Completion of structured patient descriptions by semantic mining.

This paper presents experiments in automatic Information Extraction of medication events, diagnoses, and laboratory tests form hospital patient records, in order to increase the completeness of the description of the episode of care. Each patient record in our hospital information system contains structured data and text descriptions, including full discharge letters. From these letters, we extract automatically information about the medication just before and in the time of hospitalization, especially for the drugs prescribed to the patient, but not delivered by the hospital pharmacy; we also extract values of lab tests not performed and not registered in our laboratory as well as all non-encoded diagnoses described only in the free text of discharge letters. Thus we increase the availability of suitable and accurate information about the hospital stay and the outpatient segment of care before the hospitalization. Information Extraction also helps to understand the clinical and organizational decisions concerning the patient without increasing the complexity of the structured health record.