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Updated: Jun 2, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Meaningful use in practice using patient-specific risk in an electronic health record for shared decision making
J B Jones1, Nirav R Shah, Christa A Bruce
1Center for Health Research, Geisinger Clinic, 100 N. Academy Avenue, Danville, PA 17822, USA. jbjones@geisinger.edu
Abstract:
Quantitative risk (QR) formulas have been developed for multiple conditions but are not routinely used in clinical practice. Tests were made of the feasibility of an automated clinical care process for using QR in routine primary care. Several modifications were made to the Framingham Risk Score (FRS) and it was applied to routine care in three areas: (1) for risk-stratification, (2) patient education about care options, and (3) guidance on optimizing choice of care options. Evidence-based methods were used to convert the smoking status variable from a binary- to a continuous-scale format and to add variables for alcohol use and HbA1c. An automated protocol tested in 2008-2010 was successful for all three applications. At-risk patients (defined according to criteria from the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure [JNC]-7 or the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults [adult treatment panel/ATP-III]) were automatically identified during routine encounters. Patient-reported data were obtained (n = 1826) by touchscreen questionnaire and automatically used with electronic health record (EHR) data to calculate risks on 1068 patients who had complete data. Patients were risk-stratified. Higher-risk patients viewed an interactive web-based tool and chose options to modify risk factors. Feasibility was successful for use of the FRS in the interactive web tool.
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