Ignite Creation Date:
2024-10-26 @ 3:36 PM
Last Modification Date:
2024-10-26 @ 3:36 PM
Study NCT ID:
NCT06525181
Status:
RECRUITING
Last Update Posted:
None
First Post:
2024-07-18
Brief Title:
AI as an Aid for Weekly Symptom Intake in Radiotherapy
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Evaluation of AI-Enhanced Symptom Summarization in Weekly Radiotherapy Consultations A Comparative Study
Status:
RECRUITING
Status Verified Date:
2024-10
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
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
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
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None