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Related Experiment Video

Updated: May 19, 2026

Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis
07:51

Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis

Published on: September 26, 2018

Towards human-centric visual access control for clinical data management.

Sascha Fahl1, Marian Harbach, Matthew Smith

  • 1Leibniz University Hannover, Distributed Computing & Security Group, Germany. fahl@dcsec.uni-hannover.de

Studies in Health Technology and Informatics
|August 10, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a human-centric visual access control (AC) system for managing clinical data. It enhances usability and security by involving both medical staff and patients in configuring access rules.

Related Experiment Videos

Last Updated: May 19, 2026

Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis
07:51

Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis

Published on: September 26, 2018

Area of Science:

  • Health Informatics
  • Information Security
  • Human-Computer Interaction

Background:

  • Traditional access control (AC) systems lack usability and flexibility for non-technical users in healthcare.
  • Distributed clinical data management requires robust security while adhering to privacy regulations.

Purpose of the Study:

  • To develop a human-centric, visual, and context-aware AC system for distributed clinical data.
  • To improve usability, information security, and patient interaction in health information systems.

Main Methods:

  • Proposed a novel human-centric visual AC model.
  • Integrated patient involvement into the AC process.
  • Focused on dynamic AC configuration at the end-user level.

Main Results:

  • The proposed system addresses the need for timesaving and reliable AC rule configuration by medical staff.
  • It enhances security by incorporating patient interaction into the AC policy creation.
  • The model aims for widespread acceptance among non-tech-savvy users in medical settings.

Conclusions:

  • The human-centric visual AC model offers a more usable and flexible solution for managing clinical data.
  • It balances strong security requirements with patient privacy and end-user needs.
  • This approach supports dynamic AC configuration in distributed medical institutions.