AIM-AHEAD FHIR Collaborative Training Program

The purpose of the AIM-AHEAD FHIR (Fast Healthcare Interoperability Resources) Collaborative Training Program is to train, accelerate, and sustain workforce development in FHIR and related technologies in various disciplines from academia, industry, and community-based organizations. We aim to expand and empower a skilled workforce, including researchers, practicing clinicians, healthcare providers, developers, informaticists, and graduate students, that is proficient in the FHIR standard, its practical applications, and its implementation, with a focus on research, innovation, and quality improvement.

The AIM-AHEAD FHIR Collaborative Training Program will not only equip trainees with FHIR skills but also foster a culture of interdisciplinary collaboration, laying the groundwork for a more seamless integration of FHIR within basic, clinical, social, and behavioral sciences.

All of Us Trainee Presentation at the AIM-AHEAD Annual Meeting
All of Us Trainee Presentation at the AIM-AHEAD Annual Meeting

Program Goals

Leverage the All of Us Data and Infrastructure

Increase Research in AI/ML

Train and Mentor Professionals to Benefit American Communities

all of us

Program Awardees

Through a collaborative partnership between AIM-AHEAD, All of Us, and RTI, Cohort 1 engaged 23 trainees made up of graduate students, postdocs, early-career faculty, healthcare professionals, and other non-academic professionals from communities across the United States.

Geographical Distribution of Awardees by Institution

Cohort 1

Distribution of Cohort 1 Awardees by Hub
Distribution of Cohort 1 Awardees by Hub

Cohort 2

Distribution of Cohort 2 Awardees by Hub
Distribution of Cohort 2 Awardees by Hub

Impact

Trainees leveraged the AIM-AHEAD Connect Platform, AIM-AHEAD Data Science Training Core, and All of Us Resources to navigate the program and complete a research project utilizing All of Us data subsets in the Researcher Workbench. Participants also received training and technical assistance related to R, Python, Jupyter Notebook, and model development. Graduates of this training program are well prepared to harness AI/ML approaches to conduct hypothesis-driven analysis of complex datasets.

All of Us Data types as of April 2023
All of Us Data types as of April 2023

Program Directors

Robert Mallet, PhD; Legand (Lee) Burge, PhD; Toufeeq Syed, PhD;

All questions and inquiries regarding this program can be directed to the All of Us Training Program Helpdesk.

Submit a Helpdesk Ticket
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