Current cancer screening recommendations often apply coarse age cutoffs for screening requirements without regard to predicted life expectancy. Using these cutoffs, healthier older patients may be under-screened, and sicker younger patients may be screened too often. Mortality risk classification using EHR data could be used to tailor screening reminders to physicians in ways that better align screening recommendations with patients who are more likely to live long enough to benefit from early detection. We have evaluated the performance of an existing prognostic index for 4-year mortality using data readily available in the electronic health record (EHR), and investigated the effect of the index in retrospective cohorts of adults age 65 and older undergoing screening colonoscopy. Risk scores in this adaptation of a four-year prognostic index were found to be associated with actual death rates and consistent with mortality rates from a national sample. Our results demonstrate that data extracted from electronic health records can be used to classify mortality risk. With improvements, including extension to a 5-year mortality model with inclusion of additional variables and extension of variable definitions, informatics methods to implement mortality models may prove to be clinically useful in tailoring screening guidelines.