Data collection tools

Data collection tools

WHO Health EDRM Knowledge Hub

Data collection is the systematic process of gathering, compiling, managing and analyzing different types of information from multiple sources. To provide the full picture of ongoing issues and a foundation for efficient decision-making and research, good quality data should be collected in a standardized manner ( See Chapter 4.4)

 

However, collecting and sharing health data in emergencies is often a challenge. Evidence from a literature review funded by the WKC identified key barriers to effective data collection and analysis, such as a lack of standardized systems for collecting, sharing, and storing data, a lack of clear guidance, limited collaboration between stakeholders, a lack of trained personnel, and unreliable infrastructure.

To tackle these challenges, various standardized data collection approaches and tools have been developed and implemented at national, regional, and global levels. The WHO Health EDRM Knowledge Hub on Health Data Management introduces 3 data collection tools in emergencies: 1. Emergency Medical Team Minimum Data Set (EMT MDS), 2. Early Warning Alert and Response System (EWARS), and 3. Japan Surveillance in Post Extreme Emergencies and Disasters (J-SPEED).

1. Emergency Medical Team Menimum Data Set (EMT MDS)

During emergencies, external health professionals may provide extra health services in disaster affected areas. The WHO Emergency Medical Team (EMT) initiative was developed after the 2010 Haiti earthquake, aiming to improve the timeliness and quality of health services provided by national and international Emergency Medical Teams (EMTs) and to increase capacity of national health systems in leading the activation and coordination of EMT response. 

 

For EMTs to obtain essential and standardized data for implementing efficient and coordinated responses in emergency situations, WHO developed a standardized medical data collection tool,  the Emergency Medical Team Minimum Data Set (EMT MDS), in 2017 to gather essential information during EMT consultations. The EMT MDS uses a daily reporting form to collect 85 items in four categories during EMT consultations:

 

Category 1: Team Information (14 items): e.g. name of organizations

 

Category 2: Daily Summary (6 items): e.g. the total number of consultations, new admissions, total bed capacity

 

Category 3: MDS Statistics (50 items): sex, age, health events, (e.g. trauma, infectious disease, emergency)

 

Category 4: Needs and Risks (15 items): e.g. community risks, operational constraints

 

Knowledge Hub WHO EMT MDS
The WHO EMT MDS has been used in multiple disasters and conflict situations. The case study under a WKC research project on ‘Health data collection during emergency and disaster (2020-2021)' describes how WHO EMT MDS was used during Cyclone Idai in Mozambique in 2019.

Case Study 1: Tropical Cyclone Idai, Mozambique, 2019

2. Early Warning Alert and Response System (EWARS)

The WHO’s Early Warning Alert and Response System (EWARS) was established to address the need for good quality and real-time data for timely detection and response to epidemics in emergency settings, such as in countries in conflict or following a natural disaster.

EWARS uses ‘EWARS in a box’ which contains all the equipment needed to gather data for surveillance and response activities in difficult and remote field settings without reliable internet or electricity. WHO provides an online training package for ‘EWARS in a box’ which provides a comprehensive overview of establishing EWARS in a box in the field with the key features and functionalities of the tool.

Data are entered at the facility level and automatically uploaded into a central database. The results could be rapidly achieved through automated analysis and be disseminated to all health partners regularly. The EWARS not only generates data for public health decision-making during humanitarian crises, but also serves as a foundation for strengthening disease surveillance during the transition from humanitarian to development programming. Moreover, the system is a major repository of secondary research data.

Case Study 2: EWARS in a human-made disaster in Sub-Saharan Africa [See Chapter 4.2]

An armed conflict in Sub-Saharan Africa internally displaced more than one million people into camps who were predisposed to increased risk of infectious diseases due to poor living conditions and reduced access to social services [10]. South Sudan’s Ministry of Health officially confirmed a cholera outbreak and a total of 1160 cholera cases including 23 deaths were reported between July and August 2016. The majority of cases were found in Juba County, where an average of 35 new admissions were recorded daily. The data collected by EWARS contributed to tracking cholera cases and led to a more targeted response to cholera outbreaks, such as implementing oral cholera vaccines in community centres where cholera outbreaks are expected to rise. The system resulted in improvements in the timeliness and completeness of reporting from the camps and conflict-affected locations.

This case study is from Chapter 4.2: Measuring the problem: Basic statistics in the WHO guidance on research methods for health emergency and disaster risk management, revised 2022.

3. Japan-Surveillance in Post-Extreme Emergencies and Disasters (J-SPEED)

The Japan-Surveillance in Post-Extreme Emergencies and Disasters ( J-SPEED) is a national standard data collection and reporting tool in Japan to collect near real-time health data during emergencies and disasters. J-SPEED uses a standard daily reporting form to gather data such as the number of patients and type of health problems complained during medical consultations by the EMTs. The J-SPEED reporting form can be accessed from mobile applications or websites and data can be directly typed in.  

The J-SPEED system has been used in multiple health emergency situations in Japan since 2016. The three case studies under the WKC research project on ‘ Health data management before, during and after emergencies and disasters’ (2020-2021) show what standardized health data can reveal.  

Case study 3: Earthquake, Hokkaido, 2018 

Case Study 4: Heavy rain, West Japan, 2018

Case Study 5: Incidence of Acute Respiratory Infections during Disasters in the Absence and Presence of COVID-19 Pandemic 

More information

More information on health data collection and management can be found in  Chapter 4.4: Collection and management of good quality data in the WHO guidance on research methods for health emergency and disaster risk management, revised 2022.