Ambient AI Documentation in Oncology Consultations
Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorNational Cancer Center Affiliate of Vilnius University Hospital Santaros Klinikos
About this trial
This study tests whether an artificial intelligence (AI) system can help doctors write medical notes during cancer consultations.
After a cancer patient is seen by a multidisciplinary team (a group of specialists who decide on the best treatment), they have a consultation with their oncologist to discuss the treatment plan. During this consultation, doctors must write detailed medical notes, which takes significant time and effort.
In this study, an ambient AI system called VOCALI is used during oncology consultations at the National Cancer Center in Vilnius, Lithuania. Before the consultation begins, the doctor loads relevant pseudonymized clinical data from the electronic health record (such as diagnosis and treatment plan) into the system. During the consultation, VOCALI records the conversation (with the patient's consent) and combines it with the loaded clinical data to automatically generate a draft medical note in Lithuanian. Patients may ask the doctor to stop the recording at any time. The doctor then reviews the draft, makes any necessary corrections, and approves the final document. The AI does not make any medical decisions - the doctor is always responsible for the final note.
What the study measures:
The study has three main goals:
* To assess the quality of the AI-generated notes, rated by two independent reviewers using the PDQI-10, a standardized documentation quality instrument translated into Lithuanian using forward-backward translation * To measure the time doctors spend reviewing and approving the AI-generated draft * To monitor safety - whether any AI errors could affect patient care
The study also collects information on doctor workload, ease of use of the system, and patient satisfaction with the consultation.
Who can participate:
Adult patients (age 18 or older) attending a primary oncology consultation at the National Cancer Center in Vilnius, Lithuania, after a multidisciplinary team decision, who speak Lithuanian and provide written consent.
Study details:
250 patients will be enrolled over 12 months. Each participant attends one consultation and completes a short satisfaction questionnaire (about 5 minutes). No additional visits are required. There is no comparator group - all participants receive the AI-assisted documentation.
This is the first study to evaluate ambient AI documentation in the Lithuanian language and in the Lithuanian oncology setting.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Age 18 years or older at the time of signing the informed consent form
Primary oncologist consultation at the National Cancer Center following a multidisciplinary team (MDT) decision, with diagnosis and treatment plan established at the MDT meeting
MDT protocol available in the electronic health record (EHR)
Signed informed consent form, including consent to audio recording of the consultation
Disqualifiers
Absence of MDT protocol in the EHR
Diagnosis or treatment plan not yet established
MDT recommended additional diagnostic workup (treatment plan not yet defined)
Palliative care consultation (not active oncological treatment planning)
Trial population
Adult oncology patients attending a primary oncologist consultation at the National Cancer Center (Vilnius, Lithuania) following a multidisciplinary team (MDT) decision, with diagnosis and treatment plan established.
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Ambient AI documentation system
DeviceAn ambient artificial intelligence documentation system that records the consultation audio, integrates relevant pseudonymized clinical data from the electronic health record (EHR), generates a speech transcript, and produces a draft clinical note (E025 form) for physician review and approval. The system does not make autonomous clinical decisions. The physician reviews, edits if necessary, and approves all AI-generated content before it is saved to the EHR.
Treatment groups
250 Participants
are divided into 1 treatment groupGroup A: Oncology patients undergoing AI-assisted consultation1 intervention
Trial outcomes
Primary outcomes
1
Documentation Quality - AI-Generated Clinical Documentation Quality (PDQI-10)
Mean score assessed by two independent raters using the Physician Documentation Quality Instrument (PDQI-10), covering 10 domains (accuracy, completeness, usefulness, organization, clarity, conciseness, synthesis, consistency, data accuracy, and bias) on a 1-5 Likert scale.
Time frame
Per consultation, throughout the enrollment period (up to 12 months)2
Documentation Efficiency - Documentation Completion Time
Time (in minutes) from opening the AI-generated draft to final approval in the electronic health record (EHR), automatically recorded by the system.
Time frame
Per consultation, throughout the enrollment period (up to 12 months)3
Safety - AI System Incident Rate
Frequency of AI documentation incidents classified by a 5-level severity scale (1 = insignificant, 2 = minor, 3 = moderate, 4 = major, 5 = critical). Incidents reported by physicians within 3 working days. Critical incident (level 5) rate reported with 95% confidence interval using the Clopper-Pearson method.
Time frame
Per consultation, throughout the enrollment period (up to 12 months)Secondary outcomes
1
Physician Subjective Workload (NASA-TLX)
Physician-reported workload assessed using the NASA Task Load Index (NASA-TLX), covering 6 dimensions (mental demand, physical demand, temporal demand, performance, effort, frustration). Change from baseline (T0) to end of enrollment (T2) analyzed by paired t-test or Wilcoxon signed-rank test.
Time frame
Baseline (T0), 1 month (T1), and end of enrollment period (T2, up to 12 months)2
System Usability (SUS)
Physician-rated system usability assessed using the System Usability Scale (SUS), a 10-item questionnaire scored 0-100.
Time frame
End of enrollment period (T2, up to 12 months)3
AI Draft Editing Extent
Proportion of characters modified between the AI-generated draft and the final approved document, expressed as percentage. Automatically calculated per consultation.
Time frame
Per consultation, throughout the enrollment period (up to 12 months)4
Patient Satisfaction with Consultation (PSQ-18)
Patient-reported satisfaction assessed using the Patient Satisfaction Questionnaire (PSQ-18), an 18-item instrument. Results reported as subscale means.
Time frame
After each consultation, throughout the enrollment period (up to 12 months)Sponsors and contacts
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Source ClinicalTrials.gov
This trial is not recruiting at the moment. You can still explore other options: