AI-driven pathology laboratory utilization management via data- and knowledge-based analytics

Abstract

Inappropriate pathology test orders are an economic burden on laboratories and compromise patient safety. We pursue a laboratory utilization management strategy that involves raising awareness amongst physicians regarding their test ordering behaviour. We are employing an AI-driven approach for laboratory utilization management, whereby we apply both machine learning and semantic reasoning methods to analyze pathology laboratory data. We are analyzing over 6-years of primary care physician’s pathology test order ‘big’ data. Our analysis generates physician order profiles, based on their case-mix and orders-sets, to inform physicians about their laboratory utilization. We developed an AI-driven platform—i.e. Pathology Laboratory Utilization Scorecards (PLUS) that offers an interactive means for physicians to self-examine their test ordering pattern. PLUS aims to optimize the utilization of the Central Zone pathology laboratory of the Nova Scotia Health Authority.