Evaluating the Use of Artificial Intelligence to Improve Family Conversations for Intensive Care Patients and Their Families
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorDavy van de Sande
About this trial
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.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
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.
Disqualifiers
Trained to interpret medical jargon and/or intensive care terminology specifically
Difficulty reading and/or writing in the Dutch language
Trial population
Intensive care professionals performing formal family conversations and family members of patients admitted to the adult intensive care.
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Not listed
Trial groups
No trial groups listed
Trial outcomes
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.
Time frame
Within 30 days after the family conversation.Secondary outcomes
1
Time spent on documentation by ICU clinicians
The time clinicians spend on post-conversation documentation will be measured for both traditional and ambient listening methods. This outcome aims to quantify the efficiency of the ambient listening technology in reducing administrative burden.
Time frame
Within one day after the family conversation.2
Family satisfaction
Family members' feedback on their satisfaction with the intensive care unit (ICU) communication process. Satisfaction will be measured using a structured questionnaire administered after reviewing a simplified ambient-generated note. The survey includes 16 questions: 5 about demographics (age, education, occupation, and reading skills); 3 adapted from the validated Family Satisfaction with the ICU-24 survey (score range: 1-5, higher scores indicate greater satisfaction) to assess clarity, completeness, and overall satisfaction; and 10 evaluating the summary's readability and utility at a B1 language proficiency level.
Time frame
Within 30 days after the family conversation.Sponsors and contacts
Click on the lead sponsor to view all of their trials.
Davy van de Sande
Lead sponsor
Erasmus Medical Center
Sponsor institution
Source ClinicalTrials.gov