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Surgical data strengthening in Ethiopia: results of a Kirkpatrick framework evaluation of a data quality intervention

Background: One key challenge in improving surgical care in resource-limited settings is the lack of high-quality and informative data. In Ethiopia, the Safe Surgery 2020 (SS2020) project developed surgical key performance indicators (KPIs) to evaluate surgical care within the country. New data coll...

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Autores principales: Bari, Sehrish, Incorvia, Joseph, Iverson, Katherine R., Bekele, Abebe, Garringer, Kaya, Ahearn, Olivia, Drown, Laura, Emiru, Amanu Aragaw, Burssa, Daniel, Workineh, Samson, Sheferaw, Ephrem Daniel, Meara, John G., Beyene, Andualem
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7782003/
https://www.ncbi.nlm.nih.gov/pubmed/33357164
http://dx.doi.org/10.1080/16549716.2020.1855808
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author Bari, Sehrish
Incorvia, Joseph
Iverson, Katherine R.
Bekele, Abebe
Garringer, Kaya
Ahearn, Olivia
Drown, Laura
Emiru, Amanu Aragaw
Burssa, Daniel
Workineh, Samson
Sheferaw, Ephrem Daniel
Meara, John G.
Beyene, Andualem
author_facet Bari, Sehrish
Incorvia, Joseph
Iverson, Katherine R.
Bekele, Abebe
Garringer, Kaya
Ahearn, Olivia
Drown, Laura
Emiru, Amanu Aragaw
Burssa, Daniel
Workineh, Samson
Sheferaw, Ephrem Daniel
Meara, John G.
Beyene, Andualem
author_sort Bari, Sehrish
collection PubMed
description Background: One key challenge in improving surgical care in resource-limited settings is the lack of high-quality and informative data. In Ethiopia, the Safe Surgery 2020 (SS2020) project developed surgical key performance indicators (KPIs) to evaluate surgical care within the country. New data collection methods were developed and piloted in 10 SS2020 intervention hospitals in the Amhara and Tigray regions of Ethiopia. Objective: To assess the feasibility of collecting and reporting new surgical indicators and measure the impact of a surgical Data Quality Intervention (DQI) in rural Ethiopian hospitals. Methods: An 8-week DQI was implemented to roll-out new data collection tools in SS2020 hospitals. The Kirkpatrick Method, a widely used mixed-method evaluation framework for training programs, was used to assess the impact of the DQI. Feedback surveys and focus groups at various timepoints evaluated the impact of the intervention on surgical data quality, the feasibility of a new data collection system, and the potential for national scale-up. Results: Results of the evaluation are largely positive and promising. DQI participants reported knowledge gain, behavior change, and improved surgical data quality, as well as greater teamwork, communication, leadership, and accountability among surgical staff. Barriers remained in collection of high-quality data, such as lack of adequate human resources and electronic data reporting infrastructure. Conclusions: Study results are largely positive and make evident that surgical data capture is feasible in low-resource settings and warrants more investment in global surgery efforts. This type of training and mentorship model can be successful in changing individual behavior and institutional culture regarding surgical data collection and reporting. Use of the Kirkpatrick Framework for evaluation of a surgical DQI is an innovative contribution to literature and can be easily adapted and expanded for use within global surgery.
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spelling pubmed-77820032021-01-14 Surgical data strengthening in Ethiopia: results of a Kirkpatrick framework evaluation of a data quality intervention Bari, Sehrish Incorvia, Joseph Iverson, Katherine R. Bekele, Abebe Garringer, Kaya Ahearn, Olivia Drown, Laura Emiru, Amanu Aragaw Burssa, Daniel Workineh, Samson Sheferaw, Ephrem Daniel Meara, John G. Beyene, Andualem Glob Health Action Original Article Background: One key challenge in improving surgical care in resource-limited settings is the lack of high-quality and informative data. In Ethiopia, the Safe Surgery 2020 (SS2020) project developed surgical key performance indicators (KPIs) to evaluate surgical care within the country. New data collection methods were developed and piloted in 10 SS2020 intervention hospitals in the Amhara and Tigray regions of Ethiopia. Objective: To assess the feasibility of collecting and reporting new surgical indicators and measure the impact of a surgical Data Quality Intervention (DQI) in rural Ethiopian hospitals. Methods: An 8-week DQI was implemented to roll-out new data collection tools in SS2020 hospitals. The Kirkpatrick Method, a widely used mixed-method evaluation framework for training programs, was used to assess the impact of the DQI. Feedback surveys and focus groups at various timepoints evaluated the impact of the intervention on surgical data quality, the feasibility of a new data collection system, and the potential for national scale-up. Results: Results of the evaluation are largely positive and promising. DQI participants reported knowledge gain, behavior change, and improved surgical data quality, as well as greater teamwork, communication, leadership, and accountability among surgical staff. Barriers remained in collection of high-quality data, such as lack of adequate human resources and electronic data reporting infrastructure. Conclusions: Study results are largely positive and make evident that surgical data capture is feasible in low-resource settings and warrants more investment in global surgery efforts. This type of training and mentorship model can be successful in changing individual behavior and institutional culture regarding surgical data collection and reporting. Use of the Kirkpatrick Framework for evaluation of a surgical DQI is an innovative contribution to literature and can be easily adapted and expanded for use within global surgery. Taylor & Francis 2020-12-24 /pmc/articles/PMC7782003/ /pubmed/33357164 http://dx.doi.org/10.1080/16549716.2020.1855808 Text en © 2020 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.
spellingShingle Original Article
Bari, Sehrish
Incorvia, Joseph
Iverson, Katherine R.
Bekele, Abebe
Garringer, Kaya
Ahearn, Olivia
Drown, Laura
Emiru, Amanu Aragaw
Burssa, Daniel
Workineh, Samson
Sheferaw, Ephrem Daniel
Meara, John G.
Beyene, Andualem
Surgical data strengthening in Ethiopia: results of a Kirkpatrick framework evaluation of a data quality intervention
title Surgical data strengthening in Ethiopia: results of a Kirkpatrick framework evaluation of a data quality intervention
title_full Surgical data strengthening in Ethiopia: results of a Kirkpatrick framework evaluation of a data quality intervention
title_fullStr Surgical data strengthening in Ethiopia: results of a Kirkpatrick framework evaluation of a data quality intervention
title_full_unstemmed Surgical data strengthening in Ethiopia: results of a Kirkpatrick framework evaluation of a data quality intervention
title_short Surgical data strengthening in Ethiopia: results of a Kirkpatrick framework evaluation of a data quality intervention
title_sort surgical data strengthening in ethiopia: results of a kirkpatrick framework evaluation of a data quality intervention
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7782003/
https://www.ncbi.nlm.nih.gov/pubmed/33357164
http://dx.doi.org/10.1080/16549716.2020.1855808
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