Scoping Review and Case Studies of Health Data Management Before, During and After Emergencies and Disasters

The Sendai Framework on Disaster Risk Reduction 2015-2030 highlighted the health imperative in disaster risk management and the importance of scientific evidence for Health Emergency and Disaster Risk Management (Health EDRM). Reliable health data before, during and after emergencies and disasters are essential for evidence-based policies and programmes.

Recently two standardised health data collection tools were created and tested. These are the WHO Emergency Medical Team (EMT) Minimum Data Set (MDS) (global) and the Japan Surveillance in Post Extreme Emergencies and Disasters (J-SPEED) (for use in Japan). In this project, case studies were conducted on the application of the WHO EMT MDS and J-SPEED. A scoping review was also conducted to synthesise existing knowledge on evidence-gaps, as well as the various facilitators and barriers to using these types of standardised tools.

• To understand the evidence gaps about health data management before, during and after emergencies and disasters.
• To identify facilitators and barriers for successful implementation of standardised health data collection systems in the context of disasters and public health emergencies in different settings.
• To highlight internationally accepted, standardised tools or methods for setting up essential public health data for disaster response, and to demonstrate their potential uses in research, epidemiology, and services planning.

• Scoping review: A scoping review was performed in English and Japanese to identify studies pertaining to healthcare data collection and minimum data set criteria before, during, and after disasters and public health emergencies. Three electronic databases – PubMed & EMBASE (English), and the ICHUSHI database (Japanese), as well as grey literature were searched using a combination of terms related to data collection and minimum datasets that were applied to a wide range of emergency and disaster situations. Papers published prior to July 2021 were included with no other restrictions. After screening 8864 articles in English, Japanese or from grey literature, 68 studies were included in the review.
• Case Studies: Five case studies were analysed. They included the application of J-SPEED during the Hokkaido Earthquake 2018 (case 1), the West Japan Heavy Rain 2018 (case 2), and the comparison between them (case 3). In addition, the use of J-SPEED for comparative purposes was analysed in two disasters in 2018, the West Japan heavy rain that occurred in the absence of COVID-19 and the Kumamoto heavy rain that occurred in the presence of COVID-19 (case 4). In the latter comparison, data on acute respiratory infections (ARI) from daily aggregated summaries were extracted and their frequencies compared. Finally, the first application of the WHO EMT MDS during the Mozambique Cyclone Idai response 2019, was described (case 5).

The data in each case study were sent to and collated by their respective EMT coordination cells. The data were then analysed to produce descriptive analyses with summary data about individual health events that had been encountered. The five most frequent health conditions were reported, with statistical analyses conducted where relevant to examine the differences between the observed frequencies of different types of health consultations, or between disasters, or to analyse the specific health problems among different sub-groups (e.g., by age or gender).

Scoping review

Findings from the scoping review revealed a range of critical operational, structural, and functional factors of relevance to the implementation of an EMT MDS.

Facilitating factors: a standardised system that is quick and adaptable to implement to a variety of disaster types; ease in data sharing and secure storage; designated data managers and sufficient human resources to optimise data collection, analysis and relevant training; standardisation of data collection forms, containing clear definitions and operational guidance; robust technological infrastructure to support data collection and security; and collaboration with stakeholders, including local authorities.

Key barriers: insufficient standardisation and operational guidance within and among data collection forms; the absence of reliable study designs to validate and compare collected data; limited collaboration among health facilities, countries, and relevant specialists; disaster-related logistical constraints; lack of trained personnel for data collection and entry; and unreliable technology infrastructure for data collection.

Knowledge gap: The main gap lies in the transition from the acute emergency phase to the recovery phase. This is due to a lack of standardised data collection during and after an emergency, resulting in suboptimal data quality and thus substantially limiting the ability to compare variables and populations during the transition.

The Case Studies

J-SPEED in Japanese Emergencies 2018 – 2020

Case 1 Hokkaido Earthquake 2018: The J-SPEED data detailed a total of 739 consultations over 32 days. The analysis of J-SPEED data showed that the highest number of health consultations (n=721; 97.6%) occurred between day 1 and 13 of the 32-day EMT response. Most consultation were done with people over the age of 65. Women accounted for the majority of consultations. During the response period, disaster stress related symptoms were the most frequently reported health condition.

Case 2 West Japan Heavy Rain 2018: The J-SPEED data detailed a total of 3,617 health consultations, with the highest number of consultations (2,579; 71.3%) occurring between days 5 and 12 of the 65-day EMT response. Patients aged 15 to 64 comprised the majority of people seeking medical help. During the response period, the most frequently reported health complaint was skin disease followed by wounds.

