(CDSS). As medicine is becoming increasingly complex, the ability of clinicians to process all the data and apply it at the point of care becomes difficult, for example: One in eight older Americans suffer from Alzheimer’s disease, yet an April 2012 study in the Journal of Neuropa- thology and Experimental Neurology found that between 17 and 30 percent of those diagnosed with Alzheimer’s disease had been misdiagnosed and had other conditions. Clinicians capture the data using speech, and the cloud- based medical intelligence analyzes the patient data in the context of extensive knowledge bases offering relevant insights and supporting information to the clinicians and the patient.
4. Medical intelligence from the narrative note Today, the vast majority of clinical information is gen- erated through clinical narrative dictation. Information is processed either by background speech recognition or by a front-end speech-recognition input device. CLU technology allows applications to take the meaning of patient-centric, data-infused clinical information capture and utilization to a whole new level. Extracting data directly from the narrative dictation turns regular text-based information into clinically
actionable data that can drive clinical workflow. As clinicians use intelligent speech interactions, their medical notes and clinical decision making are captured and understood, offer- ing the potential for real-time clinical support and automated workflow based on the patient’s clinical data.
5. Analytics, alerts and tracking from narrative dictation
Medical intelligence derived from the narrative dictation
using CLU can then be sent to the clinical data repository and linked to multiple other sources of data (e.g., laboratory, pa- thology, imaging and other diagnostic services). When linked to appropriate sources, clinicians and healthcare facilities obtain a complete picture of individual patient data and ag- gregated population and disease trends, realizing the potential of “big data.” With the narrative decoded and an analytics tool, clinicians now have a complete picture of their patients. Today, speech recognition offers efficiencies, but recent technological advancements will expand the horizon of medi- cal opportunity. Speech recognition will change the human/ computer interface by reducing the administrative burden, decreasing costs and, most importantly, increasing the ef- ficiency and safety of healthcare delivery.