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Previously submitted to: JMIR Medical Education (no longer under consideration since May 07, 2018)

Date Submitted: Jan 15, 2018
Open Peer Review Period: Jan 19, 2018 - May 7, 2018
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Clinical Cybersecurity Training Through Novel High Fidelity Simulations

Dameff C, Selzer J, Fisher J, Killeen J, Tully J

Clinical Cybersecurity Training Through Novel High Fidelity Simulations

The Journal of Emergency Medicine

DOI: 10.1016/j.jemermed.2018.10.029

NOTE: This is an unreviewed Preprint

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Clinical Cybersecurity Training Through Novel High Fidelity Simulations

  • Christian Dameff; 
  • Jordan Selzer; 
  • Jonathan Fisher; 
  • James Killeen; 
  • Jeffrey Tully

Background:

Cybersecurity risks in healthcare systems have traditionally been measured in data breaches of protected health information but compromised medical devices and critical medical infrastructure raises questions about the risks of disrupted patient care. The increasing prevalence of these connected medical devices and systems implies that these risks are growing.

Objective:

This paper details the development and execution of three novel high fidelity clinical simulations designed to teach clinicians to recognize, treat, and prevent patient harm from vulnerable medical devices.

Methods:

Clinical simulations were developed which incorporated patient care scenarios with hacked medical devices based on previously researched security vulnerabilities.

Results:

Clinician participants universally failed to recognize the etiology of their patient’s pathology as being the result of a compromised device.

Conclusions:

Simulation can be a useful tool in educating clinicians in this new, critically important patient safety space.


 Citation

Please cite as:

Dameff C, Selzer J, Fisher J, Killeen J, Tully J

Clinical Cybersecurity Training Through Novel High Fidelity Simulations

JMIR Preprints. 15/01/2018:9853

DOI: 10.2196/preprints.9853

URL: https://preprints.jmir.org/preprint/9853

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