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Objectives The HL7® fast healthcare interoperability resources (FHIR®) specification has emerged as the leading interoperability standard for the exchange of healthcare data. We conducted a scoping review to identify trends and gaps in the use of FHIR for clinical research. Materials and methods We reviewed published literature, federally funded project databases, application websites, and other sources to discover FHIR-based papers, projects, and tools (collectively, “FHIR projects”) available to support clinical research activities. Results Our search identified 203 different FHIR projects applicable to clinical research. Most were associated with preparations to conduct research, such as data mapping to and from FHIR formats (n = 66, 32.5%) and managing ontologies with FHIR (n = 30, 14.8%), or post-study data activities, such as sharing data using repositories or registries (n = 24, 11.8%), general research data sharing (n = 23, 11.3%), and management of genomic data (n = 21, 10.3%). With the exception of phenotyping (n = 19, 9.4%), fewer FHIR-based projects focused on needs within the clinical research process itself. Discussion Funding and usage of FHIR-enabled solutions for research are expanding, but most projects appear focused on establishing data pipelines and linking clinical systems such as electronic health records, patient-facing data systems, and registries, possibly due to the relative newness of FHIR and the incentives for FHIR integration in health information systems. Fewer FHIR projects were associated with research-only activities. Conclusion The FHIR standard is becoming an essential component of the clinical research enterprise. To develop FHIR’s full potential for clinical research, funding and operational stakeholders should address gaps in FHIR-based research tools and methods.
Aims Increasing the diversity of the biomedical sciences workforce is a national priority. Having a mentor, and more crucially, a personal network of mentors, improves the likelihood that an individual will pursue an advanced degree and career in the biomedical sciences. The chief mission of the National Research Mentoring Network (NRMN) is to reduce racial and ethnic disparities in the biosciences workforce through the mentoring of historically underrepresented individuals. Methods To address this need, we created MyNRMN, an online mentoring platform that connects mentors and mentees nationwide. The platform enables multiple forms of mentoring and recommends connections to mentees that will help them build their personal networks. Results The MyNRMN online platform has registered more than 13,500 active mentors and mentees across all 50 states and from more than 2100 institutions. Black and Hispanic mentees are highly represented. Discussion MyNRMN has expanded opportunities for mentorship in the biomedical sciences, particularly among those not from a culture or institution that historically supports mentorship. The platform's robust search and recommendation capabilities and graph database technology enable members to grow their personal network of mentors. Conclusion The MyNRMN online platform has proven successful in connecting mentees and mentors nationwide, expanding the pipeline in biomedical science careers to attract a more diverse workforce.
Objective The Recruitment Innovation Center (RIC), partnering with the Trial Innovation Network and institutions in the National Institutes of Health-sponsored Clinical and Translational Science Awards (CTSA) Program, aimed to develop a service line to retrieve study population estimates from electronic health record (EHR) systems for use in selecting enrollment sites for multicenter clinical trials. Our goal was to create and field-test a low burden, low tech, and high-yield method. Materials and Methods In building this service line, the RIC strove to complement, rather than replace, CTSA hubs’ existing cohort assessment tools. For each new EHR cohort request, we work with the investigator to develop a computable phenotype algorithm that targets the desired population. CTSA hubs run the phenotype query and return results using a standardized survey. We provide a comprehensive report to the investigator to assist in study site selection. Results From 2017 to 2020, the RIC developed and socialized 36 phenotype-dependent cohort requests on behalf of investigators. The average response rate to these requests was 73%. Discussion Achieving enrollment goals in a multicenter clinical trial requires that researchers identify study sites that will provide sufficient enrollment. The fast and flexible method the RIC has developed, with CTSA feedback, allows hubs to query their EHR using a generalizable, vetted phenotype algorithm to produce reliable counts of potentially eligible study participants. Conclusion The RIC’s EHR cohort assessment process for evaluating sites for multicenter trials has been shown to be efficient and helpful. The model may be replicated for use by other programs.
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