Evaluating a Colonoscopy Surveillance Recommendations Algorithm
This study is looking at a new computer-based tool called a colonoscopy surveillance recommendations algorithm. The goal is to see if using this algorithm helps doctors make more accurate recommendations for when patients should have their next colonoscopy, compared to how they currently do it. The study also wants to find out if the algorithm saves doctors time and if that time saving has a financial benefit. Doctors, including residents and fellows, who work at NYU Langone Health and Bellevue can participate. The study will measure how accurate the recommendations are and how long it takes to make them on the first day of the study.
- Study design
- This is an observational study, meaning researchers will watch and record information without giving any specific treatments. It plans to include 100 participants.
- What's involved
- Not specified in the trial record.
- Compensation
- Not stated in the trial record.
- Follow-up
- The primary measurements for accuracy and time taken are recorded on Day 0.
AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.
Evaluating the Effectiveness of a Colonoscopy Surveillance Recommendations Algorithm in Clinical Practice
At a glance
Conditions
Where it's being run
1 sites across 1 statesStudy leadership
- Renee Williams, MD · PRINCIPAL_INVESTIGATOR · NYU Langone Health
Who to contact
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Do you actually qualify for this trial?
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Inclusion
Exclusion
What this trial measures
- Accuracy of surveillance timing recommendationsDay 0
- Time taken to answer each scenarioDay 0