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Due to the rapid growth of information available about individual patients,most physicians suffer from information overload when they review patientinformation in health information technology systems. In this manuscript, wepresent a novel hybrid dynamic and multi-collaborative filtering method toimprove information retrieval from electronic health records. This methodrecommends relevant information from electronic health records for physiciansduring patient visits. It models information search dynamics using a Markovmodel. It also leverages the key idea of collaborative filtering, originatingfrom Recommender Systems, to prioritize information based on varioussimilarities among physicians, patients and information items. We tested thisnew method using real electronic health record data from the Indiana Networkfor Patient Care. Our experimental results demonstrated that for 46.7% oftesting cases, this new method is able to correctly prioritize relevantinformation among top-5 recommendations that physicians are truly interestedin.

Improving information retrieval from electronic health records using dynamic and multi-collaborative filtering