Health Analytics as a Service with Artemis Cloud: Service Availability^.

Area of Science:

• Biomedical Engineering
• Health Informatics
• Data Science

Background:

• Critical care units generate vast amounts of high-speed physiological data.
• Existing approaches for analyzing this Big Data are often not systemic or reliable for clinical decision support.

Purpose of the Study:

• To present a Big Data analytics-based Health Analytics as-a-Service model.
• To evaluate the deployment and availability of this model in real-world clinical settings.

Main Methods:

• Instantiation of a Health Analytics as-a-Service model named Artemis Cloud.
• Deployment of two Artemis Cloud instances to support neonatal intensive care units (NICUs).
• Evaluation of the availability results from the deployed instances.

Main Results:

• Successful deployment of two Artemis Cloud instances in two NICUs in Ontario, Canada.
• Demonstrated availability of the Health Analytics as-a-Service model for supporting clinical decision-making.

Conclusions:

• A Big Data analytics-based Health Analytics as-a-Service model can be effectively implemented in critical care settings.
• The deployed model shows promise for improving clinical decision support through the analysis of high-speed physiological data.