Patient, Pelvic Cancer, Radiotherapy Side Effect
Conditions
Keywords
Artificial Intelligence, Patient-Reported Outcome
Brief summary
The study investigates the use of artificial intelligence (AI) and large language models (LLMs) to enhance the efficiency and accuracy of weekly treatment consultations (OTVs) in radiotherapy. It hypothesizes that an AI-enabled symptom summary tool will match traditional medical review methods in accuracy while saving time. The study includes patients undergoing pelvic radiotherapy and excludes those with pelvic reirradiation or who have undergone surgery. Patients will receive both standard and AI-assisted weekly consultations, with AI summaries generated using the OpenAI GPT-4 API. Blinded oncologists will compare the accuracy and quality of the AI-generated and doctor-generated summaries, while patients and doctors will rate these summaries. The primary objective is to evaluate the accuracy and time efficiency of AI-assisted symptom summaries compared to traditional methods.
Detailed description
This clinical trial is a comparative study designed to evaluate the accuracy and time efficiency of an AI-enabled symptom summary tool in comparison to traditional medical review methods in patients undergoing radiotherapy in the pelvic region. Hypothesis: The AI-enabled symptom summary tool is hypothesized to be non-inferior in accuracy to traditional medical review methods and to save time in the process. Primary Outcome: Accuracy of Documentation: The quality of the documentation will be evaluated using the Physician Documentation Quality Instrument-9 (PDQI-9), a validated questionnaire that assesses nine key elements of documentation quality: completeness, correctness, consistency, comprehensibility, relevance, organization, conciseness, formatting, and overall impression. Blinded specialist doctors will use the PDQI-9 to evaluate both AI-generated and traditional summaries, assigning scores from 1 to 10. Secondary Outcomes: Time Efficiency: The time required to complete the AI-enabled and traditional consultations will be recorded and compared. Physician Satisfaction: A custom-designed satisfaction questionnaire will be administered to the physicians participating in the study. This questionnaire will include Likert-scale questions to rate various aspects of satisfaction, including ease of use, time efficiency, accuracy perception, and overall satisfaction. Patient Satisfaction: A custom-designed satisfaction questionnaire will be administered to the patients participating in the study. This questionnaire will include Likert-scale questions to rate various aspects of satisfaction, including clarity and understanding, perceived accuracy, engagement and interaction, and overall satisfaction. Methodology: Patient Selection: Patients meeting the inclusion criteria will be selected for participation. Exclusion criteria will be applied to eliminate cases of pelvic reirradiation or prior operations in the pelvic region. Consultation Process: Patients will undergo a standard weekly consultation with a doctor. In the same week, each patient will also have a separate consultation with a different doctor. During this second consultation, a symptom questionnaire will be completed under medical supervision. The resulting summary from this questionnaire will be generated using the OpenAI GPT-4 API.
Interventions
OTHERGenerative Artificial Intelligence
Gen AI assisted symptom intake summarization
OTHERStandard weekly symptom intake
Standard weekly symptom intake performed by a physician
Sponsors
National Cancer Institute, Brazil
jaide
Study design
Allocation
NON_RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
All patients undergoing radiotherapy in the pelvic region.
Exclusion criteria
Cases of pelvic reirradiation or operated cases.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| The Physician Documentation Quality Instrument-9 (PDQI-9) | 2 months | The Physician Documentation Quality Instrument-9 (PDQI-9) will be used to evaluate the quality of the documentation. The PDQI-9 is a validated questionnaire that assesses nine key elements of documentation quality: completeness, correctness, consistency, comprehensibility, relevance, organization, conciseness, formatting, and overall impression. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Time tracking | 2 months | The total time spent with each patient and on documentation will be recorded for both the standard and AI-enabled consultations. |
| Accuracy | 2 months | A team of blinded specialist oncologists will compare the summaries generated by both methods. Accuracy ratings will be assigned based on tabulated data from the completed questionnaires. Patients will be shown both the AI-generated summary and the doctor's summary and will be asked to rate their accuracy on a scale from 1 to 10. |
| Physician satisfaction | 2 months | Physician Satisfaction Assessment: Physician satisfaction with the AI-enabled symptom summary tool compared to traditional documentation methods will be evaluated. Measurement Tool: A custom-designed satisfaction questionnaire will be administered to the physicians participating in the study. This questionnaire will include Likert-scale questions to rate various aspects of satisfaction, including: Ease of Use: Physicians will rate how easy they find the AI-enabled tool to use compared to traditional methods. Time Efficiency: Physicians will assess whether the AI tool saves time during patient consultations and documentation. Overall Satisfaction: An overall satisfaction score will be provided, reflecting the physician's general experience with the AI tool. |
| Patient satisfaction | 2 months | Patient Satisfaction Assessment: Patient satisfaction with the AI-enabled symptom summary tool compared to traditional documentation methods will be evaluated as a secondary outcome of this trial. Measurement Tool: A custom-designed satisfaction questionnaire will be administered to the patients participating in the study. This questionnaire will include Likert-scale questions to rate various aspects of satisfaction, including: Clarity and Understanding: Patients will rate how clear and understandable they find the AI-generated summaries compared to traditional documentation. Engagement and Interaction: Patients will evaluate their engagement and interaction experience during consultations using the AI tool versus traditional methods. Satisfaction: An overall satisfaction score will be provided, reflecting the patient's general experience with the AI tool. |
Countries
Brazil
Contacts
Primary ContactRachele Grazziotin, MD
Outcome results
None listed