# Maximizing Online Obesity Treatment Response in the Primary Care Environment Using Clinical Decision Support

> **NIH NIH K23** · MIRIAM HOSPITAL · 2021 · $187,418

## Abstract

PROJECT SUMMARY/ABSTRACT
With the long-term career goal of becoming a leading independent researcher using technology-driven
precision medicine approaches to improve obesity outcomes in primary care, the candidate, Dr. Hallie Espel-
Huynh, PhD, proposes a mentored research project and career development plan that will prepare her to use
advanced analytics to personalize routine clinical care for patients with obesity. Despite the promise of online
interventions to maximize access to effective behavioral obesity treatments in primary care, many patients do
not benefit due to nonresponse. Evidence-based rescue interventions (EBRI) can improve outcomes for these
patients, however, primary care clinicians require guidance on when and how to intervene, and such a tool
does not yet exist. Clinical decision support (CDS) has the potential to fill this gap by predicting risk for
nonresponse, delivering alerts about this risk to clinicians, and enabling interventions to reverse it. The overall
objective of this training application is to develop such a CDS for use in primary care and test its usability with
primary care clinicians. The proposal aims to (1) use stakeholder input to align the content and format of the
CDS with primary care providers’ needs, (2) build a machine learning model to predict early risk for online
obesity treatment nonresponse for integration into the CDS, and (3) design the prototype CDS and test its
usability with primary care clinicians, focusing on outcomes of feasibility, acceptability, and appropriateness for
the target primary care setting. This project is the first to combine precise nonresponse risk prediction with
stakeholder-informed CDS to produce a tool that has the potential to maximize obesity treatment outcomes in
primary care via delivery of CDS-facilitated, clinician-delivered rescue interventions. This research will result in
a complete CDS tool that is ready for future clinical testing with patients in primary care, and which could
greatly enhance the potential impact of online obesity treatment in this setting. The research plan is
complemented by career development activities that include formal training in technology-assisted obesity and
CVD management in primary care, stakeholder-centered CDS development, machine learning, and mixed
methods for patient-oriented implementation research. Under the guidance of an experienced mentorship
team, execution of the proposed research and training plan will lead Dr. Espel-Huynh to submission of a
competitive R01 grant application to test CDS effectiveness in a pragmatic randomized clinical trial.

## Key facts

- **NIH application ID:** 10301403
- **Project number:** 1K23HL155733-01A1
- **Recipient organization:** MIRIAM HOSPITAL
- **Principal Investigator:** Hallie Espel-Huynh
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $187,418
- **Award type:** 1
- **Project period:** 2021-08-01 → 2022-02-26

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10301403

## Citation

> US National Institutes of Health, RePORTER application 10301403, Maximizing Online Obesity Treatment Response in the Primary Care Environment Using Clinical Decision Support (1K23HL155733-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10301403. Licensed CC0.

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