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Exploring approaches to weighting estimates of facility readiness to provide health services used for estimating input-adjusted effective coverage: a case study using data from Tanzania

The ideal approach for calculating effective coverage of health services using ecological linking requires accounting for variability in facility readiness to provide health services and patient volume by incorporating adjustments for facility type into estimates of facility readiness and weighting...

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Autores principales: Sheffel, Ashley, Carter, Emily, Niyeha, Debora, Yahya-Malima, Khadija I., Malamsha, Deogratius, Shagihilu, Shagihilu, Munos, Melinda K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10355680/
https://www.ncbi.nlm.nih.gov/pubmed/37462190
http://dx.doi.org/10.1080/16549716.2023.2234750
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author Sheffel, Ashley
Carter, Emily
Niyeha, Debora
Yahya-Malima, Khadija I.
Malamsha, Deogratius
Shagihilu, Shagihilu
Munos, Melinda K.
author_facet Sheffel, Ashley
Carter, Emily
Niyeha, Debora
Yahya-Malima, Khadija I.
Malamsha, Deogratius
Shagihilu, Shagihilu
Munos, Melinda K.
author_sort Sheffel, Ashley
collection PubMed
description The ideal approach for calculating effective coverage of health services using ecological linking requires accounting for variability in facility readiness to provide health services and patient volume by incorporating adjustments for facility type into estimates of facility readiness and weighting facility readiness estimates by service-specific caseload. The aim of this study is to compare the ideal caseload-weighted facility readiness approach to two alternative approaches: (1) facility-weighted readiness and (2) observation-weighted readiness to assess the suitability of each as a proxy for caseload-weighted facility readiness. We utilised the 2014–2015 Tanzania Service Provision Assessment along with routine health information system data to calculate facility readiness estimates using the three approaches. We then conducted equivalence testing, using the caseload-weighted estimates as the ideal approach and comparing with the facility-weighted estimates and observation-weighted estimates to test for equivalence. Comparing the facility-weighted readiness estimates to the caseload-weighted readiness estimates, we found that 58% of the estimates met the requirements for equivalence. In addition, the facility-weighted readiness estimates consistently underestimated, by a small percentage, facility readiness as compared to the caseload-weighted readiness estimates. Comparing the observation-weighted readiness estimates to the caseload-weighted readiness estimates, we found that 64% of the estimates met the requirements for equivalence. We found that, in this setting, both facility-weighted readiness and observation-weighted readiness may be reasonable proxies for caseload-weighted readiness. However, in a setting with more variability in facility readiness or larger differences in facility readiness between low caseload and high caseload facilities, the observation-weighted approach would be a better option than the facility-weighted approach. While the methods compared showed equivalence, our results suggest that selecting the best method for weighting readiness estimates will require assessing data availability alongside knowledge of the country context.
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spelling pubmed-103556802023-07-20 Exploring approaches to weighting estimates of facility readiness to provide health services used for estimating input-adjusted effective coverage: a case study using data from Tanzania Sheffel, Ashley Carter, Emily Niyeha, Debora Yahya-Malima, Khadija I. Malamsha, Deogratius Shagihilu, Shagihilu Munos, Melinda K. Glob Health Action Method The ideal approach for calculating effective coverage of health services using ecological linking requires accounting for variability in facility readiness to provide health services and patient volume by incorporating adjustments for facility type into estimates of facility readiness and weighting facility readiness estimates by service-specific caseload. The aim of this study is to compare the ideal caseload-weighted facility readiness approach to two alternative approaches: (1) facility-weighted readiness and (2) observation-weighted readiness to assess the suitability of each as a proxy for caseload-weighted facility readiness. We utilised the 2014–2015 Tanzania Service Provision Assessment along with routine health information system data to calculate facility readiness estimates using the three approaches. We then conducted equivalence testing, using the caseload-weighted estimates as the ideal approach and comparing with the facility-weighted estimates and observation-weighted estimates to test for equivalence. Comparing the facility-weighted readiness estimates to the caseload-weighted readiness estimates, we found that 58% of the estimates met the requirements for equivalence. In addition, the facility-weighted readiness estimates consistently underestimated, by a small percentage, facility readiness as compared to the caseload-weighted readiness estimates. Comparing the observation-weighted readiness estimates to the caseload-weighted readiness estimates, we found that 64% of the estimates met the requirements for equivalence. We found that, in this setting, both facility-weighted readiness and observation-weighted readiness may be reasonable proxies for caseload-weighted readiness. However, in a setting with more variability in facility readiness or larger differences in facility readiness between low caseload and high caseload facilities, the observation-weighted approach would be a better option than the facility-weighted approach. While the methods compared showed equivalence, our results suggest that selecting the best method for weighting readiness estimates will require assessing data availability alongside knowledge of the country context. Taylor & Francis 2023-07-18 /pmc/articles/PMC10355680/ /pubmed/37462190 http://dx.doi.org/10.1080/16549716.2023.2234750 Text en © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
spellingShingle Method
Sheffel, Ashley
Carter, Emily
Niyeha, Debora
Yahya-Malima, Khadija I.
Malamsha, Deogratius
Shagihilu, Shagihilu
Munos, Melinda K.
Exploring approaches to weighting estimates of facility readiness to provide health services used for estimating input-adjusted effective coverage: a case study using data from Tanzania
title Exploring approaches to weighting estimates of facility readiness to provide health services used for estimating input-adjusted effective coverage: a case study using data from Tanzania
title_full Exploring approaches to weighting estimates of facility readiness to provide health services used for estimating input-adjusted effective coverage: a case study using data from Tanzania
title_fullStr Exploring approaches to weighting estimates of facility readiness to provide health services used for estimating input-adjusted effective coverage: a case study using data from Tanzania
title_full_unstemmed Exploring approaches to weighting estimates of facility readiness to provide health services used for estimating input-adjusted effective coverage: a case study using data from Tanzania
title_short Exploring approaches to weighting estimates of facility readiness to provide health services used for estimating input-adjusted effective coverage: a case study using data from Tanzania
title_sort exploring approaches to weighting estimates of facility readiness to provide health services used for estimating input-adjusted effective coverage: a case study using data from tanzania
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10355680/
https://www.ncbi.nlm.nih.gov/pubmed/37462190
http://dx.doi.org/10.1080/16549716.2023.2234750
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