Faisal Hiro Putra, Nakayama Masaharu
Department of Medical Informatics, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8574, Japan, 81 22-717-7572, 81 22-717-7505.
Department of Physiology, Faculty of Medicine, UIN Syarif Hidayatullah Jakarta, Tangerang Selatan, Indonesia.
JMIR Med Inform. 2024 Aug 28;12:e59651. doi: 10.2196/59651.
The National Disaster Management Agency (Badan Nasional Penanggulangan Bencana) handles disaster management in Indonesia as a health cluster by collecting, storing, and reporting information on the state of survivors and their health from various sources during disasters. Data were collected on paper and transferred to Microsoft Excel spreadsheets. These activities are challenging because there are no standards for data collection. The World Health Organization (WHO) introduced a standard for health data collection during disasters for emergency medical teams (EMTs) in the form of a minimum dataset (MDS). Meanwhile, the Ministry of Health of Indonesia launched the SATUSEHAT platform to integrate all electronic medical records in Indonesia based on Fast Healthcare Interoperability Resources (FHIR).
This study aims to implement the WHO EMT MDS to create a disaster profile for the SATUSEHAT platform using FHIR.
We extracted variables from 2 EMT MDS medical records-the WHO and Association of Southeast Asian Nations (ASEAN) versions-and the daily reporting form. We then performed a mapping process to match these variables with the FHIR resources and analyzed the gaps between the variables and base resources. Next, we conducted profiling to see if there were any changes in the selected resources and created extensions to fill the gap using the Forge application. Subsequently, the profile was implemented using an open-source FHIR server.
The total numbers of variables extracted from the WHO EMT MDS, ASEAN EMT MDS, and daily reporting forms were 30, 32, and 46, with the percentage of variables matching FHIR resources being 100% (30/30), 97% (31/32), and 85% (39/46), respectively. From the 40 resources available in the FHIR ID core, we used 10, 14, and 9 for the WHO EMT MDS, ASEAN EMT MDS, and daily reporting form, respectively. Based on the gap analysis, we found 4 variables in the daily reporting form that were not covered by the resources. Thus, we created extensions to address this gap.
We successfully created a disaster profile that can be used as a disaster case for the SATUSEHAT platform. This profile may standardize health data collection during disasters.
印度尼西亚国家灾害管理局（Badan Nasional Penanggulangan Bencana）作为卫生群组负责处理本国的灾害管理工作，即在灾害期间从各种来源收集、存储和报告幸存者及其健康状况的信息。数据通过纸质方式收集并转移到Microsoft Excel电子表格中。这些活动颇具挑战性，因为数据收集没有标准。世界卫生组织（WHO）以最小数据集（MDS）的形式为紧急医疗队（EMT）引入了灾害期间卫生数据收集标准。与此同时，印度尼西亚卫生部推出了SATUSEHAT平台，以基于快速医疗保健互操作性资源（FHIR）整合印度尼西亚所有的电子病历。
本研究旨在实施WHO的EMT MDS，以便使用FHIR为SATUSEHAT平台创建灾害概况。
我们从2份EMT MDS医疗记录（WHO版和东南亚国家联盟（ASEAN）版）以及每日报告表中提取变量。然后我们进行了映射过程，将这些变量与FHIR资源进行匹配，并分析变量与基础资源之间的差距。接下来，我们进行概况分析，查看所选资源是否有任何变化，并使用Forge应用程序创建扩展来填补差距。随后，使用开源FHIR服务器实施该概况。
从WHO的EMT MDS、ASEAN的EMT MDS和每日报告表中提取的变量总数分别为30、32和46，与FHIR资源匹配的变量百分比分别为100%（30/30）、97%（31/32）和85%（39/46）。在FHIR ID核心中可用的40种资源中，我们分别为WHO的EMT MDS、ASEAN的EMT MDS和每日报告表使用了10种、14种和9种。基于差距分析，我们发现每日报告表中有4个变量未被资源涵盖。因此，我们创建了扩展来解决这一差距。
我们成功创建了一个灾害概况，可作为SATUSEHAT平台的灾害案例。该概况可能会使灾害期间的卫生数据收集标准化。
