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Colorectal Cancer Simplified
Carol Burke, MD
Contact Innovation Manager
What is it? What does it do?
We have designed and tested an algorithm that can be implemented across various platforms including the web or as a native smartphone app that will assist clinicians in recommending guideline-concordant colorectal cancer (CRC) screening and surveillance intervals. Through a series of questions that can be posed to the patient and/or gleaned from the patient’s medical record, a clinician will be able to convey and act on evidence-based recommendations for CRC. As CRC recommendations apply to the general population, this solution is targeted for clinicians including primary care physicians, gastroenterologist, NPs, PAs, as well as medical and surgical trainees in both the inpatient and outpatient setting.
Why is it Better?
Currently clinicians have to rely on the published recommendations from numerous societies such as the American College of Gastroenterology, US Preventive Service Task Force as well as the US Multi Society Task Force to make evidence-based recommendations for CRC screening and surveillance. Our solution incorporates the recommendations from each of those and provides a validated
‘go-to’ resource for clinicians.
As more evidence emerges, additional variables have been incorporated that impact the guidelines, dramatically increasing the number of permutations possible to reach varying interval recommendations. We anticipate guidelines to continue to increase in complexity making recall and application very difficult. Our solution is simple and reliable.
Polyps come in all shapes, sizes and types and interval recommendations rely heavily on this. Navigating published evidence tables to account for each polyp is tedious, time consuming and can lead to errors. By navigating the clinician through a series of carefully designed questions, we make the process easier, faster and less-error prone for the clinician.
The solution is platform agnostic and portable.
What is its current status?
Further validating the algorithm by comparing interval recommendations to actual patient encounters with gastroenterologists at the Cleveland Clinic.
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