{
  "abstract": "Background: Ambient AI documentation reduces documentation burden and electronic health record (EHR) time for ambulatory clinicians. Newer features also queue orders and offer some level of coding support for clinician review. This study compares two commercial products deployed at UCLA Health. Objective: To compare Nabla and Epic Systems, Inc. ambient AI solution among ambulatory clinicians at UCLA Health on usability, documentation burden, perceived note quality, adoption, EHR time and productivity, clinician-reported experience with order queueing and coding support, coding and billing patterns and integrity, work productivity, and patient-reported communication experience. Methods: Two-arm parallel-group randomized trial, 1:1, among 374 ambulatory clinicians at a single academic health system who hold an active license for a standalone ambient application (Nabla). Randomization is covariate-constrained where cohort size permits, balancing age, sex, half-day clinic sessions, specialty group, and baseline System Usability Scale (SUS) score. Intervention runs 11/9/2026 to 1/17/2027, with the first four weeks as lead-in. The primary outcome is SUS score at follow-up, compared between arms. Analysis is by intention-to-treat using mixed-effects models. Ethics and dissemination: Determined exempt by the UCLA Institutional Review Board (IRB-26-2147). Survey completion indicates consent. No patient-level data are collected. Findings will directly inform operational decision making and will be published regardless of direction.",
  "abstract_shown": true,
  "affiliations": [
    "UCLA Health Information Technology, UCLA Health, University of California, Los Angeles"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 10,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "A. T. Chin"
    },
    {
      "name": "K. Leung"
    },
    {
      "name": "S. Vangala"
    },
    {
      "name": "H. Woo"
    },
    {
      "name": "T. Kingsley"
    },
    {
      "name": "A. Sandhu"
    },
    {
      "name": "L. Jalalian"
    },
    {
      "name": "E. M. Cheng"
    },
    {
      "name": "J. N. Mafi"
    },
    {
      "name": "P. J. Lukac"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/565dvqqmv38hc.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.11.07.26367514",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.11.07.26367514v1.full",
  "id": "565dvqqmv38hc",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.11.07.26367514v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "health informatics"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.11.07.26367514v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-07",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/565dvqqmv38hc.ris",
  "sources": [
    {
      "first_seen": "2026-11-10T00:22:41Z",
      "native_id": "10.64898/2026.11.07.26367514",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.11.07.26367514v1"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:health informatics",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "Randomized Trial Protocol: Head-to-Head Comparison of Two Ambient Artificial Intelligence Documentation Tools on Clinician Usability",
  "title_text": "Randomized Trial Protocol: Head-to-Head Comparison of Two Ambient Artificial Intelligence Documentation Tools on Clinician Usability",
  "type": "preprint",
  "updated_at": "2026-11-10T00:22:41Z",
  "url": "https://research.draconitic.com/paper/565dvqqmv38hc",
  "venue": "medRxiv",
  "versions": []
}