# An Outcome-Focused Measure of Mental Health Care Quality based on Standardized Patient-Reported Symptoms

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2024 · $588,455

## Abstract

PROJECT SUMMARY / ABSTRACT
 There are various psychological, cognitive, behavioral, medication and neurostimulation treatments
that can improve the outcomes of people with common depressive and anxiety disorders. However, in usual
practice, there is large variability in provider characteristics and delivery of treatments. Routine treatments are
often poorly characterized and structured clinical data on patients are scarce. The effectiveness and quality of
routine mental health services in the community are not accurately monitored and are poorly understood. It
will be necessary to implement monitoring of treatment quality so that treatment and outcomes can be
improved. At present, healthcare organizations, payers, and policy makers usually know little about the quality
of care they support. Similarly, patients and their families have very limited information on quality to guide
their choice of provider or treatment organization.
 This study develops, tests and validates a new, transdiagnostic outcome-focused mental health quality
measure. This measure is based on routine, regular patient reports of their symptoms. The measure can be
aggregated at the provider, clinic, organization or plan level; inform choice of provider; and be used to improve
routine delivery of services and health equity and reduce disparities among patients with common psychiatric
disorders. The quality measure is broadly relevant across community settings and populations, and suitable for
endorsement by regulatory and governing bodies. The study is guided by partnership with stakeholders and
end-users of quality measurement. The project aims to: 1) analyze existing data with responses to a wide
variety of items that are known to assess depression or anxiety, and empirically select symptom items for a
transdiagnostic outcome-focused quality measure; 2) inform risk adjustment and benchmarking of the quality
measure by studying the effects on outcomes of patient, provider, and practice factors, including social
determinants of health, baseline symptom severity, and diagnoses; and, 3) fully specify an outcome-focused
quality measure that includes risk adjustment and benchmarks for improvement; and study, at practices
nationally, its feasibility and psychometric properties, the effect of treatment characteristics on the quality of
care, and the effect of quality on health-related quality of life.
 The study leverages a unique existing database that contains more than 5 million symptom assessments
from 500,000 patients collected during treatment episodes with more than 5,000 providers and 200 real-
world practices. These patient-reported outcomes are supplemented with data on the characteristics of
patients, providers and treatment organizations. Analyses use psychometric methods, item response theory,
and hierarchical and longitudinal modeling to study symptom data from patients over time during episodes of
care. Results support development of an outcomes-focused quality measure ...

## Key facts

- **NIH application ID:** 10947949
- **Project number:** 1R01MH137080-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Alexander S. Young
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $588,455
- **Award type:** 1
- **Project period:** 2024-08-02 → 2028-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10947949

## Citation

> US National Institutes of Health, RePORTER application 10947949, An Outcome-Focused Measure of Mental Health Care Quality based on Standardized Patient-Reported Symptoms (1R01MH137080-01). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10947949. Licensed CC0.

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