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Interventions to improve district-level routine health data in low-income and middle-income countries: a systematic review
BACKGROUND: Routine health information system(s) (RHIS) facilitate the collection of health data at all levels of the health system allowing estimates of disease prevalence, treatment and preventive intervention coverage, and risk factors to guide disease control strategies. This core health system...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8202107/ https://www.ncbi.nlm.nih.gov/pubmed/34117009 http://dx.doi.org/10.1136/bmjgh-2020-004223 |
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author | Lee, Jieun Lynch, Caroline A Hashiguchi, Lauren Oliveira Snow, Robert W Herz, Naomi D Webster, Jayne Parkhurst, Justin Erondu, Ngozi A |
author_facet | Lee, Jieun Lynch, Caroline A Hashiguchi, Lauren Oliveira Snow, Robert W Herz, Naomi D Webster, Jayne Parkhurst, Justin Erondu, Ngozi A |
author_sort | Lee, Jieun |
collection | PubMed |
description | BACKGROUND: Routine health information system(s) (RHIS) facilitate the collection of health data at all levels of the health system allowing estimates of disease prevalence, treatment and preventive intervention coverage, and risk factors to guide disease control strategies. This core health system pillar remains underdeveloped in many low-income and middle-income countries. Efforts to improve RHIS data coverage, quality and timeliness were launched over 10 years ago. METHODS: A systematic review was performed across 12 databases and literature search engines for both peer-reviewed articles and grey literature reports on RHIS interventions. Studies were analysed in three stages: (1) categorisation of RHIS intervention components and processes; (2) comparison of intervention component effectiveness and (3) whether the post-intervention outcome improved above the WHO integrated disease surveillance response framework data quality standard of 80% or above. RESULTS: 5294 references were screened, resulting in 56 studies. Three key performance determinants—technical, organisational and behavioural—were proposed as critical to RHIS strengthening. Seventy-seven per cent [77%] of studies identified addressed all three determinants. The most frequently implemented intervention components were ‘providing training’ and ‘using an electronic health management information systems’. Ninety-three per cent [93%] of pre–post or controlled trial studies showed improvements in one or more data quality outputs, but after applying a standard threshold of >80% post-intervention, this number reduced to 68%. There was an observed benefit of multi-component interventions that either conducted data quality training or that addressed improvement across multiple processes and determinants of RHIS. CONCLUSION: Holistic data quality interventions that address multiple determinants should be continuously practised for strengthening RHIS. Studies with clearly defined and pragmatic outcomes are required for future RHIS improvement interventions. These should be accompanied by qualitative studies and cost analyses to understand which investments are needed to sustain high-quality RHIS in low-income and middle-income countries. |
format | Online Article Text |
id | pubmed-8202107 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-82021072021-06-28 Interventions to improve district-level routine health data in low-income and middle-income countries: a systematic review Lee, Jieun Lynch, Caroline A Hashiguchi, Lauren Oliveira Snow, Robert W Herz, Naomi D Webster, Jayne Parkhurst, Justin Erondu, Ngozi A BMJ Glob Health Original Research BACKGROUND: Routine health information system(s) (RHIS) facilitate the collection of health data at all levels of the health system allowing estimates of disease prevalence, treatment and preventive intervention coverage, and risk factors to guide disease control strategies. This core health system pillar remains underdeveloped in many low-income and middle-income countries. Efforts to improve RHIS data coverage, quality and timeliness were launched over 10 years ago. METHODS: A systematic review was performed across 12 databases and literature search engines for both peer-reviewed articles and grey literature reports on RHIS interventions. Studies were analysed in three stages: (1) categorisation of RHIS intervention components and processes; (2) comparison of intervention component effectiveness and (3) whether the post-intervention outcome improved above the WHO integrated disease surveillance response framework data quality standard of 80% or above. RESULTS: 5294 references were screened, resulting in 56 studies. Three key performance determinants—technical, organisational and behavioural—were proposed as critical to RHIS strengthening. Seventy-seven per cent [77%] of studies identified addressed all three determinants. The most frequently implemented intervention components were ‘providing training’ and ‘using an electronic health management information systems’. Ninety-three per cent [93%] of pre–post or controlled trial studies showed improvements in one or more data quality outputs, but after applying a standard threshold of >80% post-intervention, this number reduced to 68%. There was an observed benefit of multi-component interventions that either conducted data quality training or that addressed improvement across multiple processes and determinants of RHIS. CONCLUSION: Holistic data quality interventions that address multiple determinants should be continuously practised for strengthening RHIS. Studies with clearly defined and pragmatic outcomes are required for future RHIS improvement interventions. These should be accompanied by qualitative studies and cost analyses to understand which investments are needed to sustain high-quality RHIS in low-income and middle-income countries. BMJ Publishing Group 2021-06-11 /pmc/articles/PMC8202107/ /pubmed/34117009 http://dx.doi.org/10.1136/bmjgh-2020-004223 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Original Research Lee, Jieun Lynch, Caroline A Hashiguchi, Lauren Oliveira Snow, Robert W Herz, Naomi D Webster, Jayne Parkhurst, Justin Erondu, Ngozi A Interventions to improve district-level routine health data in low-income and middle-income countries: a systematic review |
title | Interventions to improve district-level routine health data in low-income and middle-income countries: a systematic review |
title_full | Interventions to improve district-level routine health data in low-income and middle-income countries: a systematic review |
title_fullStr | Interventions to improve district-level routine health data in low-income and middle-income countries: a systematic review |
title_full_unstemmed | Interventions to improve district-level routine health data in low-income and middle-income countries: a systematic review |
title_short | Interventions to improve district-level routine health data in low-income and middle-income countries: a systematic review |
title_sort | interventions to improve district-level routine health data in low-income and middle-income countries: a systematic review |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8202107/ https://www.ncbi.nlm.nih.gov/pubmed/34117009 http://dx.doi.org/10.1136/bmjgh-2020-004223 |
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