Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

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6.9K Views

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07:31 min

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May 15th, 2020

DOI :

10.3791/60794-v

May 15th, 2020

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Tao Wang¹, Dominic Oliver², Yamiko Msosa¹, Craig Colling³, Giulia Spada², Łukasz Roguski⁴, Amos Folarin¹, Robert Stewart³^,⁵, Angus Roberts¹^,³, Richard J. B. Dobson¹^,³^,⁴^,⁶, Paolo Fusar-Poli²^,³^,⁷^,⁸

¹Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, ²Early Psychosis: Interventions and Clinical-detection (EPIC) lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, ³National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, ⁴Institute of Health Informatics, University College London, ⁵Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, ⁶Health Data Research UK London, University College London, ⁷OASIS service, South London and Maudsley National Health Service (NHS) Foundation Trust, ⁸Department of Brain and Behavioral Sciences, University of Pavia

Podsumowanie

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Psychosis Detection

Risk Alerting System

Electronic Health Records

CogStack Implementation

Real time Monitoring

Psychosis Prevention

Individualized Risk Calculator

Precision Medicine

Clinical Care

Mental Health Conditions

ETL Processes

Kibana Interface

Data Ingestion

Risk Prediction Modeling

Stakeholder Engagement

Rozdziały w tym wideo

0:04

Introduction

1:58

Data Ingestion

3:18

Risk Calculation

4:12

Data Visualization

4:44

Risk Alerting

5:24

Results: Representative Risk Result Validation, Visualization, and Alerting

6:26

Conclusion

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