Intensive Care MedicineNCT06756542
Evaluating the Use of Artificial Intelligence to Improve Family Conversations for Intensive Care Patients and Their Families
An observational study of Intensive Care Medicine and Critical Care, run by Davy van de Sande at 2 sites in Netherlands.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Intensive Care Medicine, Critical Care
- How many people
- 40 participants
- Where
- 2 sitesNetherlands
- Study dates
- 14 Jan 2025to Dec 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Intensive care professionals performing formal family conversations and family members of patients admitted to the adult intensive care.
Who may be able to join
- 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.
Who cannot join
- Trained to interpret medical jargon and/or intensive care terminology specifically
- Difficulty reading and/or writing in the Dutch language
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
Netherlands2 sites, 2 recruiting
- Not yet recruiting
Erasmus University Medical Center
Rotterdam, South Holland, 3015GD
Davy van de Sande, PhD, 010 7035142 ext. 31, d.sande@erasmusmc.nl
- Recruiting
Erasmus University Medical Center
Rotterdam, 3015GD
Michel E. van Genderen, MD PhD, +31 0107039883, m.vangenderen@erasmusmc.nl
About this study
Official title: Utilizing Large Language Models to Augment Family Conversations in the Intensive Care Unit
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
- Medical subject headings
- Patient Satisfaction
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: Within 30 days after the family conversation.
Secondary outcomes (2)
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.
Measured: Within one day after the family conversation.
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.
Measured: Within 30 days after the family conversation.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Jan 2025
- Study start14 Jan 2025
- Primary completionAug 2025 (estimated)
- Study completionDec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Intensive Care MedicineStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 40 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Davy van de Sande
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Davy van de Sande, Erasmus Medical Center
- Investigators
- Diederik Gommers, MD PhD, Study director, Intensive Care Adults, Erasmus University Medical Center, Rotterdam, the NetherlandsMichel E. van Genderen, MD PhD, Principal investigator, Intensive Care Adults, Erasmus University Medical Center, Rotterdam, the Netherlands
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06756542
- Sponsor's protocol ID
- MEC-2024-0733
- Status last verified
- Nov 2024
- First submitted
- 2 Dec 2024
- Last updated
- 25 Feb 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 25 Feb 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Utilizing Large Language Models to Augment Family Conversations in the Intensive Care Unit
- ClinicalTrials.gov ID
- NCT06756542
- Acronym / sponsor ID
- MEC-2024-0733
- Conditions
- Intensive Care Medicine, Critical Care
- Keywords
- intensive care, artificial intelligence, large language models, administration reduction, patient satisfaction
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 40 participants (estimated)
- Lead sponsor
- Davy van de SandeUniversity, hospital or other
- Study start
- 14 Jan 2025 (actual)
- Primary completion
- Aug 2025 (estimated)
- Study completion
- Dec 2025 (estimated)
- First posted
- 3 Jan 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Intensive care professionals performing formal family conversations and family members of patients admitted to the adult intensive care.
Key inclusion criteria (5 listed)
- 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.
Key exclusion criteria (2 listed)
- Trained to interpret medical jargon and/or intensive care terminology specifically
- Difficulty reading and/or writing in the Dutch language
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Documentation quality of family conversations
Time frame: Within 30 days after the family conversation.
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.
2 secondary outcomes
Time spent on documentation by ICU clinicians
Time frame: Within one day after the family conversation.
Family satisfaction
Time frame: Within 30 days after the family conversation.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 25 Feb 2025.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Diederik Gommers, MD PhD study director
Intensive Care Adults, Erasmus University Medical Center, Rotterdam, the Netherlands
Michel E. van Genderen, MD PhD principal investigator
Intensive Care Adults, Erasmus University Medical Center, Rotterdam, the Netherlands
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Intensive Care Medicine and Critical Care, run by Davy van de Sande at 2 sites in Netherlands.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 25 Feb 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Netherlands. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Davy van de Sande, PhD (010 7035142 ext. +31, d.sande@erasmusmc.nl), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Documentation quality of family conversations (time frame: Within 30 days after the family conversation.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 25 Feb 2025.