Vorisek Carina Nina, Lehne Moritz, Klopfenstein Sophie Anne Ines, Mayer Paula Josephine, Bartschke Alexander, Haese Thomas, Thun Sylvia
Core Facility Digital Medicine and Interoperability, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany.
Institute for Medical Informatics, Charité - Universitätsmedizin Berlin, Berlin, Germany.
JMIR Med Inform. 2022 Jul 19;10(7):e35724. doi: 10.2196/35724.
The standard Fast Healthcare Interoperability Resources (FHIR) is widely used in health information technology. However, its use as a standard for health research is still less prevalent. To use existing data sources more efficiently for health research, data interoperability becomes increasingly important. FHIR provides solutions by offering resource domains such as "Public Health & Research" and "Evidence-Based Medicine" while using already established web technologies. Therefore, FHIR could help standardize data across different data sources and improve interoperability in health research.
The aim of our study was to provide a systematic review of existing literature and determine the current state of FHIR implementations in health research and possible future directions.
We searched the PubMed/MEDLINE, Embase, Web of Science, IEEE Xplore, and Cochrane Library databases for studies published from 2011 to 2022. Studies investigating the use of FHIR in health research were included. Articles published before 2011, abstracts, reviews, editorials, and expert opinions were excluded. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and registered this study with PROSPERO (CRD42021235393). Data synthesis was done in tables and figures.
We identified a total of 998 studies, of which 49 studies were eligible for inclusion. Of the 49 studies, most (73%, n=36) covered the domain of clinical research, whereas the remaining studies focused on public health or epidemiology (6%, n=3) or did not specify their research domain (20%, n=10). Studies used FHIR for data capture (29%, n=14), standardization of data (41%, n=20), analysis (12%, n=6), recruitment (14%, n=7), and consent management (4%, n=2). Most (55%, 27/49) of the studies had a generic approach, and 55% (12/22) of the studies focusing on specific medical specialties (infectious disease, genomics, oncology, environmental health, imaging, and pulmonary hypertension) reported their solutions to be conferrable to other use cases. Most (63%, 31/49) of the studies reported using additional data models or terminologies: Systematized Nomenclature of Medicine Clinical Terms (29%, n=14), Logical Observation Identifiers Names and Codes (37%, n=18), International Classification of Diseases 10th Revision (18%, n=9), Observational Medical Outcomes Partnership common data model (12%, n=6), and others (43%, n=21). Only 4 (8%) studies used a FHIR resource from the domain "Public Health & Research." Limitations using FHIR included the possible change in the content of FHIR resources, safety, legal matters, and the need for a FHIR server.
Our review found that FHIR can be implemented in health research, and the areas of application are broad and generalizable in most use cases. The implementation of international terminologies was common, and other standards such as the Observational Medical Outcomes Partnership common data model could be used as a complement to FHIR. Limitations such as the change of FHIR content, lack of FHIR implementation, safety, and legal matters need to be addressed in future releases to expand the use of FHIR and, therefore, interoperability in health research.
标准的快速医疗保健互操作性资源（FHIR）在健康信息技术中被广泛使用。然而，其作为健康研究标准的应用仍然不太普遍。为了更有效地利用现有数据源进行健康研究，数据互操作性变得越来越重要。FHIR通过提供诸如“公共卫生与研究”和“循证医学”等资源领域，并利用已有的网络技术来提供解决方案。因此，FHIR有助于跨不同数据源规范数据，并提高健康研究中的互操作性。
我们研究的目的是对现有文献进行系统综述，并确定FHIR在健康研究中的实施现状以及可能的未来方向。
我们在PubMed/MEDLINE、Embase、科学网、IEEE Xplore和Cochrane图书馆数据库中搜索了2011年至2022年发表的研究。纳入调查FHIR在健康研究中应用的研究。排除2011年之前发表的文章、摘要、综述、社论和专家意见。我们遵循PRISMA（系统综述和Meta分析的首选报告项目）指南，并在PROSPERO（CRD42021235393）上注册了本研究。数据综合以表格和图表形式呈现。
我们共识别出998项研究，其中49项研究符合纳入标准。在这49项研究中，大多数（73%，n = 36）涵盖临床研究领域，其余研究聚焦于公共卫生或流行病学（6%，n = 3）或未明确其研究领域（20%，n = 10）。研究将FHIR用于数据捕获（29%，n = 14）、数据标准化（41%，n = 20）、分析（12%，n = 6）、招募（14%，n = 7）和同意管理（4%，n = 2）。大多数（55%，27/49）研究采用通用方法，55%（12/22）聚焦特定医学专业（传染病、基因组学、肿瘤学、环境卫生、影像学和肺动脉高压）的研究报告其解决方案可推广至其他用例。大多数（63%，31/49）研究报告使用了其他数据模型或术语：医学临床术语系统命名法（29%，n = 14）、逻辑观察标识符名称和代码（37%，n = 18）、国际疾病分类第10版（18%，n = 9）、观察性医疗结局合作组织通用数据模型（12%，n = 6）以及其他（43%，n = 21）。仅有4项（8%）研究使用了“公共卫生与研究”领域的FHIR资源。使用FHIR的局限性包括FHIR资源内容可能的变化、安全性、法律问题以及对FHIR服务器的需求。
我们的综述发现FHIR可在健康研究中实施，其应用领域广泛且在大多数用例中具有可推广性。国际术语的实施很常见，其他标准如观察性医疗结局合作组织通用数据模型可作为FHIR的补充。FHIR内容变化、缺乏FHIR实施、安全性和法律问题等局限性需要在未来版本中加以解决，以扩大FHIR的应用，进而提高健康研究中的互操作性。
