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Updated: Jun 14, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Use of clinical alerting to improve the collection of clinical research data
Krystl Haerian1, Jon McKeeby, Gary Dipatrizio
1Laboratory for Informatics Development, National Institutes of Health Clinical Center, Bethesda, Maryland, USA.
Abstract:
Data errors in electronic health records have been shown to have the potential to adversely impact the conclusions drawn from clinical research. We prospectively studied the efficacy of a new alert to infer errors in previously stored data and to decrease the frequency of data entry errors, in an attempt to improve the quality of data for clinical trials. For the purpose of this study, we monitored data entry errors in height or weight measurements. We predetermined the criteria for probable error as a ten percent variance from a patient's reference value. The care provider entering a value satisfying our error criteria received a disruptive pop-up alert message. The study revealed a significant decrease in the frequency of data errors stored in the EHR, from 2.4% before the alert to 0.9% after the alert. These findings have implications for the development of clinical research trial data collection support tools.
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