Data Visualization

Quality of answers of generative large language models versus peer users for interpreting laboratory test results for lay patients: Evaluation study.

Citation
He Z, Bhasuran B, Jin Q, Tian S, Hanna K, Shavor C, Arguello LG, Murray P, Lu Z. Quality of answers of generative large language models versus peer users for interpreting laboratory test results for lay patients: Evaluation study. J Med Internet Res. 2024 Apr 17;26:e56655. doi: 10.2196/56655. PMID: 38630520; PMCID: PMC11063893.
Principal Investigator
He, Zhe
Lustria, Mia Liza A.
Project Name
LabGenie: A Patient-Engagement Tool to Aid Older Adults' Understanding of Lab Test Results

A web-based tool to perform a values clarification for stroke prevention in patients with atrial fibrillation: Design and preliminary testing study.

Citation
Dorsch MP, Flynn AJ, Greer KM, Ganai S, Barnes GD, Zikmund-Fisher B. A web-based tool to perform a values clarification for stroke prevention in patients with atrial fibrillation: Design and preliminary testing study. JMIR Cardio. 2025 Apr 11;9:e67956. doi: 10.2196/67956. PMID: 40215398; PMCID: PMC12007723.
Principal Investigator
Dorsch, Michael
Project Name
A User-Centered Designed Anticoagulation Shared Decision Making Tool for Stroke Prevention in Atrial Fibrillation

Facilitators and barriers to integrating patient-generated blood pressure data into primary care EHR workflows.

Citation
Canfield SM, Koopman RJ. Facilitators and barriers to integrating patient-generated blood pressure data into primary care EHR workflows. Appl Clin Inform. 2024 Oct;15(5):942-951. doi: 10.1055/s-0044-1790554. Epub 2024 Nov 13. PMID: 39537189; PMCID: PMC11560398.
Principal Investigator
Koopman, Richelle J.
Project Name
Optimizing Display of Blood Pressure Data To Support Clinical Decision Making

Development and Assessment of Artificial Intelligence (AI)-Enhanced Pretreatment Peer-review Process to Improve Patient Safety in Radiation Oncology

Description

This research develops and evaluates an artificial intelligence-enhanced pretreatment peer-review process in radiation oncology, aiming to improve patient safety by reducing variability among providers in treatment planning, minimizing clinical errors, and enhancing overall treatment outcomes.

Grant Number
R18 HS029474
Principal Investigator(s)
Mazur, Lukasz
Marks, Lawrence B

Improving Pediatric Donor Heart Utilization with Predictive Analytics

Description

This study aims to optimize the use of donor hearts for infants and children awaiting heart transplantation by developing predictive models to assess in real-time the potential for transplant success and to evaluate risk. Researchers plan to display these data through intuitive visualizations on a custom-built interface to reduce clinicians’ cognitive burden, enhance decision making confidence, and help ensure the best donor match for pediatric patients.

Grant Number
R21 HS029548
Principal Investigator(s)
McCulloch, Michael
Porter, Michael

Patient perceptions of an electronic-health-record-based rheumatoid arthritis outcomes dashboard: A mixed-methods study.

Citation
Nasrallah C, Wilson C, Hamblin A, Hariz C, Young C, Li J, Yazdany J, Schmajuk G. Patient perceptions of an electronic-health-record-based rheumatoid arthritis outcomes dashboard: A mixed-methods study. BMC Med Inform Decis Mak. 2024 Oct 12;24(1):302. doi: 10.1186/s12911-024-02696-9. PMID: 39395970; PMCID: PMC11470722.
Principal Investigator
Schmajuk, Gabriela
Project Name
Incorporating PRO Data Into RA Clinical Encounters Using Health-IT (PACT)

A step-by-step roadmap for the development and deployment of an electronic health record sidecar application that tracks patient outcomes: The RA PRO dashboard.

Citation
Schmajuk G, Nasrallah C, Berrean B, Prugh J, Wilson C, Hamblin A, Young C, Jacobsohn L, Kay J, Li J, Kersey E, Subash M, Murray S, Yazdany J. A step-by-step roadmap for the development and deployment of an electronic health record sidecar application that tracks patient outcomes: The RA PRO dashboard. Digit Health. 2024 Oct 10;10:20552076241288739. doi: 10.1177/20552076241288739. PMID: 39421306; PMCID: PMC11483702.
Principal Investigator
Schmajuk, Gabriela
Project Name
Incorporating PRO Data Into RA Clinical Encounters Using Health-IT (PACT)

i-Matter: Investigating an mHealth Texting Tool for Embedding Patient-Reported Data into Diabetes Management - Final Report

Citation
Schoenthaler A., Mann D. i-Matter: Investigating an mHealth Texting Tool for Embedding Patient-Reported Data into Diabetes Management – Final Report. (Prepared by New York University School of Medicine under Grant No. R01 HS026522). Rockville, MD: Agency for Healthcare Research and Quality, 2023.
Principal Investigator
Schoenthaler, Antoinette
Mann, Devin M
Project Name
i-Matter: Investigating an mHealth Texting Tool for Embedding Patient-Reported Data into Diabetes Management