Assessing Data Completeness in Emergency Medical Team Reports: Analysis of the Response to Cyclone Idai in Mozambique using the WHO Minimum Data Set.

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.