Evidence map›Paper›PMID 36721180›Full record

ArticleHealth research policy and systems2023

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

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 and 26 more

Open access · goldAbstract readLetter
In one paragraph

Article in Health research policy and systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
5.8field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

36 authors at 18 institutions in 12 countries.

Anne-Marie Turcotte-Tremblay *Department of Global Health and Population, Harvard T.H. Chan School of Public Health, 401 Park Drive, 3Rd Floor East, room L3-015A5, Landmark Center, Boston, MA, 02215, USA. annemarie.turcottetremblay@gmail.com.ORCID http://orcid.org/0000-0002-6138-9908
Borwornsom Leerapan *Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Patricia AkweongoSchool of Public Health, University of Ghana, Accra, Ghana.
Freddie AmponsahPolicy, Planning, Monitoring and Evaluation, Ghana Health Services, Accra, Ghana.
Amit AryalSwiss TPH, University of Basel, Basel, Switzerland.
Daisuke AsaiWorld Health Organization, Vientiane, Lao People's Democratic Republic.
John Koku Awoonor-WilliamsSchool of Public Health, University of Ghana, Accra, Ghana.
Wondimu AyeleSchool of Public Health, Addis Ababa University, Addis Ababa, Ethiopia.
Sebastian BauhoffDepartment of Global Health and Population, Harvard University, Boston, USA.
Svetlana V DoubovaEpidemiology and Health Services Research Unit CMN Siglo XXI, Mexican Institute of Social Security, Mexico City, Mexico.
Dominic Dormenyo GadekaSchool of Public Health, University of Ghana, Accra, Ghana.
Mahesh DulalOffice of the Member of Federal Parliament Gagan Kumar Thapa, Kathmandu, Nepal.
Anna GageDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, 401 Park Drive, 3Rd Floor East, room L3-015A5, Landmark Center, Boston, MA, 02215, USA.
Georgiana Gordon-StrachanCaribbean Institute for Health Research, University of West Indies, Kingston, Jamaica.
Damen Haile-MariamSchool of Public Health, Addis Ababa University, Addis Ababa, Ethiopia.
Jean Paul JosephHôpital Universitaire de Mirebalais, Zanmi Lasante, Arrondissement de Mirebalais, Haïti.
Phanuwich KaewkamjornchaiFaculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Neena R KapoorDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, 401 Park Drive, 3Rd Floor East, room L3-015A5, Landmark Center, Boston, MA, 02215, USA.
Solomon Kassahun GelawMinistry of Health of Ethiopia, Addis Ababa, Ethiopia.
Min Kyung KimTufts Clinical and Translational Science Institute, Boston, USA.
Margaret E KrukDepartment of Global Health and Population, Harvard University, Boston, USA.
Shogo KubotaWorld Health Organization, Vientiane, Lao People's Democratic Republic.
Paula MargozziniPublic Health Department, Faculty of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile.
Suresh MehataMinistry of Health and Population, Government of Nepal, Kathmandu, Nepal.
Londiwe MthethwaSchool of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa.
Adiam NegaSchool of Public Health, Addis Ababa University, Addis Ababa, Ethiopia.
Juhwan OhTufts Clinical and Translational Science Institute, Boston, USA.
Soo Kyung ParkKorea National Health Insurance Services, Health Insurance Research Institute, Wonju, Gangwon-Do, South Korea.
Alvaro Passi-SolarPublic Health Department, Faculty of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile.
Ricardo Enrique Perez CuevasDivision of Social Protection and Health, Inter-American Development Bank, Kingston, Jamaica.
Tarylee ReddyBiostatistics Unit, South African Medical Research Council, Durban, South Africa.
Thanitsara RittiphairojFaculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Jaime C SapagPublic Health Department, Faculty of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile.
Roody ThermidorStudies and Planning Unit, Ministry of Public Health and Population, Port-Au-Prince, Haiti.
Boikhutso TlouSchool of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa.
Catherine ArsenaultDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, 401 Park Drive, 3Rd Floor East, room L3-015A5, Landmark Center, Boston, MA, 02215, USA.
Harvard Global Health Institute · USAddis Ababa University · ETMahidol University · THPontificia Universidad Católica de Chile · CLUniversity of Ghana · GHGovernment of Nepal · NPHarvard University · USUniversity of KwaZulu-Natal · ZAGhana Health Service · GHGovernment of Ethiopia · ETInter-American Development Bank · USMexican Social Security Institute · MXNational Health Insurance Service · KRSeoul National University · KRSouth African Medical Research Council · ZASouthern California Clinical and Translational Science Institute · USSwiss Tropical and Public Health Institute · CHUniversity of the West Indies · JM

Funding

World Health Organization 001
6 · The paper itself

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.

Indexed as

COVID-19Population GroupsChildData AccuracyElectronic Health RecordsEthiopiaHumansInfant, NewbornCOVID-19Health systemsQuality of careRoutine health information systems

Identifiers

PMID36721180
PMCPMC9888332
OpenAlexW4318703312

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.