■国家灾害管理局(BadanNasionalPenanggulanganBencana)通过收集,将印度尼西亚的灾害管理作为一个卫生集群来处理,存储,并在灾害期间从各种来源报告幸存者状况及其健康状况的信息。在纸上收集数据并转移到MicrosoftExcel电子表格。这些活动具有挑战性,因为没有数据收集标准。世界卫生组织(WHO)以最小数据集(MDS)的形式为紧急医疗队(EMT)引入了灾难期间的健康数据收集标准。同时,印度尼西亚卫生部启动了SATUSEHAT平台,以基于快速医疗互操作性资源(FHIR)整合印度尼西亚的所有电子病历。
■本研究旨在实施WHOEMTMDS,以使用FHIR为SATUSEHAT平台创建灾难简介。
■我们从2个EMTMDS病历-WHO和东南亚国家联盟(ASEAN)版本-以及每日报告表中提取了变量。然后,我们执行了映射过程,将这些变量与FHIR资源进行匹配,并分析了变量与基础资源之间的差距。接下来,我们进行了分析,以查看所选资源中是否有任何更改,并使用Forge应用程序创建了扩展以填补空白。随后,该配置文件是使用开源FHIR服务器实现的。
■从WHOEMTMDS中提取的变量总数,东盟EMTMDS,每日报告表格为30、32和46,与FHIR资源匹配的变量百分比为100%(30/30),97%(31/32),85%(39/46),分别。从FHIRID核心的40个可用资源中,我们为WHOEMTMDS使用了10、14和9,东盟EMTMDS,和每日报告表格,分别。根据差距分析,我们在每日报告表格中发现了4个不在资源范围内的变量.因此,我们创建了扩展来解决这个差距。
■我们成功创建了一个灾难配置文件,该配置文件可用作SATUSEHAT平台的灾难案例。此配置文件可以在灾难期间标准化健康数据收集。
UNASSIGNED: 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).
UNASSIGNED: This study aims to implement the WHO EMT MDS to create a disaster profile for the SATUSEHAT platform using FHIR.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.