Case 3 Comparing the West Japan Heavy Rain 2018 & the Hokkaido Earthquake 2018 using J-SPEED: Three major health conditions (Disaster stress related symptom, skin diseases and wounds) during two health emergencies were compared and analysed. Disaster stress related symptoms were significantly higher (p<0.01) for the earthquake than heavy rain. On the other hand, skin diseases were a greater concern with the heavy rain (p<0.01) compared to the earthquake. No significant differences in the prevalence of wounds were observed between the heavy rain and the earthquake (p>0.05).

Case 4 J-SPEED during the COVID-19 pandemic: Data for acute respiratory infections (ARIs) were compared between the West Japan heavy rain that occurred before the COVID-19 pandemic (2018) and the Kumamoto heavy rain that occurred during the COVID-19 (2020) pandemic. The results showed that ARIs accounted for 5.4% in the 2018 event and only 1.2% in the 2020 event of the total consultations for each of the respective emergencies (p<0.001). The significance of the result may be related to COVID-19 preventive measures implemented in 2020, which could also indicate how health-related behaviour pre-disaster can affect health outcomes during and after emergencies and disasters.

WHO EMT in 2019

Case 5 First Use of WHO EMT MDS in Mozambique, Cyclone Idai, 2019: During the 110 days of the disaster response, there were a total of 18,468 consultations, 1,184 new admissions and 94 live births. Minor injuries (9.8%) and acute watery diarrhoea (9.4%) were the two most frequently reported conditions. This was the first application of the WHO EMT MDS and provided valuable information towards understanding the disaster situation in real-time. This information also enabled the response manager to deploy the most effective plan for resource allocations. However, there were incomplete daily reports with errors which seem to be related to the lack of sufficient pre-training.

Globally, unreliable and varying standards of documentation currently exist for reporting health data during emergencies and disasters. These research projects demonstrated the importance of the EMT MDS data for initiating appropriate disaster responses. It reinforces the importance of standardised data collection approaches to collect a minimum data set.

Standardised MDS data provide perspectives about the types of health issues encountered during an emergency or disaster. This standardisation also allows for comparisons between different types of emergencies or as we have seen in Japan, between similar emergencies but under different circumstances. The ability to do comparisons may in the future illuminate whether practice and policy changes have had some impact at the national, community or individual levels. With standardised MDS data, governments have access to the information they need to appropriately allocate medical resources over the short term. However, these data will also contribute to the planning of health services responses for future disasters. Understanding the range of medical conditions suffered by a population during an emergency or disaster could also inform health services about whether or not long-term support will be needed for disaster survivors.

To maintain high quality data collection, continuous efforts to train EMT members to deploy the MDS correctly are important. All countries should be encouraged to adopt an EMT MDS. However, the scoping review showed that a range of operational, structural, and functional factors affect the implementation of an EMT MDS. These factors need to be taken into consideration before, during and after the implementation of an EMT MDS. The consistent implementation of an EMT MDS requires a systematic plan for addressing the practical challenges to data collection throughout the course of emergencies and disasters. Local contexts and capacities will differ, and a system to conduct country assessments for capacity to implement an EMT-MDS will be needed.

Disasters resulting from heavy rains, earthquakes, typhoons and public health emergencies are frequent and repeated problems that arise in Kansai. The adoption of a system for EMT-MDS such as J-SPEED, may allow local policy makers to track disaster and emergency responses and services demand through time. As seen with the West Japan and Kumamoto heavy rains case study, utilisation of an EMT-MDS may eventually allow for the comparisons of the impact of service or policy interventions from one disaster to another, or from one context to another, especially as the MDS database grows.

Adopting a common EMT-MDS like J-SPEED in Kansai, could improve disaster and emergency medical responses in the region, as well as provide data and information needed by local governments to plan health services for current and future disaster needs. By establishing the range of medical conditions suffered by a population during an emergency or disaster through the use of an EMT-MDS, it could also inform local services about whether or not long-term support will be needed for disaster survivors, especially in relationship to post-traumatic stress and other long term health impacts.

