Chronic diseases corresponding to diabetes, heart disease and cancer disproportionally affect racial and ethnic minorities. Of the 45 percent of Americans who’ve a number of chronic diseases, underserved populations are three to 6 times more likely than whites to have a chronic disease.
Researchers from Florida Atlantic University’s Schmidt College of Medicine, in collaboration with the Caridad Center, Inc., and the University of Miami Miller School of Medicine, have received a $500,000 grant from the National Institutes of Health (NIH) for a project to tackle chronic health disparities through using electronic health records (EHR), artificial intelligence, machine learning (AI/ML) and the Web of Things (IoT).
The project, “Developing a Precise, Localized, Community Focused, Population Health Framework in an FQHC to Tackle Chronic Disease Disparities through EHR Data,” is a component of the NIH’s “Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD).” This project is made possible by NIH Other Transaction Agreement Number 1OT2OD032581.
AIM-AHEAD’s program goal is to determine mutually useful, coordinated and trusted partnerships to boost participation and representation of researchers and communities currently underrepresented in the event and AI/ML models, and improve the capabilities of this emerging technology, starting with using EHR and lengthening to other diverse data to deal with health disparities.
The AIM-AHEAD program consists of 4 cores -; partnerships, research, infrastructure, and data science training-;and this collaboration falls under the infrastructure core, which is headed by Nick Tsinoremas, Ph.D., vice provost for research, data and computing on the University of Miami and the founding director of its Institute for Data Science and Computing (IDSC), serving as principal investigator.
One major recurring challenge faced by organizations that wish to use their very own institutional EHR data for research is establishing an acceptable research environment through which the patient population will be profiled and research cohorts identified. Addressing this challenge is the primary requisite step to enabling community focused, EHR-based, research projects that aim to use AI/ML methods or every other methods to those sets of information.
FAU’s Schmidt College of Medicine and its affiliated health clinics, along with the Caridad Health Center – Florida’s largest free health clinic established in 1989 – and the University of Miami, are developing this pilot program as a national model on methods to implement AI/ML in community health centers and federally qualified health centers to enhance their AI/ML delivery and research operations.
Little has been done to actively incorporate data derived from electronic health records of federally qualified health centers and community centers that directly serve underrepresented and disadvantaged groups burdened by health disparities. Although these centers function the first source of medical look after communities affected by health disparities, they unfortunately lack adequate data, artificial intelligence and machine-learning capabilities needed to gather, collate and analyze substantial amounts of patient data.”
Janet Robishaw, Ph.D., principal investigator, chair of the Department of Biomedical Science, senior associate dean for research, and professor of biomedical science, FAU Schmidt College of Medicine
The project is spearheaded by Robishaw; Laura Kallus, chief executive officer of Caridad Center, Inc.; and Azizi Seixas, Ph.D., associate professor within the Department of Psychiatry and Behavioral Sciences on the Miller School of Medicine and director of the Population Health Informatics Program at IDSC.
With this grant, researchers will tackle these health disparity challenges by implementing a research tool developed by the University of Miami with funding from the NIH’s Clinical and Translational Science Award Program. The University Research Informatics Data Environment, also referred to as URIDE, is a web-based platform that aggregates and visualizes de-identified data from multiple clinical health systems inside the organization. URIDE enables clinical research investigators and their teams to simply explore demographics, diagnoses, procedures, vitals, medications, labs, notes, allergies, comorbidities and other information.
URIDE previously received funding from the NIH Clinical and Translational Science Award program. This latest pilot program will increase URIDE’s utilization with a much wider expansion of using this cyber infrastructure platform.
“We’re very excited to collaborate with FAU and Caridad to expand the URIDE platform, making a more representative community with this cutting-edge, health informatics tool,” said Tsinoremas.
The project team will establish a research environment to support the identification of research cohorts. Using URIDE, and with the incorporation of AI/ML and IoT, they’ll give you the chance to conduct distant health monitoring. Patients with cardiometabolic health conditions corresponding to hypertension and diabetes can be monitored remotely, which can enable the Caridad Center to implement a tailored AI/ML query and analytical platform of their EHR and conduct personalized queries of their research questions to deal with chronic disease inside their patient population.
“As a medical school of the community and for the community, we’re very excited to collaborate with the Caridad Center and the University of Miami to bring together experts and resources to advance the goals of the National Institutes of Health’s AIM-AHEAD program,” said Julie Pilitsis, M.D., Ph.D., dean and vice chairman of medical affairs, Schmidt College of Medicine. “AI and machine learning are powerful tools that may help us to optimize health care delivery and drive health care innovation.”
Source:
Florida Atlantic University