ColonFlag uses existing medical data to provide new insights on patients’ risk of harboring colorectal cancer– insights that can potentially save lives. ColonFlag is used as a decision support case-finding tool which can help optimize the use of colonoscopy resources and allow for improved patient care.
A data-driven decision support software tool, ColonFlag identifies individuals who are at high risk of having colorectal cancer, early on, often months before clinical signs are present, using CBC data, age and sex.
ColonFlag effortlessly identifies individuals at high risk for CRC using existing data, including non-screened individuals within its assessment scope and requiring no patient involvement.
Implemented at Maccabi Healthcare, an HMO covering 2 million lives, ColonFlag analyzes existing medical data and identifies a subgroup in the general population who has a high probability of harbouring colorectal cancer or precancerous lesions. Requiring no patient involvement, the system automatically alerts Maccabi GPs who then decide on further evaluation.
ColonFlag was developed using data of over 605,000 patients of Maccabi Healthcare Services (MHS) aged 40+. The model was further validated using de-identified data of 25,613 individuals aged 40+ (5,061 CRC cases), from The Health Improvement Network (THIN), a UK primary care database.