Nasab, Mohammad Hasan Imani Bahrami, Mohammad Amin Montazer, Mahsa Roozrokh Arshadi Zarchi, Mohammad Kazem Rahimi Edirippulige, Sisira A framework of evidence-based decision-making in health system management: a best-fit framework synthesis |
title | A framework of evidence-based decision-making in health system management: a best-fit framework synthesis |
title_full | A framework of evidence-based decision-making in health system management: a best-fit framework synthesis |
title_fullStr | A framework of evidence-based decision-making in health system management: a best-fit framework synthesis |
title_full_unstemmed | A framework of evidence-based decision-making in health system management: a best-fit framework synthesis |
title_short | A framework of evidence-based decision-making in health system management: a best-fit framework synthesis |
title_sort | framework of evidence-based decision-making in health system management: a best-fit framework synthesis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8961960/ https://www.ncbi.nlm.nih.gov/pubmed/35351210 http://dx.doi.org/10.1186/s13690-022-00843-0 |
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