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Predicting health services utilization using a score of perceived barriers to medical care: evidence from rural Senegal

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  • Marion Coste

    (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique, SESSTIM - U1252 INSERM - Aix Marseille Univ - UMR 259 IRD - Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale - IRD - Institut de Recherche pour le Développement - AMU - Aix Marseille Université - INSERM - Institut National de la Santé et de la Recherche Médicale, ISSPAM - Institut des sciences de la santé publique [Marseille])

  • Marwân-Al-Qays Bousmah

    (SESSTIM - U1252 INSERM - Aix Marseille Univ - UMR 259 IRD - Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale - IRD - Institut de Recherche pour le Développement - AMU - Aix Marseille Université - INSERM - Institut National de la Santé et de la Recherche Médicale, CEPED - UMR_D 196 - Centre population et développement - IRD - Institut de Recherche pour le Développement - UPCité - Université Paris Cité, ISSPAM - Institut des sciences de la santé publique [Marseille])

Abstract

BackgroundEnsuring 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).MethodsThis 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.ResultsEFA 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.ConclusionAs 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.

Suggested Citation

  • Marion Coste & Marwân-Al-Qays Bousmah, 2023. "Predicting health services utilization using a score of perceived barriers to medical care: evidence from rural Senegal," Post-Print hal-04069039, HAL.
  • Handle: RePEc:hal:journl:hal-04069039
    DOI: 10.1186/s12913-023-09192-2
    Note: View the original document on HAL open archive server: https://amu.hal.science/hal-04069039
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    1. Getayeneh Antehunegn Tesema & Zemenu Tadesse Tessema, 2021. "Pooled prevalence and associated factors of health facility delivery in East Africa: Mixed-effect logistic regression analysis," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-16, April.
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