# Improving Glaucoma Care Using a Scalable Decision Support System

> **NIH NIH K23** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2022 · $243,235

## Abstract

PROJECT SUMMARY/ABSTRACT
Through the training outlined in this K23 award, Dr. Brian Stagg will become an independent investigator in
health services research using health information technology to decrease glaucoma blindness by enhancing
clinical decision making for glaucoma to ensure that patients receive appropriate glaucoma care.
CANDIDATE BACKGROUND: Dr. Stagg is an Assistant Professor specialized in glaucoma at the University
of Utah. Following ophthalmology residency, he completed a 2-year health services research fellowship at the
University of Michigan and earned a Master of Health and Healthcare Research degree, followed by a
glaucoma fellowship at Duke University. He has background experience in health services research, healthcare
delivery research, data science, and biostatistics. CAREER DEVELOPMENT PLAN: To succeed as an
independent investigator, Dr. Stagg needs additional training in: (1) Clinical Decision Support (CDS) system
workflow and implementation research, (2) CDS system design and human factors research, (3) CDS system
EHR integration using health informatics standards, and (4) research leadership and grant writing. The
training and mentorship outlined in this K23 will give Dr. Stagg this needed expertise. MENTORS: Through
the supportive research and mentorship environment at the University of Utah and his connections with
mentors from the University of Michigan and Duke University, Dr. Stagg has put together an innovative
interdisciplinary mentoring and advising team lead by Dr. Rachel Hess, his primary mentor. CLINICAL
PROBLEM: Up to 30% of patients who are actively treated for glaucoma continue to have significant visual
field loss and need intensification of treatment to lower eye pressure and prevent further loss. Proper
identification and management of such progressive visual field loss is vital to prevent blindness from
glaucoma. This is a challenge for clinicians caring for patients with glaucoma as they must incorporate large
amounts of longitudinal data from many data sources accurately and efficiently. Optimized, workflow-
appropriate CDS systems can help address this challenge. CDS systems present information to clinicians at the
point of care to improve decision making. SPECIFIC AIMS: Dr. Stagg will (Aim 1) understand differences
between ophthalmologic specialists and generalists in glaucoma clinical decision-making workflow and
workload, (Aim 2) iteratively refine the Glaucoma CDS System and evaluate its efficacy in a pre-clinical
setting, and (Aim 3) integrate the Glaucoma CDS System with the EHR and pilot for feasibility and usability in
clinics to deliver personalized recommendations to clinicians for visual field testing frequency. The completion
of these aims will result in (1) a rigorously developed, user-centered, scalable CDS system to help clinicians
determine a personalized visual field testing frequency for patients with glaucoma and (2) generalizable
knowledge that will support future CDS developme...

## Key facts

- **NIH application ID:** 10447378
- **Project number:** 1K23EY032577-01A1
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Brian Stagg
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $243,235
- **Award type:** 1
- **Project period:** 2022-05-01 → 2027-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10447378

## Citation

> US National Institutes of Health, RePORTER application 10447378, Improving Glaucoma Care Using a Scalable Decision Support System (1K23EY032577-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10447378. Licensed CC0.

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