Clinical validity of alerts generated by the CareEngine Claims-Driven Decision Support Engine
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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
Henry G Wei1, Stephen Rosenberg, Tatiana Shnaiden
1Weill-Cornell Medical College, ActiveHealth Management, New York, NY, USA.
Abstract:
Clinical decision support based on administrative data is an important "real-world" challenge. At an academic medical center, we reviewed medical charts to assess the accuracy of 182 clinical alerts generated from administrative claims, pharmacy data, and lab results by a computerized clinical decision support (CDS) system. Overall accuracy was 82%. The primary factor affecting alert accuracy was availability of complete data. Claims-driven CDS may be sufficiently accurate to be a valuable adjunct to quality improvement.
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