Joint search in text and concept spaces for EMR-based cohort identification

In this paper, we present a novel electronic health records (EMR) retrieval system that helps to reduce manual in work in cohort identification. Our system effectively uses medical domain knowledge to enhance retrieval performance. In particular, our system first maps raw text of EMR and EMR queries from the text space to concept unique identifiers in the medical concept space, and then searches in the two spaces independently, and finally weights and combines search results adaptively based on several heuristics. Our cross-validation results show that the proposed adaptive weighting mechanism is significantly better than the fixed-weighting mechanism, and also that the joint search is more effective than text-based search or concept-based search. In addition, we introduce an effective approach for external expansion in the concept space.