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The health equity measurement framework: a comprehensive model to measure social inequities in health

BACKGROUND: Despite the wealth of frameworks on social determinants of health (SDOH), two current limitations include the relative superficial description of factors affecting health and a lack of focus on measuring health equity. The Health Equity Measurement Framework (HEMF) addresses these gaps b...

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Autores principales: Dover, Douglas C., Belon, Ana Paula
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6379929/
https://www.ncbi.nlm.nih.gov/pubmed/30782161
http://dx.doi.org/10.1186/s12939-019-0935-0
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author Dover, Douglas C.
Belon, Ana Paula
author_facet Dover, Douglas C.
Belon, Ana Paula
author_sort Dover, Douglas C.
collection PubMed
description BACKGROUND: Despite the wealth of frameworks on social determinants of health (SDOH), two current limitations include the relative superficial description of factors affecting health and a lack of focus on measuring health equity. The Health Equity Measurement Framework (HEMF) addresses these gaps by providing a more encompassing view of the multitude of SDOH and drivers of health service utilisation and by guiding quantitative analysis for public health surveillance and policy development. The objective of this paper is to present the HEMF, which was specifically designed to measure the direct and indirect effects of SDOH to support improved statistical modelling and measurement of health equity. METHODS: Based on a framework synthesis, the HEMF development involved initially integrating theoretical components from existing SDOH and health system utilisation frameworks. To further develop the framework, relevant publications on SDOH and health equity were identified through a literature review in major electronic databases. White and grey literatures were critically reviewed to identify strengths and gaps in the existing frameworks in order to inform the development of a unique health equity measurement framework. Finally, over a two-year period of consultation, scholars, health practitioners, and local policy influencers from municipal and provincial governments provided critical feedback on the framework regarding its components and causal relationships. RESULTS: This unified framework includes the socioeconomic, cultural, and political context, health policy context, social stratification, social location, material and social circumstances, environment, biological factors, health-related behaviours and beliefs, stress, quality of care, and healthcare utilisation. Alongside the HEMF’s self-exploratory diagram showing the causal pathways in-depth, a number of examples are provided to illustrate the framework’s usefulness in measuring and monitoring health equity as well as informing policy-making. CONCLUSIONS: The HEMF highlights intervention areas to be influenced by strategic public policy for any organisation whose purview has an effect on health, including helping non-health sectors (such as education and labour) to better understand how their policies influence population health and perceive their role in health equity promotion. The HEMF recognises the complexity surrounding the SDOH and provides a clear, overarching direction for empirical work on health equity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12939-019-0935-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-63799292019-02-28 The health equity measurement framework: a comprehensive model to measure social inequities in health Dover, Douglas C. Belon, Ana Paula Int J Equity Health Research BACKGROUND: Despite the wealth of frameworks on social determinants of health (SDOH), two current limitations include the relative superficial description of factors affecting health and a lack of focus on measuring health equity. The Health Equity Measurement Framework (HEMF) addresses these gaps by providing a more encompassing view of the multitude of SDOH and drivers of health service utilisation and by guiding quantitative analysis for public health surveillance and policy development. The objective of this paper is to present the HEMF, which was specifically designed to measure the direct and indirect effects of SDOH to support improved statistical modelling and measurement of health equity. METHODS: Based on a framework synthesis, the HEMF development involved initially integrating theoretical components from existing SDOH and health system utilisation frameworks. To further develop the framework, relevant publications on SDOH and health equity were identified through a literature review in major electronic databases. White and grey literatures were critically reviewed to identify strengths and gaps in the existing frameworks in order to inform the development of a unique health equity measurement framework. Finally, over a two-year period of consultation, scholars, health practitioners, and local policy influencers from municipal and provincial governments provided critical feedback on the framework regarding its components and causal relationships. RESULTS: This unified framework includes the socioeconomic, cultural, and political context, health policy context, social stratification, social location, material and social circumstances, environment, biological factors, health-related behaviours and beliefs, stress, quality of care, and healthcare utilisation. Alongside the HEMF’s self-exploratory diagram showing the causal pathways in-depth, a number of examples are provided to illustrate the framework’s usefulness in measuring and monitoring health equity as well as informing policy-making. CONCLUSIONS: The HEMF highlights intervention areas to be influenced by strategic public policy for any organisation whose purview has an effect on health, including helping non-health sectors (such as education and labour) to better understand how their policies influence population health and perceive their role in health equity promotion. The HEMF recognises the complexity surrounding the SDOH and provides a clear, overarching direction for empirical work on health equity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12939-019-0935-0) contains supplementary material, which is available to authorized users. BioMed Central 2019-02-19 /pmc/articles/PMC6379929/ /pubmed/30782161 http://dx.doi.org/10.1186/s12939-019-0935-0 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.
spellingShingle Research
Dover, Douglas C.
Belon, Ana Paula
The health equity measurement framework: a comprehensive model to measure social inequities in health
title The health equity measurement framework: a comprehensive model to measure social inequities in health
title_full The health equity measurement framework: a comprehensive model to measure social inequities in health
title_fullStr The health equity measurement framework: a comprehensive model to measure social inequities in health
title_full_unstemmed The health equity measurement framework: a comprehensive model to measure social inequities in health
title_short The health equity measurement framework: a comprehensive model to measure social inequities in health
title_sort health equity measurement framework: a comprehensive model to measure social inequities in health
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6379929/
https://www.ncbi.nlm.nih.gov/pubmed/30782161
http://dx.doi.org/10.1186/s12939-019-0935-0
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