AI-based Informational Assistant for Automated Point-of-care Documentation and Protocol Retrieval

NCT07493616 | Not Yet Recruiting

• 1 other identifier: 15243
• Study Type: observational
• Target: 25
• Locations: 0 countries
• Sites: N/A

Brief 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. 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

Outcome Measures

Primary Outcomes (1)

• 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.

  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

  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

  Before integration of the AI-based informational assistant and 12-weeks after integration

• Perceived usefulness, clarity, and trustworthiness

  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)

  During the 12-weeks utilization of the AI-based informational assistant.

• Technical output quality

  Before integration of the AI-based informational assistant and during the 12-weeks utilization.

Eligibility Criteria

• Sex: all
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

ICU physicians (nurse practicioners, residents, and staff intensivists) working at the Adult ICU of Erasmus MC.

You may qualify if:

• ICU physician (nurse practicioner, resident, or staff intensivist) at the Erasmus MC.
• Signed informed-consent for study participation.

You may not qualify if:

• \- Physicians not expected to work on the ICU during the study period will not be approached.

Sponsors & Collaborators

• Willemijn Berkhout: lead

Study Design

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

Study Record Dates

• First Submitted: March 18, 2026
• First Posted: March 25, 2026
• Study Start (Estimated): July 1, 2026
• Primary Completion (Estimated): October 1, 2026
• Study Completion (Estimated): December 1, 2026
• Last Updated: March 25, 2026

Record last verified: 2026-03