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Visualizing the drivers of an effective health workforce: a detailed, interactive logic model

BACKGROUND: A strong health workforce is a key building block of a well-functioning health system. To achieve health systems goals, policymakers need information on what works to improve and sustain health workforce performance. Most frameworks on health workforce planning and policymaking are high-...

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Autores principales: Sonderegger, Serena, Bennett, Sara, Sriram, Veena, Lalani, Ummekulsoom, Hariyani, Shreya, Roberton, Timothy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7953552/
https://www.ncbi.nlm.nih.gov/pubmed/33706778
http://dx.doi.org/10.1186/s12960-021-00570-7
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author Sonderegger, Serena
Bennett, Sara
Sriram, Veena
Lalani, Ummekulsoom
Hariyani, Shreya
Roberton, Timothy
author_facet Sonderegger, Serena
Bennett, Sara
Sriram, Veena
Lalani, Ummekulsoom
Hariyani, Shreya
Roberton, Timothy
author_sort Sonderegger, Serena
collection PubMed
description BACKGROUND: A strong health workforce is a key building block of a well-functioning health system. To achieve health systems goals, policymakers need information on what works to improve and sustain health workforce performance. Most frameworks on health workforce planning and policymaking are high-level and conceptual, and do not provide a structure for synthesizing the growing body of empirical literature on the effectiveness of strategies to strengthen human resources for health (HRH). Our aim is to create a detailed, interactive logic model to map HRH evidence and inform policy development and decision-making. METHODS: We reviewed existing conceptual frameworks and models on health workforce planning and policymaking. We included frameworks that were: (1) visual, (2) comprehensive (not concentrated on specific outcomes or strategies), and (3) designed to support decision-making. We compared and synthesized the frameworks to develop a detailed logic model and interactive evidence visualization tool. RESULTS: Ten frameworks met our inclusion criteria. The resulting logic model, available at hrhvisualizer.org, allows for visualization of high-level linkages as well as a detailed understanding of the factors that affect health workforce outcomes. HRH data and governance systems interact with the context to affect how human resource policies are formulated and implemented. These policies affect HRH processes and strategies that influence health workforce outcomes and contribute to the overarching health systems goals of clinical quality, responsiveness, efficiency, and coverage. Unlike existing conceptual frameworks, this logic model has been operationalized in a highly visual, interactive platform that can be used to map the research informing policies and illuminating their underlying mechanisms. CONCLUSIONS: The interactive logic model presented in this paper will allow for comprehensive mapping of literature around effective strategies to strengthen HRH. It can aid researchers in communicating with policymakers about the evidence behind policy questions, thus supporting the translation of evidence to policy.
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spelling pubmed-79535522021-03-12 Visualizing the drivers of an effective health workforce: a detailed, interactive logic model Sonderegger, Serena Bennett, Sara Sriram, Veena Lalani, Ummekulsoom Hariyani, Shreya Roberton, Timothy Hum Resour Health Research BACKGROUND: A strong health workforce is a key building block of a well-functioning health system. To achieve health systems goals, policymakers need information on what works to improve and sustain health workforce performance. Most frameworks on health workforce planning and policymaking are high-level and conceptual, and do not provide a structure for synthesizing the growing body of empirical literature on the effectiveness of strategies to strengthen human resources for health (HRH). Our aim is to create a detailed, interactive logic model to map HRH evidence and inform policy development and decision-making. METHODS: We reviewed existing conceptual frameworks and models on health workforce planning and policymaking. We included frameworks that were: (1) visual, (2) comprehensive (not concentrated on specific outcomes or strategies), and (3) designed to support decision-making. We compared and synthesized the frameworks to develop a detailed logic model and interactive evidence visualization tool. RESULTS: Ten frameworks met our inclusion criteria. The resulting logic model, available at hrhvisualizer.org, allows for visualization of high-level linkages as well as a detailed understanding of the factors that affect health workforce outcomes. HRH data and governance systems interact with the context to affect how human resource policies are formulated and implemented. These policies affect HRH processes and strategies that influence health workforce outcomes and contribute to the overarching health systems goals of clinical quality, responsiveness, efficiency, and coverage. Unlike existing conceptual frameworks, this logic model has been operationalized in a highly visual, interactive platform that can be used to map the research informing policies and illuminating their underlying mechanisms. CONCLUSIONS: The interactive logic model presented in this paper will allow for comprehensive mapping of literature around effective strategies to strengthen HRH. It can aid researchers in communicating with policymakers about the evidence behind policy questions, thus supporting the translation of evidence to policy. BioMed Central 2021-03-12 /pmc/articles/PMC7953552/ /pubmed/33706778 http://dx.doi.org/10.1186/s12960-021-00570-7 Text en © The Author(s) 2021 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/. The Creative Commons Public Domain Dedication waiver (http://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
Sonderegger, Serena
Bennett, Sara
Sriram, Veena
Lalani, Ummekulsoom
Hariyani, Shreya
Roberton, Timothy
Visualizing the drivers of an effective health workforce: a detailed, interactive logic model
title Visualizing the drivers of an effective health workforce: a detailed, interactive logic model
title_full Visualizing the drivers of an effective health workforce: a detailed, interactive logic model
title_fullStr Visualizing the drivers of an effective health workforce: a detailed, interactive logic model
title_full_unstemmed Visualizing the drivers of an effective health workforce: a detailed, interactive logic model
title_short Visualizing the drivers of an effective health workforce: a detailed, interactive logic model
title_sort visualizing the drivers of an effective health workforce: a detailed, interactive logic model
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7953552/
https://www.ncbi.nlm.nih.gov/pubmed/33706778
http://dx.doi.org/10.1186/s12960-021-00570-7
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