QuickSilver clinical tracker - a risk-management approach
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Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Daniel T Rosenthal1, Henry Chueh
1Laboratory of Computer Science, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Abstract:
While many guidelines strive to automate the high-granular clinical thought process, the resulting risk stratification is often a low-granular management class (i.e. low, medium or high risk). Furthermore, the "low hanging fruit" of guidelines is not in decision support, rather in the subsequent action tracking. Therefore, we believe that only a small amount of data is required to produce significant reminders. In our approach, the clinician risk-stratifies the patient and enters the guideline at the management level. We do not attempt to replicate the clinical thought process; rather we ask the question, "Now that you have decided, how can we help track your decisions?" A risk-management approach encapsulates salient guideline features and provides a framework for basic decision support and data tracking.
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