Assessing the feasibility of using publicly available data sources to identify healthcare data discrepancies and enhance service delivery: a retrospective cross-sectional study of four low human index scoring countries
Introduction Quality of care (QoC) remains a persistent challenge in countries with low Human Development Index scores (LHDIS) despite global efforts to promote universal health coverage. Addressing root causes and systematically implementing improvement interventions in LHDIS countries require a be...
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BMJ Publishing Group
2024-04-01
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| Series: | BMJ Public Health |
| Online Access: | https://bmjpublichealth.bmj.com/content/2/1/e000145.full |
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| author | Sheila Leatherman Matthew Neilson Alix Boisson-Walsh Jack Lewis |
| author_facet | Sheila Leatherman Matthew Neilson Alix Boisson-Walsh Jack Lewis |
| author_sort | Sheila Leatherman |
| collection | DOAJ |
| description | Introduction Quality of care (QoC) remains a persistent challenge in countries with low Human Development Index scores (LHDIS) despite global efforts to promote universal health coverage. Addressing root causes and systematically implementing improvement interventions in LHDIS countries require a better understanding and use of QoC data. We aim to describe the data gaps and illustrate the state of quality in health services across a small set of countries. We demonstrate how we can leverage currently available, although imperfect, public data sources to compile quality metrics across multiple LHDIS countries.Methods Using public data sources, the Demographic Health Survey (DHS) and Service Provision Assessment (SPA), we selected relevant quality metrics and categorised them within a QoC matrix. We based the selection of metrics on the quality of care in fragile, conflict-affected and vulnerable settings framework domains and the Donabedian model. Criteria for our retrospective cross-sectional study included a LHDIS and recent availability of both DHS and SPA data for data relevance.Results The approach was feasible, with relevant indicators distributed across various QoC categories. However, some cells in the indicator matrix lacked suitable indicators from SPA and DHS data. We selected the Democratic Republic of the Congo, Haiti, Afghanistan and Senegal for a snapshot of QoC in LHDIS countries. Comparisons highlighted areas of positive performance and shared challenges across these countries, with notable variability in certain categories. Senegal ranked highest overall, while Afghanistan ranked lowest across all matrix categories. Senegal had the most comprehensive data, with 94.7% of metrics available. Missing data existed for two specific metrics in all four countries, particularly within the improving clinical care domain.Conclusion The results are a clarion call for advancing efforts to develop standardised, publicly available, routinely collected and validated data sets to measure and publicly report LHDIS countries’ state of quality to marshal global attention and action in pursuit of more significant health equity. |
| format | Article |
| id | doaj-art-6b2ad794316a4de6b5542fab22a56abb |
| institution | Kabale University |
| issn | 2753-4294 |
| language | English |
| publishDate | 2024-04-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Public Health |
| spelling | doaj-art-6b2ad794316a4de6b5542fab22a56abb2025-01-28T20:30:09ZengBMJ Publishing GroupBMJ Public Health2753-42942024-04-012110.1136/bmjph-2023-000145Assessing the feasibility of using publicly available data sources to identify healthcare data discrepancies and enhance service delivery: a retrospective cross-sectional study of four low human index scoring countriesSheila Leatherman0Matthew Neilson1Alix Boisson-Walsh2Jack Lewis34 Gillings School of Public Health, The University of North Carolina at Chapel Hill Gillings School of Global Public Health, Chapel Hill, North Carolina, USA3 Department of Integrated Health Services, World Health Organization, Geneva, Switzerland1 Department of Health Policy and Management, The University of North Carolina at Chapel Hill Gillings School of Global Public Health, Chapel Hill, North Carolina, USA2 Department of Health Sciences, University of York, York, North Yorkshire, UKIntroduction Quality of care (QoC) remains a persistent challenge in countries with low Human Development Index scores (LHDIS) despite global efforts to promote universal health coverage. Addressing root causes and systematically implementing improvement interventions in LHDIS countries require a better understanding and use of QoC data. We aim to describe the data gaps and illustrate the state of quality in health services across a small set of countries. We demonstrate how we can leverage currently available, although imperfect, public data sources to compile quality metrics across multiple LHDIS countries.Methods Using public data sources, the Demographic Health Survey (DHS) and Service Provision Assessment (SPA), we selected relevant quality metrics and categorised them within a QoC matrix. We based the selection of metrics on the quality of care in fragile, conflict-affected and vulnerable settings framework domains and the Donabedian model. Criteria for our retrospective cross-sectional study included a LHDIS and recent availability of both DHS and SPA data for data relevance.Results The approach was feasible, with relevant indicators distributed across various QoC categories. However, some cells in the indicator matrix lacked suitable indicators from SPA and DHS data. We selected the Democratic Republic of the Congo, Haiti, Afghanistan and Senegal for a snapshot of QoC in LHDIS countries. Comparisons highlighted areas of positive performance and shared challenges across these countries, with notable variability in certain categories. Senegal ranked highest overall, while Afghanistan ranked lowest across all matrix categories. Senegal had the most comprehensive data, with 94.7% of metrics available. Missing data existed for two specific metrics in all four countries, particularly within the improving clinical care domain.Conclusion The results are a clarion call for advancing efforts to develop standardised, publicly available, routinely collected and validated data sets to measure and publicly report LHDIS countries’ state of quality to marshal global attention and action in pursuit of more significant health equity.https://bmjpublichealth.bmj.com/content/2/1/e000145.full |
| spellingShingle | Sheila Leatherman Matthew Neilson Alix Boisson-Walsh Jack Lewis Assessing the feasibility of using publicly available data sources to identify healthcare data discrepancies and enhance service delivery: a retrospective cross-sectional study of four low human index scoring countries BMJ Public Health |
| title | Assessing the feasibility of using publicly available data sources to identify healthcare data discrepancies and enhance service delivery: a retrospective cross-sectional study of four low human index scoring countries |
| title_full | Assessing the feasibility of using publicly available data sources to identify healthcare data discrepancies and enhance service delivery: a retrospective cross-sectional study of four low human index scoring countries |
| title_fullStr | Assessing the feasibility of using publicly available data sources to identify healthcare data discrepancies and enhance service delivery: a retrospective cross-sectional study of four low human index scoring countries |
| title_full_unstemmed | Assessing the feasibility of using publicly available data sources to identify healthcare data discrepancies and enhance service delivery: a retrospective cross-sectional study of four low human index scoring countries |
| title_short | Assessing the feasibility of using publicly available data sources to identify healthcare data discrepancies and enhance service delivery: a retrospective cross-sectional study of four low human index scoring countries |
| title_sort | assessing the feasibility of using publicly available data sources to identify healthcare data discrepancies and enhance service delivery a retrospective cross sectional study of four low human index scoring countries |
| url | https://bmjpublichealth.bmj.com/content/2/1/e000145.full |
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