# Leveraging Electronic Health Records to Measure and Reduce Harmful, Low-Value Care Among Older Adults

> **NIH NIH K76** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2020 · $243,000

## Abstract

ABSTRACT
 I (John N. Mafi, MD, MPH) am an Assistant Professor at UCLA, with a secondary Natural Scientist
appointment at RAND. I practice general internal medicine and pursue health services research focused on
identifying and reducing low-value care—patient care that provides no net benefit in specific clinical scenarios,
and can also cause harm. After receiving outstanding training in health services research at Harvard University
and publishing a series of papers on low-value care, I have turned the focus of my research on studying older
adults because they disproportionately suffer from low-value care and its consequences. A major barrier to
reducing low-value care in older adults is a lack of valid measures: current measurement relies on claims data
(e.g., billing claims physicians submit to Medicare) that lack enough clinical detail to correctly classify care as
“low value.” In contrast, electronic health records (EHRs) contain richer clinical data and are also a potential
tool for reducing low-value care. To advance my career goals and improve care for older adults, I propose to
develop an EHR-based low-value care measure (“eMeasure”), and then design and test an intervention
consisting of a behavioral economic EHR clinical decision support tool (EHR CDS) to reduce low-value care in
older adults. My prototype focus will address low-value proton pump inhibitor (PPI) drugs, which are associated
with some harm. My overarching goal is to improve the health and healthcare of older Americans by becoming
a leading principal investigator utilizing the EHR to measure and reduce low-value care in older adults.
 To achieve this goal, I seek support from the NIA Beeson Career Development Award. I have the support
of an outstanding group including primary mentor Dr. Catherine Sarkisian (Professor, PI of NIA-R01 pragmatic
trial), co-primary mentor Dr. Cheryl Damberg (PI of RAND/AHRQ U19 Center), mentors Dr. Ron Hays (Quality
Measure Expert), Dr. Eric Cheng (Chief Medical Informatics Officer), Dr. Noah Goldstein (Economist), and
collaborators Dr. Folasade May (Gastroenterologist), Dr. Sam Skootsky (Chief Medical Officer), and Dr. Chi-
Hong Tseng (Statistician). I will acquire skills in EHR-based quality measure development and utilization
(Damberg/Hays/Cheng), geriatrics (Sarkisian), behavioral economics and behavior change (Goldstein),
pragmatic trials testing user-centered EHR decision support (Sarkisian/Damberg/Cheng), and leadership.
 I propose 3 specific aims for my career development: (1) Develop and test an eMeasure of low-value PPI
prescriptions among older adults, (2) Design and pilot test an intervention (behavioral economic EHR CDS) to
reduce low-value PPI prescriptions in older adults to determine feasibility and (3) Implement and evaluate a
delayed-onset pragmatic trial of the intervention at UCLA Health—informing an NIA R01 proposal for a
multisite pragmatic trial. I will apply knowledge learned from my training to Aims #1-3. The Beeson Awa...

## Key facts

- **NIH application ID:** 10029513
- **Project number:** 1K76AG064392-01A1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** John N. Mafi
- **Activity code:** K76 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $243,000
- **Award type:** 1
- **Project period:** 2020-09-15 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10029513

## Citation

> US National Institutes of Health, RePORTER application 10029513, Leveraging Electronic Health Records to Measure and Reduce Harmful, Low-Value Care Among Older Adults (1K76AG064392-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10029513. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*