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A small area model to assess temporal trends and sub-national disparities in healthcare quality

Author

Listed:
  • Adrien Allorant

    (McGill University
    University of Washington
    University of Washington)

  • Nancy Fullman

    (University of Washington
    University of Washington)

  • Hannah H. Leslie

    (University of California San Francisco)

  • Moussa Sarr

    (Institut de Recherche en Santé de Surveillance Epidémiologique et de Formation)

  • Daouda Gueye

    (Institut de Recherche en Santé de Surveillance Epidémiologique et de Formation)

  • Eliudi Eliakimu

    (Ministry of Health)

  • Jon Wakefield

    (University of Washington)

  • Joseph L. Dieleman

    (University of Washington
    University of Washington)

  • David Pigott

    (University of Washington
    University of Washington)

  • Nancy Puttkammer

    (University of Washington)

  • Robert C. Reiner

    (University of Washington
    University of Washington)

Abstract

Monitoring subnational healthcare quality is important for identifying and addressing geographic inequities. Yet, health facility surveys are rarely powered to support the generation of estimates at more local levels. With this study, we propose an analytical approach for estimating both temporal and subnational patterns of healthcare quality indicators from health facility survey data. This method uses random effects to account for differences between survey instruments; space-time processes to leverage correlations in space and time; and covariates to incorporate auxiliary information. We applied this method for three countries in which at least four health facility surveys had been conducted since 1999 – Kenya, Senegal, and Tanzania – and estimated measures of sick-child care quality per WHO Service Availability and Readiness Assessment (SARA) guidelines at programmatic subnational level, between 1999 and 2020. Model performance metrics indicated good out-of-sample predictive validity, illustrating the potential utility of geospatial statistical models for health facility data. This method offers a way to jointly estimate indicators of healthcare quality over space and time, which could then provide insights to decision-makers and health service program managers.

Suggested Citation

  • Adrien Allorant & Nancy Fullman & Hannah H. Leslie & Moussa Sarr & Daouda Gueye & Eliudi Eliakimu & Jon Wakefield & Joseph L. Dieleman & David Pigott & Nancy Puttkammer & Robert C. Reiner, 2023. "A small area model to assess temporal trends and sub-national disparities in healthcare quality," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40234-9
    DOI: 10.1038/s41467-023-40234-9
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    References listed on IDEAS

    as
    1. Steve Gutreuter & Ehimario Igumbor & Njeri Wabiri & Mitesh Desai & Lizette Durand, 2019. "Improving estimates of district HIV prevalence and burden in South Africa using small area estimation techniques," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-14, February.
    2. Leonard, Kenneth L. & Masatu, Melkiory C., 2005. "The use of direct clinician observation and vignettes for health services quality evaluation in developing countries," Social Science & Medicine, Elsevier, vol. 61(9), pages 1944-1951, November.
    3. Lindsay Mallick & Gheda Temsah & Wenjuan Wang, 2019. "Comparing summary measures of quality of care for family planning in Haiti, Malawi, and Tanzania," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-18, June.
    4. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
    5. Laura Di Giorgio & David K. Evans & Magnus Lindelow & Son Nam Nguyen & Jakob Svensson & Waly Wane & Anna Welander Tärneberg, 2020. "An Analysis of Clinical Knowledge, Absenteeism, and Availability of Resources for Maternal and Child Health: A Cross-Sectional Quality of Care Study in 10 African Countries," Working Papers 552, Center for Global Development.
    6. Lange, Siri & Mwisongo, Aziza & Mæstad, Ottar, 2014. "Why don't clinicians adhere more consistently to guidelines for the Integrated Management of Childhood Illness (IMCI)?," Social Science & Medicine, Elsevier, vol. 104(C), pages 56-63.
    7. Arman Bidarbakhtnia, 2020. "Measuring Sustainable Development Goals (SDGs): An Inclusive Approach," Global Policy, London School of Economics and Political Science, vol. 11(1), pages 56-67, February.
    8. Lindgren, Finn & Rue, Håvard, 2015. "Bayesian Spatial Modelling with R-INLA," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i19).
    9. Ramadhani Kigume & Stephen Maluka & Peter Kamuzora, 2018. "Decentralisation and health services delivery in Tanzania: Analysis of decision space in planning, allocation, and use of financial resources," International Journal of Health Planning and Management, Wiley Blackwell, vol. 33(2), pages 621-635, April.
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