Artificial IntelligenceNCT07493616
AI-based Informational Assistant for Automated Point-of-care Documentation and Protocol Retrieval
An observational study of Artificial Intelligence and Usability, run by Willemijn Berkhout.
Trial summary
Clinical rounds in the intensive care unit (ICU) involve substantial manual documentation. Retrieving the correct protocol text and structuring notes at the bedside is time-consuming and may contribute to variation in documentation quality. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Artificial Intelligence, Usability
- How many people
- 25 participants
- Where
- No sites listed yet
- Study dates
- 1 Jul 2026to 1 Dec 2026
- 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 Any age
- All sexes
- Child, Adult, Older adult
Study population: ICU physicians (nurse practicioners, residents, and staff intensivists) working at the Adult ICU of Erasmus MC.
Who may be able to join
- ICU physician (nurse practicioner, resident, or staff intensivist) at the Erasmus MC.
- Signed informed-consent for study participation.
Who cannot join
- Physicians not expected to work on the ICU during the study period will not be approached.
About this study
Official title: Evaluation of an AI-based Informational Assistant for Automated Point-of-care Documentation and Protocol Retrieval in the Intensive Care Unit
Clinical rounds in the intensive care unit (ICU) involve substantial manual documentation. Retrieving the correct protocol text and structuring notes at the bedside is time-consuming and may contribute to variation in documentation quality. Modern artificial intelligence (AI) can help structure existing information and automate protocol look-ups within a restricted, manually selected document set.
The tool evaluated in this study acts as an AI-based informational assistant for clinicians. It (1) pre-populates a standardized physical-exam and daily-rounds format, (2) prepares a concise ICU course/overview using predefined formatting, and (3) retrieves relevant passages from protocols to enable rapid consistency checks by the clinician.
The AI-based informational assistant does not provide treatment recommendations or patient-specific advice; all outputs require clinician verification and clinical responsibility remains with the physician.
- Conditions
- Artificial Intelligence, Usability
What is being measured
The primary outcome is the main question the study is designed to answer.
Implementation outcomes acceptability, appropriateness, and feasibility
The mean scores and standard deviations of the 5-point Likert scale (1 = strongly disagree, 2 = disagree, 3 = undecided, 4 = agree, 5 = strongly agree) closed-ended questions of the survey on the physicians' perspectives will be calculated. Standardised questionnaires AIM, IAM and FIM are used.
Measured: Before integration of the AI-based informational assistant and 4-, 8-, and 12-weeks after integration.
Secondary outcomes (6)
Perceived time saved when using the AI-based informational assistant during ICU rounds
The mean scores and standard deviations of the 5-point Likert scale closed-ended questions of the survey on the physicians' perceptions on retrieval speed.
Measured: 12-weeks after integration of the AI-based informational assistant .
Task-based efficiency, including time to (i) produce a structured rounds note and (ii) retrieve relevant protocol text
Timed predefined ICU round documentation tasks with and without AI-based informational assistant. Time difference will be calculated.
Measured: Before integration of the AI-based informational assistant and 12-weeks after integration
Perceived usefulness, clarity, and trustworthiness
The mean scores and standard deviations of the 5-point Likert scale (1 = strongly disagree, 2 = disagree, 3 = undecided, 4 = agree, 5 = strongly agree) closed-ended questions of the survey on the physicians' perspectives will be calculated.
Measured: Before integration of the AI-based informational assistant and during the 12-weeks utilization.
Adoption and use, including frequency of use, retention over time, and interaction patterns (e.g., number/type of edits, use cases, feature use)
Adoption will be determined by frequency of use (interactions per participant per week) and retention (continued use over time), expressed as counts and proportions. Fidelity will be determined by the misusage per participant, reported as counts and proportions. Adoption and fidelity will be aggregated at both participant and cohort level. Interaction logs will be used to characterize use patterns, including number and type of edits, use cases and feature usage.
Measured: During the 12-weeks utilization of the AI-based informational assistant.
Technical output quality
Outputs is reviewed on accuracy, recall, precision, groundedness, contextual usefulness, and hallucination presence. Reported as counts and proportions.
Measured: Before integration of the AI-based informational assistant and during the 12-weeks utilization.
Trust in the system, perceived workload, and task satisfaction
The mean scores and standard deviations of the 5-point Likert scale (1 = strongly disagree, 2 = disagree, 3 = undecided, 4 = agree, 5 = strongly agree) closed-ended questions of the survey on the physicians' perspectives will be calculated. Standardised questionnaires S-TIAS and NASA-TLX are used.
