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Predicting health services utilization using a score of perceived barriers to medical care: evidence from rural Senegal
BACKGROUND: Ensuring access to healthcare services is a key element to achieving the Sustainable Development Goal 3 of “promoting healthy lives and well-being for all” through Universal Health Coverage (UHC). However, in the context of low- and middle-income countries, most studies focused on financ...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018867/ https://www.ncbi.nlm.nih.gov/pubmed/36927564 http://dx.doi.org/10.1186/s12913-023-09192-2 |
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author | Coste, Marion Bousmah, Marwân-al-Qays |
author_facet | Coste, Marion Bousmah, Marwân-al-Qays |
author_sort | Coste, Marion |
collection | PubMed |
description | BACKGROUND: Ensuring access to healthcare services is a key element to achieving the Sustainable Development Goal 3 of “promoting healthy lives and well-being for all” through Universal Health Coverage (UHC). However, in the context of low- and middle-income countries, most studies focused on financial protection measured through catastrophic health expenditures (CHE), or on health services utilization among specific populations exhibiting health needs (such as pregnancy or recent sickness). METHODS: This study aims at building an individual score of perceived barriers to medical care (PBMC) in order to predict primary care utilization (or non-utilization). We estimate the score on six items: (1) knowing where to go, (2) getting permission, (3) having money, (4) distance to the facility, (5) finding transport, and (6) not wanting to go alone, using individual data from 1787 adult participants living in rural Senegal. We build the score via a stepwise descendent explanatory factor analysis (EFA), and assess its internal consistency. Finally, we assess the construct validity of the factor-based score by testing its association (univariate regressions) with a wide range of variables on determinants of healthcare-seeking, and evaluate its predictive validity for primary care utilization. RESULTS: EFA yields a one-dimensional score combining four items with a 0.7 Cronbach’s alpha indicating good internal consistency. The score is strongly associated—p-values significant at the 5% level—with determinants of healthcare-seeking (including, but not limited to, sex, education, marital status, poverty, and distance to the health facility). Additionally, the score can predict non-utilization of primary care at the household level, utilization and non-utilization of primary care following an individual’s episode of illness, and utilization of primary care during pregnancy and birth. These results are robust to the use of a different dataset. CONCLUSION: As a valid, sensitive, and easily documented individual-level indicator, the PBMC score can be a complement to regional or national level health services coverage to measure health services access and predict utilization. At the individual or household level, the PBMC score can also be combined with conventional metrics of financial risk protection such as CHE to comprehensively document deficits in, and progress towards UHC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-09192-2. |
format | Online Article Text |
id | pubmed-10018867 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-100188672023-03-17 Predicting health services utilization using a score of perceived barriers to medical care: evidence from rural Senegal Coste, Marion Bousmah, Marwân-al-Qays BMC Health Serv Res Research BACKGROUND: Ensuring access to healthcare services is a key element to achieving the Sustainable Development Goal 3 of “promoting healthy lives and well-being for all” through Universal Health Coverage (UHC). However, in the context of low- and middle-income countries, most studies focused on financial protection measured through catastrophic health expenditures (CHE), or on health services utilization among specific populations exhibiting health needs (such as pregnancy or recent sickness). METHODS: This study aims at building an individual score of perceived barriers to medical care (PBMC) in order to predict primary care utilization (or non-utilization). We estimate the score on six items: (1) knowing where to go, (2) getting permission, (3) having money, (4) distance to the facility, (5) finding transport, and (6) not wanting to go alone, using individual data from 1787 adult participants living in rural Senegal. We build the score via a stepwise descendent explanatory factor analysis (EFA), and assess its internal consistency. Finally, we assess the construct validity of the factor-based score by testing its association (univariate regressions) with a wide range of variables on determinants of healthcare-seeking, and evaluate its predictive validity for primary care utilization. RESULTS: EFA yields a one-dimensional score combining four items with a 0.7 Cronbach’s alpha indicating good internal consistency. The score is strongly associated—p-values significant at the 5% level—with determinants of healthcare-seeking (including, but not limited to, sex, education, marital status, poverty, and distance to the health facility). Additionally, the score can predict non-utilization of primary care at the household level, utilization and non-utilization of primary care following an individual’s episode of illness, and utilization of primary care during pregnancy and birth. These results are robust to the use of a different dataset. CONCLUSION: As a valid, sensitive, and easily documented individual-level indicator, the PBMC score can be a complement to regional or national level health services coverage to measure health services access and predict utilization. At the individual or household level, the PBMC score can also be combined with conventional metrics of financial risk protection such as CHE to comprehensively document deficits in, and progress towards UHC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-09192-2. BioMed Central 2023-03-16 /pmc/articles/PMC10018867/ /pubmed/36927564 http://dx.doi.org/10.1186/s12913-023-09192-2 Text en © The Author(s) 2023 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 Coste, Marion Bousmah, Marwân-al-Qays Predicting health services utilization using a score of perceived barriers to medical care: evidence from rural Senegal |
title | Predicting health services utilization using a score of perceived barriers to medical care: evidence from rural Senegal |
title_full | Predicting health services utilization using a score of perceived barriers to medical care: evidence from rural Senegal |
title_fullStr | Predicting health services utilization using a score of perceived barriers to medical care: evidence from rural Senegal |
title_full_unstemmed | Predicting health services utilization using a score of perceived barriers to medical care: evidence from rural Senegal |
title_short | Predicting health services utilization using a score of perceived barriers to medical care: evidence from rural Senegal |
title_sort | predicting health services utilization using a score of perceived barriers to medical care: evidence from rural senegal |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018867/ https://www.ncbi.nlm.nih.gov/pubmed/36927564 http://dx.doi.org/10.1186/s12913-023-09192-2 |
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