Original Medical Notes Versus AI Plain-Language Summaries

NCT07602725 | Not Yet Recruiting

• 1 other identifier: STUDY00008863
• Study Type: interventional
• Target: 135
• Locations: 0 countries
• Sites: N/A

Brief Summary

The goal of this clinical trial is to learn how patients feel when reading their medical notes. The study compares reading the original doctor's note with reading a simpler, Artificial Intelligence (AI)-generated version written in plain language in adults receiving musculoskeletal specialty care. The main questions the study aims to answer are:

• Read either their original clinic note or a plain-language summary of the note
• Complete short questionnaires about their experience, emotions, and trust in their clinician
• Optionally provide written comments about how it felt to read the information

Conditions

Orthopedic Patients; Musculoskeletal Disease

Keywords

Artificial intelligence; Musculoskeletal Care; Patient experience; Medical documentation

Outcome Measures

Primary Outcomes (1)

• Trust and Experience with the Clinician Scale (TRECS-7)

  The Trust and Experience with the Clinician Scale (TRECS-7) is a validated 7-item scale that measures patients' trust in and experience with their clinician during a medical consultation. Designed to minimize ceiling effects, it enables more sensitive detection of variation in patient experience across different clinical interactions (Brinkman et al.). Each of 7 statements is scored from 0-4 (strongly disagree, disagree, neutral, agree, strongly agree), resulting in a total score between 0 and 28. Higher scores indicate greater perceived trust in the clinician. Source: Brinkman N, Looman R, Jayakumar P, Ring D, Choi S. Is It Possible to Develop a Patient-reported Experience Measure With Lower Ceiling Effect? Clin Orthop Relat Res. 2025 Apr 1;483(4):693-703. Time Frame: Measured once, immediately following consultation with the musculoskeletal specialist

  Immediately after visit

Secondary Outcomes (2)

• Emotional response to medical note

  Immediately after intervention

• Themes identified by the LLM in verbatim text

  Collected immediately after intervention/control

Study Arms (2)

Intervention (LLM-simplified notes)

EXPERIMENTAL

Participants randomized to the intervention arm will review a plain-language summary generated from a curated version of their prior musculoskeletal clinic note using a large language model (LLM). All protected health information (PHI) and identifying information will be removed prior to LLM processing. The summary will be designed to simplify medical terminology and improve readability while maintaining the original clinical meaning of the note. The specific LLM used has not yet been finalized but will likely consist of the most current version of ChatGPT and/or Perplexity available through institutionally approved platforms at the time of the study. Participants will review the summary on an iPad prior to their clinic visit and complete questionnaires assessing trust, experience, and emotional responses.

Behavioral: LLM-Generated Medical Note

Control (Original medical note)

ACTIVE COMPARATOR

Participants randomized to the control arm will review the original clinical note from their prior musculoskeletal clinic visit. The note will be presented in its original format without language simplification. Participants will review the note on an iPad prior to their clinic visit and complete questionnaires assessing trust, experience, and emotional responses.

Behavioral: Control (Original Medical Note)

Interventions

LLM-Generated Medical Note BEHAVIORAL

The intervention consists of presenting participants with an LLM-generated plain-language summary of a prior musculoskeletal clinic note. The summary will be produced from a curated version of the original documentation after removal of all protected health information (PHI), macros, and administrative content. Physical therapy notes will be excluded, and normal examination or imaging findings may be simplified (e.g., "Exam otherwise normal"). The LLM will be instructed to preserve clinical meaning while reducing jargon and improving readability. The summary will be concise, neutral in tone, and written in patient-friendly language without adding new medical information or altering clinical recommendations. The specific LLM platform is not yet finalized but will likely use the most current version of ChatGPT and/or Perplexity available through institutional access.

Intervention (LLM-simplified notes)

Control (Original Medical Note) BEHAVIORAL

Participants randomized to the control arm will review the original clinical note from their prior musculoskeletal clinic visit. The note will be presented in its original format without language simplification. Participants will review the note on an iPad prior to their clinic visit and complete questionnaires assessing trust, experience, and emotional responses.

Control (Original medical note)

Eligibility Criteria

• Age: 18 Years - 89 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Adult (18-89)
• Seeking outpatient musculoskeletal specialty care
• English language literacy
• Return patient to the clinic

You may not qualify if:

• \- Any impairment precluding completion of a survey on a tablet

Sponsors & Collaborators

• University of Texas at Austin: lead

Related Publications (11)

• Park J, Saha S, Chee B, Taylor J, Beach MC. Physician Use of Stigmatizing Language in Patient Medical Records. JAMA Netw Open. 2021 Jul 1;4(7):e2117052. doi: 10.1001/jamanetworkopen.2021.17052.

