Tracking health system performance in times of crisis using routine health data: lessons learned from a multicountry consortium
Abstract 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 countrie...
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| Format: | Article |
| Language: | English |
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BMC
2023-01-01
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| Series: | Health Research Policy and Systems |
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| Online Access: | https://doi.org/10.1186/s12961-022-00956-6 |
| _version_ | 1811171505277501440 |
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| author | Anne-Marie Turcotte-Tremblay Borwornsom Leerapan Patricia Akweongo Freddie Amponsah Amit Aryal Daisuke Asai John Koku Awoonor-Williams Wondimu Ayele Sebastian Bauhoff Svetlana V. Doubova Dominic Dormenyo Gadeka Mahesh Dulal Anna Gage Georgiana Gordon-Strachan Damen Haile-Mariam Jean Paul Joseph Phanuwich Kaewkamjornchai Neena R. Kapoor Solomon Kassahun Gelaw Min Kyung Kim Margaret E. Kruk Shogo Kubota Paula Margozzini Suresh Mehata Londiwe Mthethwa Adiam Nega Juhwan Oh Soo Kyung Park Alvaro Passi-Solar Ricardo Enrique Perez Cuevas Tarylee Reddy Thanitsara Rittiphairoj Jaime C. Sapag Roody Thermidor Boikhutso Tlou Catherine Arsenault |
| author_facet | Anne-Marie Turcotte-Tremblay Borwornsom Leerapan Patricia Akweongo Freddie Amponsah Amit Aryal Daisuke Asai John Koku Awoonor-Williams Wondimu Ayele Sebastian Bauhoff Svetlana V. Doubova Dominic Dormenyo Gadeka Mahesh Dulal Anna Gage Georgiana Gordon-Strachan Damen Haile-Mariam Jean Paul Joseph Phanuwich Kaewkamjornchai Neena R. Kapoor Solomon Kassahun Gelaw Min Kyung Kim Margaret E. Kruk Shogo Kubota Paula Margozzini Suresh Mehata Londiwe Mthethwa Adiam Nega Juhwan Oh Soo Kyung Park Alvaro Passi-Solar Ricardo Enrique Perez Cuevas Tarylee Reddy Thanitsara Rittiphairoj Jaime C. Sapag Roody Thermidor Boikhutso Tlou Catherine Arsenault |
| author_sort | Anne-Marie Turcotte-Tremblay |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-04-10T17:15:07Z |
| format | Article |
| id | doaj.art-65ff198a4bf947499652e67a233ec7c2 |
| institution | Directory Open Access Journal |
| issn | 1478-4505 |
| language | English |
| last_indexed | 2024-04-10T17:15:07Z |
| publishDate | 2023-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Health Research Policy and Systems |
| spelling | doaj.art-65ff198a4bf947499652e67a233ec7c22023-02-05T12:27:26ZengBMCHealth Research Policy and Systems1478-45052023-01-012111810.1186/s12961-022-00956-6Tracking health system performance in times of crisis using routine health data: lessons learned from a multicountry consortiumAnne-Marie Turcotte-Tremblay0Borwornsom Leerapan1Patricia Akweongo2Freddie Amponsah3Amit Aryal4Daisuke Asai5John Koku Awoonor-Williams6Wondimu Ayele7Sebastian Bauhoff8Svetlana V. Doubova9Dominic Dormenyo Gadeka10Mahesh Dulal11Anna Gage12Georgiana Gordon-Strachan13Damen Haile-Mariam14Jean Paul Joseph15Phanuwich Kaewkamjornchai16Neena R. Kapoor17Solomon Kassahun Gelaw18Min Kyung Kim19Margaret E. Kruk20Shogo Kubota21Paula Margozzini22Suresh Mehata23Londiwe Mthethwa24Adiam Nega25Juhwan Oh26Soo Kyung Park27Alvaro Passi-Solar28Ricardo Enrique Perez Cuevas29Tarylee Reddy30Thanitsara Rittiphairoj31Jaime C. Sapag32Roody Thermidor33Boikhutso Tlou34Catherine Arsenault35Department of Global Health and Population, Harvard T.H. Chan School of Public HealthFaculty of Medicine Ramathibodi Hospital, Mahidol UniversitySchool of Public Health, University of GhanaPolicy, Planning, Monitoring and Evaluation, Ghana Health ServicesSwiss TPH, University of BaselWorld Health OrganizationSchool of Public Health, University of GhanaSchool of Public Health, Addis Ababa UniversityDepartment of Global Health and Population, Harvard UniversityEpidemiology and Health Services Research Unit CMN Siglo XXI, Mexican Institute of Social SecuritySchool of Public Health, University of GhanaOffice of the Member of Federal Parliament Gagan Kumar ThapaDepartment of Global Health and Population, Harvard T.H. Chan School of Public HealthCaribbean Institute for Health Research, University of West IndiesSchool of Public Health, Addis Ababa UniversityHôpital Universitaire de Mirebalais, Zanmi LasanteFaculty of Medicine Ramathibodi Hospital, Mahidol UniversityDepartment of Global Health and Population, Harvard T.H. Chan School of Public HealthMinistry of Health of EthiopiaTufts Clinical and Translational Science InstituteDepartment of Global Health and Population, Harvard UniversityWorld Health OrganizationPublic Health Department, Faculty of Medicine, Pontificia Universidad Católica de ChileMinistry of Health and Population, Government of NepalSchool of Nursing and Public Health, University of KwaZulu-NatalSchool of Public Health, Addis Ababa UniversityTufts Clinical and Translational Science InstituteKorea National Health Insurance Services, Health Insurance Research InstitutePublic Health Department, Faculty of Medicine, Pontificia Universidad Católica de ChileDivision of Social Protection and Health, Inter-American Development BankBiostatistics Unit, South African Medical Research CouncilFaculty of Medicine Ramathibodi Hospital, Mahidol UniversityPublic Health Department, Faculty of Medicine, Pontificia Universidad Católica de ChileStudies and Planning Unit, Ministry of Public Health and PopulationSchool of Nursing and Public Health, University of KwaZulu-NatalDepartment of Global Health and Population, Harvard T.H. Chan School of Public HealthAbstract 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.https://doi.org/10.1186/s12961-022-00956-6Routine health information systemsHealth systemsQuality of careCOVID-19 |
| spellingShingle | Anne-Marie Turcotte-Tremblay Borwornsom Leerapan Patricia Akweongo Freddie Amponsah Amit Aryal Daisuke Asai John Koku Awoonor-Williams Wondimu Ayele Sebastian Bauhoff Svetlana V. Doubova Dominic Dormenyo Gadeka Mahesh Dulal Anna Gage Georgiana Gordon-Strachan Damen Haile-Mariam Jean Paul Joseph Phanuwich Kaewkamjornchai Neena R. Kapoor Solomon Kassahun Gelaw Min Kyung Kim Margaret E. Kruk Shogo Kubota Paula Margozzini Suresh Mehata Londiwe Mthethwa Adiam Nega Juhwan Oh Soo Kyung Park Alvaro Passi-Solar Ricardo Enrique Perez Cuevas Tarylee Reddy Thanitsara Rittiphairoj Jaime C. Sapag Roody Thermidor Boikhutso Tlou Catherine Arsenault Tracking health system performance in times of crisis using routine health data: lessons learned from a multicountry consortium Health Research Policy and Systems Routine health information systems Health systems Quality of care COVID-19 |
| 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 | Routine health information systems Health systems Quality of care COVID-19 |
| url | https://doi.org/10.1186/s12961-022-00956-6 |
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