Health AI Central
Peer-Reviewed Publication
Appl Clin Inform2026;17(4):834-843.August 1, 2026Journal Article

The Effects of Artificial Intelligence in Quality Assessment of Outpatient Mental Health Services on Human Auditors.

Hayden T McLeod1, Joshua L Cohen1, Dena M Bravata1,2, Roma M Bajaria1, Kelvin Tran1, Neha P Chaudhary1,3, Nicole M Benson1,4, Jeff Gould1,5
1TherapyMatch, Inc (dba Headway), New York, United States, New York.
2Stanford University, Center for Primary Care and Outcomes Research, California, United States, San Mateo.
3Massachusetts General Hospital, Harvard Medical School, Massachusetts, United States, Boston.
4McLean Hospital, Harvard Medical School, Massachusetts, United States, Belmont.
5University of California, California, United States, San Francisco.
PubMed PMC DOI PDF

Abstract

ABSTRACT: BACKGROUND: The use of large language model (LLM)-based artificial intelligence (AI) to assess the quality of outpatient mental health documentation represents an understudied application. Critical questions remain about the effects of exposing human auditors to AI-generated recommendations on auditor efficiency, agreement, and patterns of decision-making. ABSTRACT: OBJECTIVES: The obje…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free AccountSign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.