  PMID: 34259849 BACKGROUND

• Delbanco T, Walker J, Bell SK, Darer JD, Elmore JG, Farag N, Feldman HJ, Mejilla R, Ngo L, Ralston JD, Ross SE, Trivedi N, Vodicka E, Leveille SG. Inviting patients to read their doctors' notes: a quasi-experimental study and a look ahead. Ann Intern Med. 2012 Oct 2;157(7):461-70. doi: 10.7326/0003-4819-157-7-201210020-00002.

  PMID: 23027317 BACKGROUND

• Walker J, Leveille S, Bell S, Chimowitz H, Dong Z, Elmore JG, Fernandez L, Fossa A, Gerard M, Fitzgerald P, Harcourt K, Jackson S, Payne TH, Perez J, Shucard H, Stametz R, DesRoches C, Delbanco T. OpenNotes After 7 Years: Patient Experiences With Ongoing Access to Their Clinicians' Outpatient Visit Notes. J Med Internet Res. 2019 May 6;21(5):e13876. doi: 10.2196/13876.

  PMID: 31066717 BACKGROUND

• Gerard M, Chimowitz H, Fossa A, Bourgeois F, Fernandez L, Bell SK. The Importance of Visit Notes on Patient Portals for Engaging Less Educated or Nonwhite Patients: Survey Study. J Med Internet Res. 2018 May 24;20(5):e191. doi: 10.2196/jmir.9196.

  PMID: 29793900 BACKGROUND

• Bell SK, Mejilla R, Anselmo M, Darer JD, Elmore JG, Leveille S, Ngo L, Ralston JD, Delbanco T, Walker J. When doctors share visit notes with patients: a study of patient and doctor perceptions of documentation errors, safety opportunities and the patient-doctor relationship. BMJ Qual Saf. 2017 Apr;26(4):262-270. doi: 10.1136/bmjqs-2015-004697. Epub 2016 May 18.

  PMID: 27193032 BACKGROUND

• Vranceanu AM, Elbon M, Adams M, Ring D. The emotive impact of medical language. Hand (N Y). 2012 Sep;7(3):293-6. doi: 10.1007/s11552-012-9419-z.

  PMID: 23997735 BACKGROUND

• Bala S, Keniston A, Burden M. Patient Perception of Plain-Language Medical Notes Generated Using Artificial Intelligence Software: Pilot Mixed-Methods Study. JMIR Form Res. 2020 Jun 5;4(6):e16670. doi: 10.2196/16670.

  PMID: 32442148 BACKGROUND

• Brinkman N, Looman R, Jayakumar P, Ring D, Choi S. Is It Possible to Develop a Patient-reported Experience Measure With Lower Ceiling Effect? Clin Orthop Relat Res. 2025 Apr 1;483(4):693-703. doi: 10.1097/CORR.0000000000003262. Epub 2024 Oct 25.

  PMID: 39466401 BACKGROUND

• Santesso N, Rader T, Wells GA, O'Connor AM, Brooks PM, Driedger M, Gallois C, Kristjansson E, Lyddiatt A, O'Leary G, Prince M, Stacey D, Wale J, Welch V, Wilson AJ, Tugwell PS. Responsiveness of the Effective Consumer Scale (EC-17). J Rheumatol. 2009 Sep;36(9):2087-91. doi: 10.3899/jrheum.090363.

  PMID: 19738218 BACKGROUND

• Brinkman N, Broekman M, Teunis T, Choi S, Ring D, Jayakumar P. A New Measure of Quantified Social Health Is Associated With Levels of Discomfort, Capability, and Mental and General Health Among Patients Seeking Musculoskeletal Specialty Care. Clin Orthop Relat Res. 2025 Apr 1;483(4):647-663. doi: 10.1097/CORR.0000000000003394. Epub 2025 Feb 5.

  PMID: 39915110 BACKGROUND

• Teunis T, Al Salman A, Koenig K, Ring D, Fatehi A. Unhelpful Thoughts and Distress Regarding Symptoms Limit Accommodation of Musculoskeletal Pain. Clin Orthop Relat Res. 2022 Feb 1;480(2):276-283. doi: 10.1097/CORR.0000000000002006.

  PMID: 34652286 BACKGROUND

MeSH Terms

Conditions

Musculoskeletal Diseases

Study Officials

• David Ring, MD, PhD

  Dell Medical School, University of Texas at Austin, TX, United States

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Emily H Jaarsma, MD

CONTACT

7472879601; emily.jaarsma@austin.utexas.edu

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: CARE PROVIDER, OUTCOMES ASSESSOR
• Purpose: HEALTH SERVICES RESEARCH
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Dean for Comprehensive Care; Professor and Associate Chair for Faculty Academic Affairs, Department of Surgery and Perioperative Care; Courtesy Professor of Psychiatry and Behavioral Sciences

Study Record Dates

• First Submitted: May 9, 2026
• First Posted: May 22, 2026
• Study Start: June 1, 2026
• Primary Completion (Estimated): December 1, 2026
• Study Completion (Estimated): February 1, 2027
• Last Updated: May 22, 2026

Record last verified: 2026-05

Data Sharing

• IPD Sharing: Will not share