AI-based Informational Assistant for Automated Point-of-care Documentation and Protocol Retrieval
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Artificial Intelligence, Usability. Basic parameters: No limits · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Center list to be confirmed — check the primary protocol.
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Evaluation of an AI-based Informational Assistant for Automated Point-of-care Documentation and Protocol Retrieval in the Intensive Care Unit
Overview
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.
Primary outcome measures
- Implementation outcomes acceptability, appropriateness, and feasibility [Time frame: Before integration of the AI-based informational assistant and 4-, 8-, and 12-weeks after integration.]
Secondary outcome measures (6)
- 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.]
Eligibility criteria
Inclusion criteria
- ICU physician (nurse practicioner, resident, or staff intensivist) at the Erasmus MC.
- Signed informed-consent for study participation.
Exclusion criteria
\- Physicians not expected to work on the ICU during the study period will not be approached.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Study design
- Observational model
- Cohort
Study locations
Center list to be confirmed — check the primary protocol.
Identifiers
NCT: NCT07493616 · 15243