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Related Experiment Video

Updated: May 24, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
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Supporting Risk Assessment Through a Visual, Browser-Based Tool.

Christopher Gundler1, Frank Ückert1

  • 1Institute for Applied Medical Informatics, University Medical Center Hamburg-Eppendorf.

Studies in Health Technology and Informatics
|May 23, 2026
PubMed
Summary
This summary is machine-generated.

A new browser-based tool enhances risk management in medical information systems. It visually models processes and assesses hazards, improving adherence to international data protection and risk standards.

Keywords:
collaborationdata protection impact assessmenthazard identificationmedical informaticsrisk assessment

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Last Updated: May 24, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

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

Published on: May 15, 2020

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

Area of Science:

  • Medical Informatics
  • Information Systems Security
  • Risk Management

Background:

  • Effective risk management in medical information systems requires adherence to international standards.
  • Current challenges include a lack of intuitive tools to bridge regulatory frameworks and daily practice.

Purpose of the Study:

  • To design, implement, and evaluate a browser-based tool for visual risk modeling and assessment in medical informatics.
  • To address the need for accessible tools connecting regulatory requirements with operational workflows.

Main Methods:

  • The study employed the Design Science Research framework across three phases: requirements/design, implementation, and evaluation.
  • A browser-based tool was developed enabling process modeling, hazard list management, and structured risk assessments.
  • Expert evaluation involved four medical informatics professionals assessing usability via the System Usability Scale.

Main Results:

  • The developed tool facilitates process modeling with simplified notation and structured risk assessments.
  • Expert evaluation yielded high usability ratings (83.75) on the System Usability Scale.
  • The tool effectively supports process-oriented risk assessment in medical informatics.

Conclusions:

  • Browser-based, interactive tools can significantly improve risk management in medical informatics.
  • The developed tool offers a systematic and collaborative approach to managing risks in healthcare information systems.
  • Enhanced usability and integration of standards are key for effective medical informatics risk management.