Assessing Data Completeness in Emergency Medical Team Reports: Analysis of the Response to Cyclone Idai in Mozambique using the WHO Minimum Data Set
Archives of Academic Emergency Medicine,
Vol. 13 No. 1 (2025),
6 September 2025
,
Page e63
https://doi.org/10.22037/aaemj.v13i1.2719
Abstract
Introduction: In 2017, WHO endorsed the Emergency Medical Team (EMT) Minimum Data Set (MDS) for real-time data collection during health emergencies. It was first activated during Cyclone Idai in Mozambique in 2019. The objective of the study is to evaluate the completeness of data collected by EMTs during the Cyclone Idai response in Mozambique.
Methods: This study evaluated data completeness from Cyclone Idai, analyzing 277 daily reports with 18,468 patient consultations from 13 international teams between 27 March and 12 July, 2019. Completeness of team information, demographics, health events, disaster relation, and outcomes were compared across EMT types and classifications using box plots, Kruskal-Wallis, t-tests, and multivariable logistic regression.
Results: During the 110-day response, 13 EMTs submitted 277 daily reports on patient information. Findings showed that, out of the 277 daily reports, demographic information was complete in 92.8% of reports, health event information in 62.1%, information on the relation of health events to disaster in 57.4%, and outcome data in 50.2%. Type 2 EMTs exhibited higher data completeness, likely due to greater resources and personnel, compared to Type 1 Mobile and Type 1 Fixed EMTs. Type 1 Fixed EMTs demonstrated lower completeness for outcomes, health events, and disaster relation, potentially due to heavier workloads. Type 1 Mobile EMTs likely benefited from enhanced training and frequent interactions with data managers, which may have contributed to their higher data completeness compared to Type 1 Fixed EMTs. Classified EMTs performed better overall.
Conclusion: This study underscores the need for standardized training, and the data collection applications that enable the automatic inclusion of information such as geotags.
- Data collection
- data quality
- disaster
- Emergency Medical Team
- MDS
How to Cite
References
Noran O. Collaborative disaster management: An interdisciplinary approach. Comput Ind. 2014;65(6):1032-40.
Jafar AJ, Norton I, Lecky F, Redmond AD. A literature review of medical record keeping by foreign medical teams in sudden onset disasters. Prehosp Disaster Med. 2015;30(2):216-22.
Mills EJ, Robinson J, Attaran A, Clarke M, Singh S, Upshur RE, et al. Sharing evidence on humanitarian relief. BMJ. 2005;331(7531):1485-6.
Chu K, Stokes C, Trelles M, Ford N. Improving effective surgical delivery in humanitarian disasters: lessons from Haiti. PLoS Med. 2011;8(4):e1001025.
Joint Committee for Disaster Medical Recording. J-SPEED information site. 2023. Accessed July 10, 2023. Available from: https://www.j-speed.org/top.
Indd S. OPERATIONS MANUAL FOR MANAGERS. Accessed September 25, 2024. Available from: https://www.medbox.org/preview/5280ab38-a4a0-4a21-a0fd-17f01fcc7b89/doc.pdf.
Mashoufi M, Ayatollahi H, Khorasani-Zavareh D. A Review of Data Quality Assessment in Emergency Medical Services. Open Med Inform J. 2018;12:19-32.
McDonald N, Little N, Kriellaars D, Doupe MB, Giesbrecht G, Pryce RT. Database quality assessment in research in paramedicine: a scoping review. Scand J Trauma Resusc Emerg Med. 2023;31(1):78.
Emergency Medical Team Minimum Data Set Working Group. MINIMUM DATA SET FOR REPORTING BY EMERGENCY MEDICAL TEAMS. Tokyo, Jerusalem, Geneva: JICA, MASHAV, World Health Organization; 2016. Available from: https://teams-project.s3-eu-west-1.amazonaws.com/docs/attachments/MDS_Report_Instructions.pdf.
WHO EMT MDS Working Group. EMT MDS Gateway. J-SPEED information site 2023. Accessed July 10, 2023. Available from: https://www.j-speed.org/mds.
Ciottone GR. Ciottone’s Disaster Medicine: Elsevier; 2024:121.
World Health Organization. Classification and minimum standards for emergency medical teams: World Health Organization; 2021. Available from: https://extranet.who.int/emt/sites/default/files/BlueBook2021.pdf.
Walker DA, Smith TJ. Logistic regression under sparese data conditions. J Mod Appl Stat Methods. 2020;18(2):2-18.
Heinze G, Schemper M. A solution to the problem of separation in logistic regression. Stat Med. 2002;21(16):2409-19.
Steyerberg EW. FRANK E. harrell, Jr., regression modeling strategies: With applications, to linear models, logistic and ordinal regression, and survival analysis, 2nd ed. Heidelberg: Springer. Biometrics. 2016;72(3):1006-7.
Jordan A. The role of EMTs in disaster response and recovery. Unitek EMT. May 24, 2023. Accessed September 26, 2024. Available from: https://www.unitekemt.com/blog/the-role-of-emts-in-disaster-response-and-recovery/.
Pan American Health Organization. Emergency medical teams. Accessed September 26, 2024. Available from: https://www.paho.org/en/health-emergencies/emergency-medical-teams.
Hamilton ARL SB, Liverani M. The role of emergency medical teams in disaster response: a summary of the literature. Nat Hazards (Dordr). 2022;110(3):1417-26.
What is Data Completeness? Examples, Differences and Steps: Atlan; 2023. updated September 8, 2023. Accessed September 26, 2024. Available from: https://atlan.com/what-is-data-completeness/.
Ghawana T, Pashova L, Zlatanova S. Geospatial Data Utilisation in National Disaster Management Frameworks and the Priorities of Multilateral Disaster Management Frameworks: Case Studies of India and Bulgaria. ISPRS International Journal of Geo-information. 2021;10(9):610.
Kubo T, Chimed-Ochir O, Cossa M, Ussene I, Toyokuni Y, Yumiya Y, et al. First Activation of the WHO Emergency Medical Team Minimum Data Set in the 2019 Response to Tropical Cyclone Idai in Mozambique. Prehosp Disaster Med. 2022;37(6):727-34.
Doocy S, Dick A, Daniels A, Kirsch TD. The human impact of tropical cyclones: a historical review of events 1980-2009 and systematic literature review. PLoS Curr. 2013;5.
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