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Tracking health system performance in times of crisis using routine health data: lessons learned from a multicountry consortium

COVID-19 has prompted the use of readily available administrative data to track health system performance in times of crisis and to monitor disruptions in essential healthcare services. In this commentary we describe our experience working with these data and lessons learned across countries. Since...

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Autores principales: Turcotte-Tremblay, Anne-Marie, Leerapan, Borwornsom, Akweongo, Patricia, Amponsah, Freddie, Aryal, Amit, Asai, Daisuke, Awoonor-Williams, John Koku, Ayele, Wondimu, Bauhoff, Sebastian, Doubova, Svetlana V., Gadeka, Dominic Dormenyo, Dulal, Mahesh, Gage, Anna, Gordon-Strachan, Georgiana, Haile-Mariam, Damen, Joseph, Jean Paul, Kaewkamjornchai, Phanuwich, Kapoor, Neena R., Gelaw, Solomon Kassahun, Kim, Min Kyung, Kruk, Margaret E., Kubota, Shogo, Margozzini, Paula, Mehata, Suresh, Mthethwa, Londiwe, Nega, Adiam, Oh, Juhwan, Park, Soo Kyung, Passi-Solar, Alvaro, Perez Cuevas, Ricardo Enrique, Reddy, Tarylee, Rittiphairoj, Thanitsara, Sapag, Jaime C., Thermidor, Roody, Tlou, Boikhutso, Arsenault, Catherine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9888332/
https://www.ncbi.nlm.nih.gov/pubmed/36721180
http://dx.doi.org/10.1186/s12961-022-00956-6
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author Turcotte-Tremblay, Anne-Marie
Leerapan, Borwornsom
Akweongo, Patricia
Amponsah, Freddie
Aryal, Amit
Asai, Daisuke
Awoonor-Williams, John Koku
Ayele, Wondimu
Bauhoff, Sebastian
Doubova, Svetlana V.
Gadeka, Dominic Dormenyo
Dulal, Mahesh
Gage, Anna
Gordon-Strachan, Georgiana
Haile-Mariam, Damen
Joseph, Jean Paul
Kaewkamjornchai, Phanuwich
Kapoor, Neena R.
Gelaw, Solomon Kassahun
Kim, Min Kyung
Kruk, Margaret E.
Kubota, Shogo
Margozzini, Paula
Mehata, Suresh
Mthethwa, Londiwe
Nega, Adiam
Oh, Juhwan
Park, Soo Kyung
Passi-Solar, Alvaro
Perez Cuevas, Ricardo Enrique
Reddy, Tarylee
Rittiphairoj, Thanitsara
Sapag, Jaime C.
Thermidor, Roody
Tlou, Boikhutso
Arsenault, Catherine
author_facet Turcotte-Tremblay, Anne-Marie
Leerapan, Borwornsom
Akweongo, Patricia
Amponsah, Freddie
Aryal, Amit
Asai, Daisuke
Awoonor-Williams, John Koku
Ayele, Wondimu
Bauhoff, Sebastian
Doubova, Svetlana V.
Gadeka, Dominic Dormenyo
Dulal, Mahesh
Gage, Anna
Gordon-Strachan, Georgiana
Haile-Mariam, Damen
Joseph, Jean Paul
Kaewkamjornchai, Phanuwich
Kapoor, Neena R.
Gelaw, Solomon Kassahun
Kim, Min Kyung
Kruk, Margaret E.
Kubota, Shogo
Margozzini, Paula
Mehata, Suresh
Mthethwa, Londiwe
Nega, Adiam
Oh, Juhwan
Park, Soo Kyung
Passi-Solar, Alvaro
Perez Cuevas, Ricardo Enrique
Reddy, Tarylee
Rittiphairoj, Thanitsara
Sapag, Jaime C.
Thermidor, Roody
Tlou, Boikhutso
Arsenault, Catherine
author_sort Turcotte-Tremblay, Anne-Marie
collection PubMed
description COVID-19 has prompted the use of readily available administrative data to track health system performance in times of crisis and to monitor disruptions in essential healthcare services. In this commentary we describe our experience working with these data and lessons learned across countries. Since April 2020, the Quality Evidence for Health System Transformation (QuEST) network has used administrative data and routine health information systems (RHIS) to assess health system performance during COVID-19 in Chile, Ethiopia, Ghana, Haiti, Lao People’s Democratic Republic, Mexico, Nepal, South Africa, Republic of Korea and Thailand. We compiled a large set of indicators related to common health conditions for the purpose of multicountry comparisons. The study compiled 73 indicators. A total of 43% of the indicators compiled pertained to reproductive, maternal, newborn and child health (RMNCH). Only 12% of the indicators were related to hypertension, diabetes or cancer care. We also found few indicators related to mental health services and outcomes within these data systems. Moreover, 72% of the indicators compiled were related to volume of services delivered, 18% to health outcomes and only 10% to the quality of processes of care. While several datasets were complete or near-complete censuses of all health facilities in the country, others excluded some facility types or population groups. In some countries, RHIS did not capture services delivered through non-visit or nonconventional care during COVID-19, such as telemedicine. We propose the following recommendations to improve the analysis of administrative and RHIS data to track health system performance in times of crisis: ensure the scope of health conditions covered is aligned with the burden of disease, increase the number of indicators related to quality of care and health outcomes; incorporate data on nonconventional care such as telehealth; continue improving data quality and expand reporting from private sector facilities; move towards collecting patient-level data through electronic health records to facilitate quality-of-care assessment and equity analyses; implement more resilient and standardized health information technologies; reduce delays and loosen restrictions for researchers to access the data; complement routine data with patient-reported data; and employ mixed methods to better understand the underlying causes of service disruptions.
