Digital Easy Breathing (DEB)
Team Approach: The Research IT Builds Team collaborated closely with the UF College of Medicine research group to develop and test DEB. A digital adaptation of Easy Breathing®, an evidence-based clinical decision support system (CDS) for pediatric asthma management. DEB integrates directly into the Epic EHR, replacing paper-based workflows with a streamlined, user-friendly digital experience for providers and families. The team utilized:
• Patient-facing questionnaires built in MyChart
• Our Practice Advisory; OPA triggered by algorithm-based logic
• SmartSets and SmartText for guided treatment planning
• After-visit summary integration for patient education
Clinical testing in Epic’s Proof of Concept and Clinical Validation (sandbox) environments
Weekly meetings, agile development cycles, and end-user feedback sessions with pediatric and family medicine providers ensured iterative refinement and high usability.
Delivered Product:
• Custom MyChart parent survey for asthma screening
• BPA alerts and asthma severity classification tools
• SmartSet-based asthma treatment planning
• Integrated documentation to support provider workflow
• Usability-tested Epic sandbox build ready for broader evaluation
• Screenshots and mockups to assist NIH grant application for full deployment
Build Effort: The project required approximately 6 months total, representing a Medium build size project.
Outcomes: Successful usability test and grant submitted to NIH – under review
Study Principal Investigator & Contact:
David Fedele, Ph.D., ABPP – PI
Principal Research Scientist, Nemours Children’s Health, Jacksonville
david.fedele@nemours.org
Megan Gregor, PhD
Associate Professor of Health Outcomes & Biomedical Informatics
University of Florida
megan.gregory@ufl.edu
DEMONSTRATE – Prediction Algorithm for Patients at Risk for Opioid Overdose/Use Disorder
Team Approach: The Research IT team, in collaboration with faculty, clinicians, and technical experts across UF Health, implemented a multidisciplinary build process. This team approach integrates expertise from the study team, Integrated Data Repository (IDR) analysts, Epic builders, Enterprise Software Engineering (ESE) database developers, and interface specialists to design, test, and deliver a comprehensive clinical decision support tool for primary care providers
Delivered Product: The team developed an AI driven- Our Practice Advisory (OPA; also known as Best Practice Advisories or Best Practice Alerts) integrated into Epic that alerts primary care providers enrolled in the study when a patient is at high risk of opioid overdose or opioid use disorder. The tool includes:
• A predictive algorithm score incorporated into the patient flow sheet.
• A real-time OPA that triggers during opioid prescribing.
• A custom HL7 messaging app, risk score database, and reporting workbench (RWB) reporting.
• Full deployment in UF Gainesville outpatient Family and Internal Medicine clinics.
Build Effort: The project required approximately 134 total hours, representing a Large build—a major custom Epic integration and system development project.
Outcomes: Clinical trial ongoing to collect data on performance and feedback from providers. Publication on the development method: PMID 394420438
Study Principal Investigator & Contact:
Dr. Khoa Nguyen, Site- PI
Clinical Associate Professor, University of Florida College of Pharmacy
Khoanguyen@cop.ufl.edu
Dr. Jenny Lo-Ciganic, PI
Professor of Medicine,
University of Pittsburgh, Department of Medicine
jenny.lociganic@pitt.edu
MyPain and Pain Manager Integration for Shared Decision-Making in Chronic Pain Care
Team Approach: The Research IT Builds team collaborated with clinical and academic partners to locally adapt, integrate, and evaluate two SMART on FHIR third-party applications: MyPain (patient-facing) and Pain Manager (clinician-facing). The project utilized user-centered design and agile development methodologies, engaging stakeholders such as UF Health’s Epic team, Integrated Data Repository (IDR), Enterprise Software Engineering, and Epic training units. Development relied on open-source Docker containers from prior implementations at Vanderbilt and University of Chicago, adapted to UF Health’s Epic infrastructure.
Delivered Product: The finalized product consists of two interoperable applications embedded in the Epic EHR. MyPain enables patients to input pain-related assessments and receive educational resources via MyChart. Pain Manager synthesizes this input with key EHR data, providing clinicians with a decision support interface for pain treatment that aligns with patient goals and reduces opioid-related risks. The pilot was deployed in 8 UF Health Jacksonville primary care clinics, with full Epic integration and training completed.
Build Effort: This was a large, multi-unit build completed over 41 weeks and requiring more than 500 total staff hours.
Outcomes: Pragmatic trial completed on 8/2025. Pending data analysis. Study protocol manuscript: PMID 35841043
Study Principal Investigators and Contact
Dr. Ramzi Salloum, PI
University of Florida Health
rsalloum@ufl.edu
Dr. Christopher Harle, Co-PI
Professor, Indiana University
charle@iu.edu
Dr. Khoa Nguyen, Co-I, IT build support
Clinical Associate Professor, University of Florida College of Pharmacy
Khoanguyen@cop.ufl.edu
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