Fast Healthcare Interoperability Resources (FHIR) in a FAIR Metadata Registry for COVID-19 Research

Klopfenstein, Sophie Anne Inès; Vorisek, Carina Nina; Shutsko, Aliaksandra; Lehne, Moritz; Saß, Julian; Löbe, Matthias; Schmidt, Carsten Oliver; Thun, Sylvia

doi:10.3233/shti210817

Cited by 12 publications

(11 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Overall, the results were consistent with prior, limited studies of FHIR® integration [22,24]. These results are also consistent with FHIR's 80/20 rule, in that the resources have been designed to support a more general or common set of data requirements across many use cases.…”

Section: Discussionsupporting

confidence: 85%

Measuring the Coverage of the HL7® FHIR® Standard in Supporting Data Acquisition for 3 Public Health Registries

Bikkanuri,

Robins,

Wong

et al. 2023

Preprint

View full text Add to dashboard Cite

With the increasing need for timely submission of data to state and national public health registries, current manual approaches to data acquisition and submission are insufficient. In clinical practice, federal regulations are now mandating the use of data messaging standards, i.e., the Health Level Seven (HL7®) Fast Healthcare Interoperability Resources (FHIR®) standard, to facilitate the electronic exchange of clinical (patient) data. In both research and public health practice, we can also leverage FHIR® ‒ and the infrastructure already in place for supporting exchange of clinical practice data ‒ to enable seamless exchange between the electronic medical record and public health registries. That said, in order to understand the current utility of FHIR® for supporting the public health use case, we must first measure the extent to which the standard resources map to the required registry data elements. Thus, using a systematic mapping approach, we evaluated the level of completeness of the FHIR® standard to support data collection for three public health registries (Trauma, Stroke, and National Surgical Quality Improvement Program). On average, approximately 80% of data elements were available (71%, 77%, and 92%, respectively) in FHIR®. This tells us that there is the potential for significant automation to support EHR-to-Registry data exchange, which will reduce the amount of manual, error-prone processes and ensure higher data quality. Further, identification of the remaining 20% of data elements that are “not mapped” will enable us to improve the standard and develop profiles that will better fit the registry data model.

show abstract

Section: Discussionsupporting

confidence: 85%

Measuring the Coverage of the HL7® FHIR® Standard in Supporting Data Acquisition for 3 Public Health Registries

Bikkanuri,

Robins,

Wong

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Of the 49 studies, most (73%, n=36) studies covered the research domain of clinical research, of which 10 (20%) studies were clinical trials [ 22 , 29 - 31 , 36 , 39 , 43 , 56 , 65 , 66 ]; 3 (6%) studies focused on solutions in public health and epidemiology [ 38 , 40 , 64 ], and the remaining studies did not specify their research domain (20%, n=10; Figure 4 ) [ 24 , 32 , 41 , 42 , 45 - 47 , 50 , 63 , 69 ]. The included studies used FHIR for the standardization of data (41%, n=20) [ 23 , 26 , 30 , 34 , 41 , 45 - 48 , 51 - 53 , 57 - 60 , 63 , 66 , 67 , 70 ], data capture (29%, n=14) [ 1 , 12 , 22 , 24 , 27 , 35 - 37 , 43 , 44 , 55 , 61 , 64 , 65 ], recruitment (14%, n=7) [ 28 , 29 , 31 , 32 , 49 , 56 , 62 ], analysis (12%, n=6) [ 25 , 38 , 42 , 50 , 68 , ...…”

Section: Resultsmentioning

confidence: 99%

“…Though provided by FHIR specifically for research, resources out of the domains “Public Health & Research” and “Evidence-Based Medicine” were used in only 4 studies. A recently published study investigated the feasibility of the FHIR resource “ResearchStudy” in a metadata registry for COVID-19 research and found that there was a need for the use of extensions on more than 20% of the data items [ 41 ]. However, the resources “ResearchStudy” and “ResearchSubject” are currently under revision and will likely be tailored more to researchers’ needs when released with FHIR version R5 in 2022 [ 73 ].…”

Section: Discussionmentioning

confidence: 99%

“…Of the 49 studies, the majority were conducted in Germany (47%, n=23) [12,26,[28][29][30][31]34,35,[40][41][42][45][46][47]52,53,[56][57][58]60,62,63,69], the United States (27%, n=13) [22,25,36,44,[48][49][50]61,[64][65][66]68,70], and Australia (6%, n=3) [1,43,67]. The remaining studies were performed in Austria (2%, n=1) [32], Canada (2%, n=1) [24], France (2%, n=1) [51], Greece (2%, n=1) [59], Japan (2%, n=1) [27], Pakistan (2%, n=1) [38], Spain (2%, n=1) [55], Switzerland (2%, n=1) [39], Taiwan (2%, n=1) [23], and the United Kingdom (2%, n=1)…”

Section: Characteristics Of Included Studiesmentioning

confidence: 99%

“…In terms of medical specialty, most (55%, 27/49) of the studies [24,[27][28][29][30][31][32]34,[36][37][38][39][40][41][42]44,46,48,49,53,56,[60][61][62][63]67,70] were using a generic approach-implementable in any kind of specialty (Table 2). Of the remaining studies, 16% (8/49) use cases focused on infectious disease [1,22,23,26,45,47,50,59], whereas 12% (6/49) focused on oncology [25,55,57,58,65,66] and 8% (4/49) on genomics [43,52,68,69].…”

Section: Study Objectivesmentioning

confidence: 99%

See 2 more Smart Citations

Fast Healthcare Interoperability Resources (FHIR) for Interoperability in Health Research: Systematic Review

Vorisek¹,

Lehne²,

Klopfenstein³

et al. 2022

JMIR Med Inform

Self Cite

100

View full text Add to dashboard Cite

Background: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. Objective: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. Methods: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. Results: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. Conclusions: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...

show abstract

The Fast Health Interoperability Resources (FHIR) and Clinical Research, a Scoping Review

Pavão,

Bastardo,

Rocha

2024

Lecture Notes in Networks and Systems

View full text Add to dashboard Cite

Fast Healthcare Interoperability Resources (FHIR) in a FAIR Metadata Registry for COVID-19 Research

Cited by 12 publications

References 5 publications

Measuring the Coverage of the HL7® FHIR® Standard in Supporting Data Acquisition for 3 Public Health Registries

Measuring the Coverage of the HL7® FHIR® Standard in Supporting Data Acquisition for 3 Public Health Registries

Fast Healthcare Interoperability Resources (FHIR) for Interoperability in Health Research: Systematic Review

The Fast Health Interoperability Resources (FHIR) and Clinical Research, a Scoping Review

Contact Info

Product

Resources

About