CLINICAL KNOWLEDGE EXTRACTION, PROVIDER-GUIDED EDUCATIONAL MATERIAL AND TOP OF MIND CONCEPTS FOR PATIENT

摘要

A computerized Medical Information Navigation Engine ("MINE") extracts clinical knowledge, by identifying coded elements with reimbursement potential contributing to payoff based on clinical history, and subtracting coded elements documented in an encounter from the coded elements, based on business logic. The MINE sorts the remaining coded elements in accordance to at least one optimization criteria to payoff based on clinical history. Additionally, a medical processor computes concept associations by mining aggregated data from patient documents thereby reducing risk of PHI exposure. The processor identifies clinically relevant terms in patient documents, compute associations between pairs of clinically relevant terms using co¬ occurrences, and filter out random associations. A knowledge provider receives user query concepts, retrieves patient concepts, and extracts relevant apixions from an association matrix. The knowledge provider intersects relevant apixions with patient concepts, ranks and provides the results to the user.