Publications

1. Mitchell AJ, Kubo T, Chang AH, Ochir OC, Salerno A, Yumiya Y, Barnett DJ, Nakase K, Hsu EB. (2022). Disaster and public health emergency health data collection and management: A scoping review. Am J Disaster Med. 2022 Fall;17(4):277-285. doi: 10.5055/ajdm.2022.0443. PMID: 37551899. (Published: 25 July 2023).
2. Yumiya Y, Chimed-Ochir O, Kayano R, Hitomi Y, Akahoshi K, Kondo H, Wakai A, Mimura S, Chishima K, Toyokuni Y, Koido Y, and Kubo T. (2023). Emergency Medical Team Response during the Hokkaido Eastern Iburi Earthquake 2018: J-SPEED Data Analysis. Prehospital and Disaster Medicine, 1-6. doi:10.1017/S1049023X23000432
3. Chimed-Ochir O, Yumiya Y, Taji A, Kishita E, Kondo H, Wakai A, Akahoshi K, Chishima K, Toyokuni Y, Koido Y, Kubo T. Emergency Medical Teams' Responses during the West Japan Heavy Rain 2018: J-SPEED Data Analysis. (2022). Prehosp Disaster Med. 28;37(2):1-7. doi:10.1017/S1049023X22000231. Epub ahead of print. PMID: 35225205; PMCID: PMC8958047.
4. Sugimura M, Chimed-Ochir O, Yumiya Y, Taji A, Kishita E, Tsurugi Y, Kiwaki K, Wakai A, Kondo H, Akahoshi K, Chishima K, Toyokuni Y, Koido Y, Kubo T. Incidence of Acute Respiratory Infections during Disasters in the Absence and Presence of COVID-19 Pandemic. (2022). Prehosp Disaster Med. 11:1-10. doi: 10.1017/S1049023X22000085. Epub ahead of print. PMID: 35012691.
5. Kubo T, Chimed-Ochir O, Cossa M, Ussene I, Toyokuni Y, Yumiya Y, Kayano, R, and Salio, F. (2022). First Activation of the WHO Emergency Medical Team Minimum Data Set in the 2019 Response to Tropical Cyclone Idai in Mozambique. Prehospital and Disaster Medicine, 37(6), 727-734. doi:10.1017/S1049023X22001406
6. Fukunaga A, Chimed-Ochir O, Yumiya Y, Cossa M, Ussene I, Toyokuni Y, Kayano R, Salio F, Kubo T. Temporal Trends in Acute Mental Health Problems during the Emergency Medical Team Response to Cyclone Idai 2019 in Mozambique: Findings from the WHO Emergency Medical Team Minimum Data Set. Disaster Med Public Health Prep. 2025 Mar 4;19:e48. doi: 10.1017/dmp.2025.29. PMID: 40033901.