Measured: 12-weeks after integration of the AI-based informational assistant.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted25 Mar 2026
- Study start1 Jul 2026 (estimated)
- Primary completion1 Oct 2026 (estimated)
- Study completion1 Dec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Artificial IntelligenceStudies 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
- 25 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Willemijn Berkhout
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Willemijn Berkhout, Erasmus Medical Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07493616
- Sponsor's protocol ID
- 15243
- Status last verified
- Mar 2026
- First submitted
- 18 Mar 2026
- Last updated
- 25 Mar 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 25 Mar 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation of an AI-based Informational Assistant for Automated Point-of-care Documentation and Protocol Retrieval in the Intensive Care Unit
- ClinicalTrials.gov ID
- NCT07493616
- Acronym / sponsor ID
- 15243
- Conditions
- Artificial Intelligence, Usability
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 25 participants (estimated)
- Lead sponsor
- Willemijn BerkhoutUniversity, hospital or other
- Study start
- 1 Jul 2026 (estimated)
- Primary completion
- 1 Oct 2026 (estimated)
- Study completion
- 1 Dec 2026 (estimated)
- First posted
- 25 Mar 2026 (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.
Clinical rounds in the intensive care unit (ICU) involve substantial manual documentation. Retrieving the correct protocol text and structuring notes at the bedside is time-consuming and may contribute to variation in documentation quality. Modern artificial intelligence (AI) can help structure existing information and automate protocol look-ups within a restricted, manually selected document set.
The tool evaluated in this study acts as an AI-based informational assistant for clinicians. It (1) pre-populates a standardized physical-exam and daily-rounds format, (2) prepares a concise ICU course/overview using predefined formatting, and (3) retrieves relevant passages from protocols to enable rapid consistency checks by the clinician.
The AI-based informational assistant does not provide treatment recommendations or patient-specific advice; all outputs require clinician verification and clinical responsibility remains with the physician.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Sex
- All
- Age groups
- Child, Adult, Older adult
- Study population
- ICU physicians (nurse practicioners, residents, and staff intensivists) working at the Adult ICU of Erasmus MC.
Key inclusion criteria (2 listed)
- ICU physician (nurse practicioner, resident, or staff intensivist) at the Erasmus MC.
- Signed informed-consent for study participation.
Key exclusion criteria (1 listed)
- Physicians not expected to work on the ICU during the study period will not be approached.
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
Implementation outcomes acceptability, appropriateness, and feasibility
Time frame: Before integration of the AI-based informational assistant and 4-, 8-, and 12-weeks after integration.
The mean scores and standard deviations of the 5-point Likert scale (1 = strongly disagree, 2 = disagree, 3 = undecided, 4 = agree, 5 = strongly agree) closed-ended questions of the survey on the physicians' perspectives will be calculated. Standardised questionnaires AIM, IAM and FIM are used.
6 secondary outcomes
Perceived time saved when using the AI-based informational assistant during ICU rounds
Time frame: 12-weeks after integration of the AI-based informational assistant .
Task-based efficiency, including time to (i) produce a structured rounds note and (ii) retrieve relevant protocol text
Time frame: Before integration of the AI-based informational assistant and 12-weeks after integration
Perceived usefulness, clarity, and trustworthiness
Time frame: Before integration of the AI-based informational assistant and during the 12-weeks utilization.
Adoption and use, including frequency of use, retention over time, and interaction patterns (e.g., number/type of edits, use cases, feature use)
Time frame: During the 12-weeks utilization of the AI-based informational assistant.
Technical output quality
Time frame: Before integration of the AI-based informational assistant and during the 12-weeks utilization.
Trust in the system, perceived workload, and task satisfaction
Time frame: 12-weeks after integration of the AI-based informational assistant.
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 Mar 2026.
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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.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
An observational study of Artificial Intelligence and Usability, run by Willemijn Berkhout.
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 2 inclusion and 1 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: opening soon, as of the sponsor's last update on 25 Mar 2026. Status can change between updates, so confirm with the study contact before making plans.
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?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Implementation outcomes acceptability, appropriateness, and feasibility (time frame: Before integration of the AI-based informational assistant and 4-, 8-, and 12-weeks after integration.). 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 Mar 2026.