Cognitive Computing for Electronic Medical Records

The explosive growth of data has led to a situation where the human brain is overloaded with more information than it can process. It is particularly dire in healthcare where critical information may be buried in the mountains of data in the Electronic Medical Record systems (EMR systems) and healthcare workers struggle to make sense of this information to provide the best care for their patients. Cognitive computing, exemplified by Watson, offers the promise of transforming EMR systems from mere data storage to intelligent systems that help physicians in providing improved patient care. When seeing a patient, a physician needs to quickly grasp the summary of the patient’s medical history from the EMR to prepare for the visit and to put the patient’s complaints in context. During the visit, there may be a need to supplement, confirm, and investigate the information that the patient provides with information from the EMR. These information needs can be fulfilled by a cognitive system using advanced analytics on the patient record data. Some of the ways this can happen are a problem-oriented summary of a patient record, precisely answering natural language questions about the patient record content, automatically identifying urgent abnormalities, and by providing precise causes for such abnormalities. In this cognitive computing view, an EMR is an active entity that leverages the vast knowledge of the medical sciences, drug information, and medical ontologies in the context of the patient medical records to meet the information needs of the healthcare provider.