Evidence map›Paper›PMID 42826230›Full record

ArticleJMIR medical informatics2026

Standardizing Disaster Health Data Visualization Using Fast Healthcare Interoperability Resources in Indonesia: Dashboard Development and Technical Evaluation.

Hiro Putra Faisal, Masaharu Nakayama

Abstract read
In one paragraph

Article in JMIR medical informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

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0 citing papers in PubMed.

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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

2 authors.

Hiro Putra Faisal *Department of Physiology, Faculty of Medicine, Syarif Hidayatullah State Islamic University Jakarta, Tangerang Selatan, Banten, Indonesia.ORCID http://orcid.org/0000-0001-6741-6834
Masaharu Nakayama *Department of Medical Informatics, Graduate School of Medicine, Tohoku University, Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8574, Japan, 81 22-717-7572, 81 22-717-7505.ORCID http://orcid.org/0000-0002-6052-6202

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Health data management during disasters enables responders to assess the needs of survivors, efficiently allocate resources, and monitor survivors' health conditions. However, government agencies need to interpret health data in real time during disasters because the volume and complexity of such data can hinder timely decision-making. Objective: In this study, we aimed to develop a visual interface for Fast Healthcare Interoperability Resources (FHIR)-based data from various sources, using the daily report form of the World Health Organization (WHO) Emergency Medical Teams Minimum Data Set (EMT MDS) as a template and ensuring compliance with the SATUSEHAT platform. Methods: The proposed solution involves creating a dashboard application within a web-based system to visualize health data using FHIR, leveraging the WHO EMT MDS disaster profile. The interface includes Overview, Location, and Demography pages that display information in tables, graphs, and maps. This application was developed using JavaScript and React. The dataset consisted of 13,300 synthetic patient records generated using Synthea, subsequently modified with GPT-5, and stored on the Health Level 7 (HL7) Application Programming Interface (HAPI) FHIR server. Results: We developed a dashboard application based on the WHO EMT MDS Daily Reporting Form comprising 3 main pages: Overview, Demography, and Location. The Demography page contains several sections, including the total number of patients, health conditions, outcomes, relationships, and protection. The Location page lists all health care facilities, along with their corresponding locations, on a map. Each Location page displays detailed information regarding the organization and demographics of the respective location. Conclusions: The dashboard application demonstrates that health data collected in accordance with FHIR standards can be integrated and presented in a form suitable for disaster response. This dashboard has the potential to support disaster management agencies by enabling real-time, data-driven decision-making during disaster response.

Indexed as

Data VisualizationDisastersHealth Information InteroperabilityDashboard SystemsHumansIndonesiadashboarddata visualizationdisasterFast Healthcare Interoperability ResourcesFHIRWHO EMT MDSWorld Health Organization Emergency Medical Teams Minimum Data Set

Identifiers

PMID42826230
PMCPMC13632908

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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.