Cargando…
Health service quality in 2929 facilities in six low-income and middle-income countries: a positive deviance analysis
BACKGROUND: Primary care is of insufficient quality in many low-income and middle-income countries. Some health facilities perform better than others despite operating in similar contexts, although the factors that characterise best performance are not well known. Existing best-performance analyses...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10205971/ https://www.ncbi.nlm.nih.gov/pubmed/37202022 http://dx.doi.org/10.1016/S2214-109X(23)00163-8 |
_version_ | 1785046125022019584 |
---|---|
author | Lewis, Todd P McConnell, Margaret Aryal, Amit Irimu, Grace Mehata, Suresh Mrisho, Mwifadhi Kruk, Margaret E |
author_facet | Lewis, Todd P McConnell, Margaret Aryal, Amit Irimu, Grace Mehata, Suresh Mrisho, Mwifadhi Kruk, Margaret E |
author_sort | Lewis, Todd P |
collection | PubMed |
description | BACKGROUND: Primary care is of insufficient quality in many low-income and middle-income countries. Some health facilities perform better than others despite operating in similar contexts, although the factors that characterise best performance are not well known. Existing best-performance analyses are concentrated in high-income countries and focus on hospitals. We used the positive deviance approach to identify the factors that differentiate best from worst primary care performance among health facilities across six low-resource health systems. METHODS: This positive deviance analysis used nationally representative samples of public and private health facilities from Service Provision Assessments of the Democratic Republic of the Congo, Haiti, Malawi, Nepal, Senegal, and Tanzania. Data were collected starting June 11, 2013, in Malawi and ending Feb 28, 2020, in Senegal. We assessed facility performance through completion of the Good Medical Practice Index (GMPI) of essential clinical actions (eg, taking a thorough history, conducting an adequate physical examination) according to clinical guidelines and measured with direct observations of care. We identified hospitals and clinics in the top decile of performance (defined as best performers) and conducted a quantitative, cross-national positive deviance analysis to compare them with facilities performing below the median (defined as worst performers) and identify facility-level factors that explain the gap between best and worst performance. FINDINGS: We identified 132 best-performing and 664 worst-performing hospitals, and 355 best-performing and 1778 worst-performing clinics based on clinical performance across countries. The mean GMPI score was 0·81 (SD 0·07) for the best-performing hospitals and 0·44 (0·09) for the worst-performing hospitals. Among clinics, mean GMPI scores were 0·75 (0·07) for the best performers and 0·34 (0·10) for the worst performers. High-quality governance, management, and community engagement were associated with best performance compared with worst performance. Private facilities out-performed government-owned hospitals and clinics. INTERPRETATION: Our findings suggest that best-performing health facilities are characterised by good management and leaders who can engage staff and community members. Governments should look to best performers to identify scalable practices and conditions for success that can improve primary care quality overall and decrease quality gaps between health facilities. FUNDING: Bill & Melinda Gates Foundation. |
format | Online Article Text |
id | pubmed-10205971 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-102059712023-05-25 Health service quality in 2929 facilities in six low-income and middle-income countries: a positive deviance analysis Lewis, Todd P McConnell, Margaret Aryal, Amit Irimu, Grace Mehata, Suresh Mrisho, Mwifadhi Kruk, Margaret E Lancet Glob Health Articles BACKGROUND: Primary care is of insufficient quality in many low-income and middle-income countries. Some health facilities perform better than others despite operating in similar contexts, although the factors that characterise best performance are not well known. Existing best-performance analyses are concentrated in high-income countries and focus on hospitals. We used the positive deviance approach to identify the factors that differentiate best from worst primary care performance among health facilities across six low-resource health systems. METHODS: This positive deviance analysis used nationally representative samples of public and private health facilities from Service Provision Assessments of the Democratic Republic of the Congo, Haiti, Malawi, Nepal, Senegal, and Tanzania. Data were collected starting June 11, 2013, in Malawi and ending Feb 28, 2020, in Senegal. We assessed facility performance through completion of the Good Medical Practice Index (GMPI) of essential clinical actions (eg, taking a thorough history, conducting an adequate physical examination) according to clinical guidelines and measured with direct observations of care. We identified hospitals and clinics in the top decile of performance (defined as best performers) and conducted a quantitative, cross-national positive deviance analysis to compare them with facilities performing below the median (defined as worst performers) and identify facility-level factors that explain the gap between best and worst performance. FINDINGS: We identified 132 best-performing and 664 worst-performing hospitals, and 355 best-performing and 1778 worst-performing clinics based on clinical performance across countries. The mean GMPI score was 0·81 (SD 0·07) for the best-performing hospitals and 0·44 (0·09) for the worst-performing hospitals. Among clinics, mean GMPI scores were 0·75 (0·07) for the best performers and 0·34 (0·10) for the worst performers. High-quality governance, management, and community engagement were associated with best performance compared with worst performance. Private facilities out-performed government-owned hospitals and clinics. INTERPRETATION: Our findings suggest that best-performing health facilities are characterised by good management and leaders who can engage staff and community members. Governments should look to best performers to identify scalable practices and conditions for success that can improve primary care quality overall and decrease quality gaps between health facilities. FUNDING: Bill & Melinda Gates Foundation. Elsevier Ltd 2023-05-16 /pmc/articles/PMC10205971/ /pubmed/37202022 http://dx.doi.org/10.1016/S2214-109X(23)00163-8 Text en © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Articles Lewis, Todd P McConnell, Margaret Aryal, Amit Irimu, Grace Mehata, Suresh Mrisho, Mwifadhi Kruk, Margaret E Health service quality in 2929 facilities in six low-income and middle-income countries: a positive deviance analysis |
title | Health service quality in 2929 facilities in six low-income and middle-income countries: a positive deviance analysis |
title_full | Health service quality in 2929 facilities in six low-income and middle-income countries: a positive deviance analysis |
title_fullStr | Health service quality in 2929 facilities in six low-income and middle-income countries: a positive deviance analysis |
title_full_unstemmed | Health service quality in 2929 facilities in six low-income and middle-income countries: a positive deviance analysis |
title_short | Health service quality in 2929 facilities in six low-income and middle-income countries: a positive deviance analysis |
title_sort | health service quality in 2929 facilities in six low-income and middle-income countries: a positive deviance analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10205971/ https://www.ncbi.nlm.nih.gov/pubmed/37202022 http://dx.doi.org/10.1016/S2214-109X(23)00163-8 |
work_keys_str_mv | AT lewistoddp healthservicequalityin2929facilitiesinsixlowincomeandmiddleincomecountriesapositivedevianceanalysis AT mcconnellmargaret healthservicequalityin2929facilitiesinsixlowincomeandmiddleincomecountriesapositivedevianceanalysis AT aryalamit healthservicequalityin2929facilitiesinsixlowincomeandmiddleincomecountriesapositivedevianceanalysis AT irimugrace healthservicequalityin2929facilitiesinsixlowincomeandmiddleincomecountriesapositivedevianceanalysis AT mehatasuresh healthservicequalityin2929facilitiesinsixlowincomeandmiddleincomecountriesapositivedevianceanalysis AT mrishomwifadhi healthservicequalityin2929facilitiesinsixlowincomeandmiddleincomecountriesapositivedevianceanalysis AT krukmargarete healthservicequalityin2929facilitiesinsixlowincomeandmiddleincomecountriesapositivedevianceanalysis |