Presentations at Conferences / Symposiums / Webinars

1. 避難所アセスメント 情報分析 (Assessment of shelter: Information analysis). Kumamoto University Hospital Disaster Medical Education and Research Center. 2021 Disaster Medical Worker Workshop-Practical Training, 26-28 November, 2021. Kumamoto, Japan.
2. 将来の新興感染症も見据えた広島県独自のデータ収集システム 広島県新型コロナウイルス感染症版 J-SPEED (Hiroshima Prefecture's unique data collection system with focus on future emerging infectious diseases: Hiroshima Prefecture New Coronavirus Infection J-SPEED Version). Hiroshima University Kasumi Campus Joint Homecoming Day. 13 November 2021. Hiroshima, Japan.
3. J-SPEEDによる診療概況可視化: 東日本大震災の教訓に基づく変革への挑戦災害医学に学ぶ診療現場データの収集・可視化 (Challenge to change based on lessons learned from J-SPEED Collection and visualization of medical field data learned from disaster medicine of the Great East Japan Earthquake). The 49th Annual Meeting of the Japanese Society of Emergency Medicine. 23 November 2021. Tokyo, Japan.
4.  J-SPEED専門職をつなぐ災害医療の取り組み(Disaster medical care initiatives connecting professionals). The 29th Annual Meeting of the Japanese Society of Clinical Behavior and the 39th Annual Meeting of the Society of Japan. Fukuoka, Japan.
5. J-SPEED 災害医療分野の日本発WHO国際標準の国際戦略 (J-SPEED International Strategy of WHO International Standards from Japan in Disaster Medicine). 28 October 2021. Japan.
6. 災害診療記録/J-SPEED 令和2年熊本豪雨等からの最新知見 (Disaster Medical Records/J-SPEED Latest knowledge from 2020 Kumamoto heavy rain). The 2nd Emergency and Disaster Medical Response Committee of the Japan Hospital Association. 26 October 2021. Japan.
7. Instruction for the EMT MDS Daily Report. WHO EMT MDS Working Group/Japan Disaster Relief EMT Initiative Corresponding Unit. 21 October 2022. Japan.
8. 災害時における保健医療の不易流行:災害とパブリックヘルス／J-SPEED (The epidemic of health care in the event of a disaster Disasters and Public Health/J-SPEED). International University of Health and Welfare. 1 October 2021. Tokyo, Japan.
9. 東日本大震災の教訓から災害医療の未来を創る: Ｊ-ＳＰＥＥＤ-災害時の診療情報管理 (Creating the Future of Disaster Medicine from the Lessons Learned from the Great East Japan Earthquake: J-SPEED - Management of Medical Information in the Event of a Disaster. The 80th POC Seminar (The 53rd Annual Meeting of the Japanese Society of Medical Laboratory Science. 8 October 2021. Yokohama, Japan.
10. J-SPEED ― 災害時の診療情報管理について―(J-SPEED - Management of medical information in the event of a disaster). 16 September 2021.
11. 災害医療をデータするJ-SPEED/MDS日本発WHO国際標準の国際戦略 (Data on disaster health J-SPEED/MDS International Strategy of WHO International Standards from Japan). International Conference on the Unity of the Sciences, ICUS. 3 September 2021.
12. 災害時診療概況報告システムJ-SPEEDと広島県の新型コロナウイルス感染症対応 (With the disaster medical care overview report system J-SPEED and Response to the new coronavirus infection in Hiroshima Prefecture). Disaster Response Medical Training Session, Nishi-ku Community Health Measures Industry Council, Hiroshima City. 9 September 2021.
13. 災害医療チームの診療情報管理:災害診療記録/Ｊ－ＳＰＥＥＤ. (Medical information management of disaster medical care team: Medical Records/J-SPEED). On-demand delivery Fukuoka Medical Association JMAT training (Basic Edition). March, 2021.
14. J-SPEEDをアタッチメントとした災害医療分野におけるAIの導入方向性 (Direction of Introduction of AI in disaster medicine with J-SPEED as an attachment). The 26th Annual Meeting of the Japanese Society of Disaster Medicine. 17 March 2021.
15. 新型コロナウィルス感染症を踏まえた今後の広島県健康危機管理 - DX推進のための突破口 (In light of the new coronavirus infection Future Hiroshima Prefecture Health Crisis Management - Breakthroughs for DX Promotion). Hiroshima Prefectural Assembly Budget Special Committee. 5 March 2021.
16. 新型コロナウイルス感染症 (New Coronavirus Infection). 17 March 2021. Hiroshima, Japan. 
17. 新型コロナウイルス感染症を踏まえた感染症対策と災害支援のあり方 (Measures against infectious diseases and disaster support based on the novel coronavirus infection). 2020 Chugoku-Shikoku Area Disaster Support Seminar. 26 January 2021. Hiroshima, Japan.
18. 災害医療チームの診療情報管理 災害診療記録/J-SPEED (Medical information management of disaster medical care team. Disaster Medical Records/J-SPEED). Education Material on J-SPEED for Japan Medical Association Team (JMAT). 16 January 2021. Japan.
19. EMT Minimum Data Set (MDS) for COVID-19. 2nd Webinar on Good Practice on Medical Response Against COVID-19 Outbreak. 8 December 2020.
20. 保健師等研究の基礎知識量的研究、やりましょう！(Basic knowledge of public health nurse research: Quantitative research, let's do it!). 2020 New Late And Mid-Term Public Health Nurse Training Program. 5 October 2020, Hiroshima, Japan.
21. 災害防止の実際から見えてきた公衆衛生学的課題とその対応～自然災害から何を学び、職場における緊急対応として何を備えるべきか (Public health issues and responses to disaster prevention - What should be learned from natural disasters and prepared as an emergency response in the workplace). Yamaguchi Medical Association Industrial Physician Workshop. 19 September 2020. Yamaguchi, Japan.
22. 災害診療記録/J-SPEED ― 豪雨災害を踏まえた避難所COVID-19　モニタリングを含めて(Disaster Medical Care Record/J-SPEED - Including COVID-19 Monitoring of Evacuation Centers in Light of Heavy Rain Disasters). 2020 Asa Medical Association Disaster Medical Lecture. 27 August 2020.
23. Introducing the WHO Emergency Medical Team Minimum Data Set (MDS). The ASEAN EOC NETWORK. 18 August 2020.