# California Collaborative Network to Promote Data Driven Care and Improve Outcomes in Early Psychosis (EPI-CAL)

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA AT DAVIS · 2022 · $1,579,592

## Abstract

Project Summary
A prolonged first episode of psychosis (FEP) without adequate treatment is the most consistent predictor of
poor clinical and functional outcomes 1, poor health outcomes 2 and significant economic burden 3. Team-based
“coordinated specialty care” (CSC)4 for early psychosis (EP) has established effectiveness in promoting clinical
and functional recovery 5 . EP treatment programs have expanded rapidly with increased funding across the US
without formal coordination of training or implementation. While EP programs share many features, the lack of
state and national coordination and data infrastructure limits the capacity for large-scale evaluation or
accelerated dissemination of best practices 6. Based on prior collaborations with 30 California (CA) EP
programs and experiences using mobile health (MOBI mHealth) technology to measure individual outcomes in
EP care, the UC Davis (UCD) team is uniquely poised to create EPI-CAL, a CA network that will contribute
systematically collected outcomes data on over 1000 FEP clients per year, from 6 community and 6 university
EP clinics, to a national EP network supported by the NIMH EPINET program. Building on our prior work
evaluating CA EP programs, EPI-CAL programs will participate in a formative evaluation in Year 1 to define
core EP clinical features, intervention targets, and outcomes needed to harmonize network input. A “core
battery” based on current measures collected at the sites, the PhenX toolkit 7 and expanded to cover all critical
domains, will be installed across the network in Year 2. Core client outcomes and metrics of data use for
treatment decisions will be collected using the custom MOBI mHealth data network at the client, program, and
state level to allow easy data analysis, interpretation and dissemination. Training and ongoing monitoring will
be provided at all EPI-CAL sites to ensure appropriate implementation. EPI-CAL will contribute de-identified
data to the national coordinating hub. Using the RE-AIM implementation science framework 8,9, we will
systematically evaluate the impact of MOBI on EP programs across 5 dimensions: reach, efficacy, adoption,
implementation, and maintenance (see Figure 1). To demonstrate the network’s research capacity, in the R34
component of this application, we propose to develop and validate a measure of the Duration of Untreated
Psychosis (DUP) that is feasible for use in community settings and psychometrically sound. Although DUP is a
significant predictor of both short-term CSC treatment response5 and long-term outcomes 10 for FEP, no
measure currently exists that has been rigorously validated and is feasible for use by community providers 7,11.
We will utilize stakeholder feedback (clients, family members, academic experts and CSC staff) to develop a
tool with standardized DUP definitions that includes anchored assessment of psychosis onset and start of
treatment. Developing such a tool will allow standardized assessment of this critica...

## Key facts

- **NIH application ID:** 10437668
- **Project number:** 5R01MH120555-04
- **Recipient organization:** UNIVERSITY OF CALIFORNIA AT DAVIS
- **Principal Investigator:** Tara Ann Niendam
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $1,579,592
- **Award type:** 5
- **Project period:** 2019-09-10 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10437668

## Citation

> US National Institutes of Health, RePORTER application 10437668, California Collaborative Network to Promote Data Driven Care and Improve Outcomes in Early Psychosis (EPI-CAL) (5R01MH120555-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10437668. Licensed CC0.

---

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