# Hybrid Closed Loop Insulin Pump use in Poorly Controlled Type 1 Diabetes

> **NIH NIH K23** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2022 · $173,849

## Abstract

Project Summary/Abstract
This career development award will establish me (Dr. Estelle Everett MD, MHS), as an independent
investigator focused on evaluating and addressing disparities in management and outcomes in vulnerable
patient populations with type 1 diabetes (T1D). This K23 award will provide the support I need to develop
expertise in three key areas: 1) EMR-based retrospective data analysis and natural language processing
(NLP) methods, 2) clinical trial design, implementation, and analysis, and 3) qualitative study development,
data collection and analysis.
After receiving my medical and research training in at Johns Hopkins and publishing a series of general
diabetes papers, my research interests have increasingly focused on patients with poorly controlled T1D. I
am committed to improving care and outcomes in this complex group of patients whose long duration of T1D
increases their risk of developing complications early in their lifetime. Although diabetes technology has
revolutionized T1D management, disparities in technology access are evident among racial-ethnic minorities,
patients with lower socioeconomic status and those with poorly controlled T1D.
To help address these gaps, it is critical to leverage electronic health record (EHR) data to readily identify
patients experiencing diabetes technology disparities. In order to examine whether diabetes technology can
reduce diabetes care burdens and enhance outcomes among some of highest need patients, we need to
expand diabetes technology clinical trials beyond the very select populations included thus far (ie., mostly
White, higher SES). Therefore, I propose to: 1) To develop and validate a novel electronic medical record
(EMR) algorithm using natural language processing (NLP) to identify insulin pump and/or CGM use among
patients with type 1 diabetes; 2) To perform a pilot RCT of hybrid closed-loop insulin pump therapy (HCL) in
40 diverse adult patients with poorly controlled T1D (HbA1c >9%) from the largest academic and safety net
health systems in the Los Angeles region; and 3) To identify facilitators and barriers of effective use of
closed loop insulin pump therapy in patients with poorly controlled T1D. Findings from Aim 1 can be readily
used to support T1D care in other settings and findings from Aims 2 and 3 will also be used to inform a future
RCT as part of a future NIDDK R01 application. This K23 award will provide the support to complete these
aims and my educational objectives, which will provide me with the training and skills needed to become a
national leader and independent clinician-investigator aimed to improve outcomes in vulnerable populations
with T1D.

## Key facts

- **NIH application ID:** 10429863
- **Project number:** 1K23DK132482-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Estelle Marla Everett
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $173,849
- **Award type:** 1
- **Project period:** 2022-04-19 → 2027-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10429863

## Citation

> US National Institutes of Health, RePORTER application 10429863, Hybrid Closed Loop Insulin Pump use in Poorly Controlled Type 1 Diabetes (1K23DK132482-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10429863. Licensed CC0.

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