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spelling pubmed-98883322023-02-01 Tracking health system performance in times of crisis using routine health data: lessons learned from a multicountry consortium Turcotte-Tremblay, Anne-Marie Leerapan, Borwornsom Akweongo, Patricia Amponsah, Freddie Aryal, Amit Asai, Daisuke Awoonor-Williams, John Koku Ayele, Wondimu Bauhoff, Sebastian Doubova, Svetlana V. Gadeka, Dominic Dormenyo Dulal, Mahesh Gage, Anna Gordon-Strachan, Georgiana Haile-Mariam, Damen Joseph, Jean Paul Kaewkamjornchai, Phanuwich Kapoor, Neena R. Gelaw, Solomon Kassahun Kim, Min Kyung Kruk, Margaret E. Kubota, Shogo Margozzini, Paula Mehata, Suresh Mthethwa, Londiwe Nega, Adiam Oh, Juhwan Park, Soo Kyung Passi-Solar, Alvaro Perez Cuevas, Ricardo Enrique Reddy, Tarylee Rittiphairoj, Thanitsara Sapag, Jaime C. Thermidor, Roody Tlou, Boikhutso Arsenault, Catherine Health Res Policy Syst Commentary COVID-19 has prompted the use of readily available administrative data to track health system performance in times of crisis and to monitor disruptions in essential healthcare services. In this commentary we describe our experience working with these data and lessons learned across countries. Since April 2020, the Quality Evidence for Health System Transformation (QuEST) network has used administrative data and routine health information systems (RHIS) to assess health system performance during COVID-19 in Chile, Ethiopia, Ghana, Haiti, Lao People’s Democratic Republic, Mexico, Nepal, South Africa, Republic of Korea and Thailand. We compiled a large set of indicators related to common health conditions for the purpose of multicountry comparisons. The study compiled 73 indicators. A total of 43% of the indicators compiled pertained to reproductive, maternal, newborn and child health (RMNCH). Only 12% of the indicators were related to hypertension, diabetes or cancer care. We also found few indicators related to mental health services and outcomes within these data systems. Moreover, 72% of the indicators compiled were related to volume of services delivered, 18% to health outcomes and only 10% to the quality of processes of care. While several datasets were complete or near-complete censuses of all health facilities in the country, others excluded some facility types or population groups. In some countries, RHIS did not capture services delivered through non-visit or nonconventional care during COVID-19, such as telemedicine. We propose the following recommendations to improve the analysis of administrative and RHIS data to track health system performance in times of crisis: ensure the scope of health conditions covered is aligned with the burden of disease, increase the number of indicators related to quality of care and health outcomes; incorporate data on nonconventional care such as telehealth; continue improving data quality and expand reporting from private sector facilities; move towards collecting patient-level data through electronic health records to facilitate quality-of-care assessment and equity analyses; implement more resilient and standardized health information technologies; reduce delays and loosen restrictions for researchers to access the data; complement routine data with patient-reported data; and employ mixed methods to better understand the underlying causes of service disruptions. BioMed Central 2023-01-31 /pmc/articles/PMC9888332/ /pubmed/36721180 http://dx.doi.org/10.1186/s12961-022-00956-6 Text en © The Author(s) 2023 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 Commentary
Turcotte-Tremblay, Anne-Marie
Leerapan, Borwornsom
Akweongo, Patricia
Amponsah, Freddie
Aryal, Amit
Asai, Daisuke
Awoonor-Williams, John Koku
Ayele, Wondimu
Bauhoff, Sebastian
Doubova, Svetlana V.
Gadeka, Dominic Dormenyo
Dulal, Mahesh
Gage, Anna
Gordon-Strachan, Georgiana
Haile-Mariam, Damen
Joseph, Jean Paul
Kaewkamjornchai, Phanuwich
Kapoor, Neena R.
Gelaw, Solomon Kassahun
Kim, Min Kyung
Kruk, Margaret E.
Kubota, Shogo
Margozzini, Paula
Mehata, Suresh
Mthethwa, Londiwe
Nega, Adiam
Oh, Juhwan
Park, Soo Kyung
Passi-Solar, Alvaro
Perez Cuevas, Ricardo Enrique
Reddy, Tarylee
Rittiphairoj, Thanitsara
Sapag, Jaime C.
Thermidor, Roody
Tlou, Boikhutso
Arsenault, Catherine
Tracking health system performance in times of crisis using routine health data: lessons learned from a multicountry consortium
title Tracking health system performance in times of crisis using routine health data: lessons learned from a multicountry consortium
title_full Tracking health system performance in times of crisis using routine health data: lessons learned from a multicountry consortium
title_fullStr Tracking health system performance in times of crisis using routine health data: lessons learned from a multicountry consortium
title_full_unstemmed Tracking health system performance in times of crisis using routine health data: lessons learned from a multicountry consortium
title_short Tracking health system performance in times of crisis using routine health data: lessons learned from a multicountry consortium
title_sort tracking health system performance in times of crisis using routine health data: lessons learned from a multicountry consortium
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9888332/
https://www.ncbi.nlm.nih.gov/pubmed/36721180
http://dx.doi.org/10.1186/s12961-022-00956-6
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