Evaluating the Use of Artificial Intelligence to Improve Family Conversations for Intensive Care Patients and Their Families

NCT06756542 | Recruiting

• 1 other identifier: MEC-2024-0733
• Study Type: observational
• Target: 40
• Locations: 1 country
• Sites: 2

Brief Summary

This study looks at how artificial intelligence (AI), like generative pre-trained transformer (GPT-4), can help doctors in the intensive care unit (ICU) save time and improve communication with families. Right now, doctors spend a lot of time writing notes after family conversations, which takes time away from patient care. The investigators are testing whether AI can create accurate and easy-to-understand summaries of these conversations, making it quicker for doctors to document and clearer for families to understand. ICU doctors and adult family members of patients will take part in this study, with their full consent. The goal is to see if this new technology can make life easier for doctors while helping families better understand medical information.

Conditions

Intensive Care Medicine; Critical Care

Keywords

intensive care; artificial intelligence; large language models; administration reduction; patient satisfaction

Outcome Measures

Primary Outcomes (1)

• Documentation quality of family conversations

  The primary outcome measure is the documentation quality of family conversations, evaluated using a modified Physician Documentation Quality Instrument-9. Originally validated for progress notes and discharge summaries, Physician Documentation Quality Instrument-9 scores notes on nine attributes (accurate, thorough, useful, organized, comprehensible, succinct, synthesized, consistent, up-to-date) using a 1-5 scale (1 = "not at all," 5 = "extremely"), for a total ranging from 9 to 45. To adapt it for AI-generated text, the investigators removed the "up-to-date" domain (focused on whether the note includes the latest test results/recommendations) and added two new attributes: freedom from hallucinations (unfounded information) and freedom from bias (discriminatory data, algorithms, or heuristics). These additions address potential pitfalls in large language model outputs, such as introducing incorrect content or skewed results.

  Within 30 days after the family conversation.

Secondary Outcomes (2)

• Time spent on documentation by ICU clinicians

  Within one day after the family conversation.

• Family satisfaction

  Within 30 days after the family conversation.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Intensive care professionals performing formal family conversations and family members of patients admitted to the adult intensive care.

You may qualify if:

• Informed-consent is signed by all participating family members during the conversation.
• Informed-consent is signed by the ICU healthcare professionals.
• The patient of the family must be admitted to the adult ICU.
• All participating family members must be 18 years or older.
• The family conversation must be in Dutch.

You may not qualify if:

• Trained to interpret medical jargon and/or intensive care terminology specifically
• Difficulty reading and/or writing in the Dutch language

Sponsors & Collaborators

• Davy van de Sande: lead

Study Sites (2)

Erasmus University Medical Center

Rotterdam, South Holland, 3015GD, Netherlands

NOT YET RECRUITING

Erasmus University Medical Center

Rotterdam, 3015GD, Netherlands

RECRUITING

MeSH Terms

Conditions

Patient Satisfaction

Condition Hierarchy (Ancestors)

Treatment Adherence and Compliance; Health Behavior; Behavior

Study Officials

• Diederik Gommers, MD PhD

  Intensive Care Adults, Erasmus University Medical Center, Rotterdam, the Netherlands

  STUDY DIRECTOR

• Michel E. van Genderen, MD PhD

  Intensive Care Adults, Erasmus University Medical Center, Rotterdam, the Netherlands

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Davy van de Sande, PhD

CONTACT

010 7035142; d.sande@erasmusmc.nl

Michel E. van Genderen, MD PhD

CONTACT

010 7035142; m.vangenderen@erasmusmc.nl

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Coordinating Investigator

Study Record Dates

• First Submitted: December 2, 2024
• First Posted: January 3, 2025
• Study Start: January 14, 2025
• Primary Completion: August 1, 2025
• Study Completion: December 1, 2025
• Last Updated: February 25, 2025

Record last verified: 2024-11

Locations

NL (2)