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Opening the ‘black box’ of collaborative improvement: a qualitative evaluation of a pilot intervention to improve quality of malaria surveillance data in public health centres in Uganda
BACKGROUND: Demand for high-quality surveillance data for malaria, and other diseases, is greater than ever before. In Uganda, the primary source of malaria surveillance data is the Health Management Information System (HMIS). However, HMIS data may be incomplete, inaccurate or delayed. Collaborativ...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8243860/ https://www.ncbi.nlm.nih.gov/pubmed/34187481 http://dx.doi.org/10.1186/s12936-021-03805-z |
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author | Hutchinson, Eleanor Nayiga, Susan Nabirye, Christine Taaka, Lilian Westercamp, Nelli Rowe, Alexander K. Staedke, Sarah G. |
author_facet | Hutchinson, Eleanor Nayiga, Susan Nabirye, Christine Taaka, Lilian Westercamp, Nelli Rowe, Alexander K. Staedke, Sarah G. |
author_sort | Hutchinson, Eleanor |
collection | PubMed |
description | BACKGROUND: Demand for high-quality surveillance data for malaria, and other diseases, is greater than ever before. In Uganda, the primary source of malaria surveillance data is the Health Management Information System (HMIS). However, HMIS data may be incomplete, inaccurate or delayed. Collaborative improvement (CI) is a quality improvement intervention developed in high-income countries, which has been advocated for low-resource settings. In Kayunga, Uganda, a pilot study of CI was conducted in five public health centres, documenting a positive effect on the quality of HMIS and malaria surveillance data. A qualitative evaluation was conducted concurrently to investigate the mechanisms of effect and unintended consequences of the intervention, aiming to inform future implementation of CI. METHODS: The study intervention targeted health workers, including brief in-service training, plus CI with ‘plan-do-study-act’ (PDSA) cycles emphasizing self-reflection and group action, periodic learning sessions, and coaching from a CI mentor. Health workers collected data on standard HMIS out-patient registers. The qualitative evaluation (July 2015 to September 2016) included ethnographic observations at each health centre (over 12–14 weeks), in-depth interviews with health workers and stakeholders (n = 20), and focus group discussions with health workers (n = 6). RESULTS: The results suggest that the intervention did facilitate improvement in data quality, but through unexpected mechanisms. The CI intervention was implemented as planned, but the PDSA cycles were driven largely by the CI mentor, not the health workers. In this context, characterized by a rigid hierarchy within the health system of limited culture of self-reflection and inadequate training and supervision, CI became an effective form of high-quality training with frequent supervisory visits. Health workers appeared motivated to improve data collection habits by their loyalty to the CI mentor and the potential for economic benefits, rather than a desire for self-improvement. CONCLUSIONS: CI is a promising method of quality improvement and could have a positive impact on malaria surveillance data. However, successful scale-up of CI in similar settings may require deployment of highly skilled mentors. Further research, focusing on the effectiveness of ‘real world’ mentors using robust study designs, will be required to determine whether CI can be translated effectively and sustainably to low-resource settings. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12936-021-03805-z. |
format | Online Article Text |
id | pubmed-8243860 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-82438602021-06-30 Opening the ‘black box’ of collaborative improvement: a qualitative evaluation of a pilot intervention to improve quality of malaria surveillance data in public health centres in Uganda Hutchinson, Eleanor Nayiga, Susan Nabirye, Christine Taaka, Lilian Westercamp, Nelli Rowe, Alexander K. Staedke, Sarah G. Malar J Research BACKGROUND: Demand for high-quality surveillance data for malaria, and other diseases, is greater than ever before. In Uganda, the primary source of malaria surveillance data is the Health Management Information System (HMIS). However, HMIS data may be incomplete, inaccurate or delayed. Collaborative improvement (CI) is a quality improvement intervention developed in high-income countries, which has been advocated for low-resource settings. In Kayunga, Uganda, a pilot study of CI was conducted in five public health centres, documenting a positive effect on the quality of HMIS and malaria surveillance data. A qualitative evaluation was conducted concurrently to investigate the mechanisms of effect and unintended consequences of the intervention, aiming to inform future implementation of CI. METHODS: The study intervention targeted health workers, including brief in-service training, plus CI with ‘plan-do-study-act’ (PDSA) cycles emphasizing self-reflection and group action, periodic learning sessions, and coaching from a CI mentor. Health workers collected data on standard HMIS out-patient registers. The qualitative evaluation (July 2015 to September 2016) included ethnographic observations at each health centre (over 12–14 weeks), in-depth interviews with health workers and stakeholders (n = 20), and focus group discussions with health workers (n = 6). RESULTS: The results suggest that the intervention did facilitate improvement in data quality, but through unexpected mechanisms. The CI intervention was implemented as planned, but the PDSA cycles were driven largely by the CI mentor, not the health workers. In this context, characterized by a rigid hierarchy within the health system of limited culture of self-reflection and inadequate training and supervision, CI became an effective form of high-quality training with frequent supervisory visits. Health workers appeared motivated to improve data collection habits by their loyalty to the CI mentor and the potential for economic benefits, rather than a desire for self-improvement. CONCLUSIONS: CI is a promising method of quality improvement and could have a positive impact on malaria surveillance data. However, successful scale-up of CI in similar settings may require deployment of highly skilled mentors. Further research, focusing on the effectiveness of ‘real world’ mentors using robust study designs, will be required to determine whether CI can be translated effectively and sustainably to low-resource settings. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12936-021-03805-z. BioMed Central 2021-06-29 /pmc/articles/PMC8243860/ /pubmed/34187481 http://dx.doi.org/10.1186/s12936-021-03805-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Hutchinson, Eleanor Nayiga, Susan Nabirye, Christine Taaka, Lilian Westercamp, Nelli Rowe, Alexander K. Staedke, Sarah G. Opening the ‘black box’ of collaborative improvement: a qualitative evaluation of a pilot intervention to improve quality of malaria surveillance data in public health centres in Uganda |
title | Opening the ‘black box’ of collaborative improvement: a qualitative evaluation of a pilot intervention to improve quality of malaria surveillance data in public health centres in Uganda |
title_full | Opening the ‘black box’ of collaborative improvement: a qualitative evaluation of a pilot intervention to improve quality of malaria surveillance data in public health centres in Uganda |
title_fullStr | Opening the ‘black box’ of collaborative improvement: a qualitative evaluation of a pilot intervention to improve quality of malaria surveillance data in public health centres in Uganda |
title_full_unstemmed | Opening the ‘black box’ of collaborative improvement: a qualitative evaluation of a pilot intervention to improve quality of malaria surveillance data in public health centres in Uganda |
title_short | Opening the ‘black box’ of collaborative improvement: a qualitative evaluation of a pilot intervention to improve quality of malaria surveillance data in public health centres in Uganda |
title_sort | opening the ‘black box’ of collaborative improvement: a qualitative evaluation of a pilot intervention to improve quality of malaria surveillance data in public health centres in uganda |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8243860/ https://www.ncbi.nlm.nih.gov/pubmed/34187481 http://dx.doi.org/10.1186/s12936-021-03805-z |
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