# Developing Interoperable tools for anxiety and depression screening

> **NIH NIH R03** · WAKE FOREST UNIVERSITY HEALTH SCIENCES · 2022 · $77,500

## Abstract

Project Summary
 Anxiety and depression are prevalent in neurological disorders and other chronic conditions requiring
specialty care, and these comorbidities are often under-recognized and undertreated, despite greater impact
on outcomes than the primary chronic condition. Clinician time-related barriers to screening contribute to
undertreatment. Epilepsy is a key example, with well-documented undertreatment of anxiety and depression
despite high prevalence and impact, and data indicating that patients prioritize treatment and prefer to be
treated in a neurology clinic for depression and anxiety. Tools and strategies are needed to reduce burden of
anxiety and depression screening in neurology clinics and other subspecialty settings, to close care gaps and
facilitate multicenter implementation and effectiveness studies of evidence-based interventions such as
collaborative care models that involve repeated symptom monitoring with anxiety and depression instruments.
Our group successfully implemented screening in a tertiary epilepsy center using electronic health record
(EHR)-based tools enabling patient self-completion of instruments after brief nursing staff activation. This more
than quadrupled screening, but a substantial gap remained due to the nursing activation step, and barriers to
scaling included lack of EHR/research database integration and need for custom EHR build at each potential
site for future multicenter studies. Interoperable tools facilitating independent patient self-completion are
needed to support multicenter intervention trials with symptom monitoring and scale implementation strategies.
Thus, in this proposal we aim to develop and refine interoperable tools for anxiety and depression screening.
 Specifically, in Aim 1 we will evaluate screening completion (primary) and process measures comparing
interoperable, REDCap-based methods to EHR patient portal-based methods for delivering validated anxiety
and depression instruments to epilepsy patients. This will be accomplished in a randomized study with N=220
individuals per arm comparing 4 delivery modalties (Twilio text vs. REDCap survey vs. EHR portal
questionnaires with reminder vs. standard EHR portal questionnaires). In Aim 2, we will evaluate and
implement a reproducible approach to EHR and research system integration of Epic EHR flowsheet data with
REDCap via Kit Flowsheets Application Programming Interface (API). We will also develop and disseminate a
governance process to accomplish bidirectional integration for EHR flowsheet data with REDCap via Epic’s
AddFlowsheetValue API.
 This R03 project will be instrumental to support next-step larger scale grant applications for the
principal investigator examining collaborative care model effectiveness in neurology settings and screening
implementation. The proposal is relevant across chronic conditions treated by subspecialists and highly
translational, overcoming key roadblocks to translation in clinical implementation resea...

## Key facts

- **NIH application ID:** 10512151
- **Project number:** 1R03TR004251-01
- **Recipient organization:** WAKE FOREST UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Heidi Munger Clary
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $77,500
- **Award type:** 1
- **Project period:** 2022-08-01 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10512151

## Citation

> US National Institutes of Health, RePORTER application 10512151, Developing Interoperable tools for anxiety and depression screening (1R03TR004251-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10512151. Licensed CC0.

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