Medical Device Interoperability With Provable Safety Properties

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Degree type
Doctor of Philosophy (PhD)
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Computer and Information Science
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formal methods
interoperability
patient safety
Computer Sciences
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2019-08-27T20:19:00-07:00
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Abstract

Applications that can communicate with and control multiple medical devices have the potential to radically improve patient safety and the effectiveness of medical treatment. Medical device interoperability requires devices to have an open, standards-based interface that allows communication with any other device that implements the same interface. This will enable applications and functionality that can improve patient safety and outcomes. To build interoperable systems, we need to match up the capabilities of the medical devices with the needs of the application. An application that requires heart rate as an input and provides a control signal to an infusion pump requires a source of heart rate and a pump that will accept the control signal. We present means for devices to describe their capabilities and a methodology for automatically checking an application’s device requirements against the device capabilities. If such applications are going to be used for patient care, there needs to be convincing proof of their safety. The safety of a medical device is closely tied to its intended use and use environment. Medical device manufacturers create a hazard analysis of their device, where they explore the hazards associated with its intended use. We describe hazard analysis for interoperable devices and how to create system safety properties from these hazard analyses. The use environment of the application includes the application, connected devices, patient, and clinical workflow. The patient model is specific to each application and represents the patient’s response to treatment. We introduce Clinical Application Modeling Language (CAML), based on Extended Finite State Machines, and use model checking to test safety properties from the hazard analysis against the parallel composition of the application, patient model, clinical workflow, and the device models of connected devices.

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Insup Lee
Date of degree
2019-01-01
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