Foundations for safety-critical on-demand medical systems
In current medical practice, therapy is delivered in critical care environments (e.g., the ICU) by clinicians who manually coordinate sets of medical devices: The clinicians will monitor patient vital signs and then reconfigure devices (e.g., infusion pumps) as is needed. Unfortunately, the current state of practice is both burdensome on clinicians and error prone. Recently, clinicians have been speculating whether medical devices supporting "plug & play interoperability" would make it easier to automate current medical workflows and thereby reduce medical errors, reduce costs, and reduce the burden on overworked clinicians. This type of plug & play interoperability would allow clinicians to attach devices to a local network and then run software applications to create a new medical system "on-demand" which automates clinical workflows by automatically coordinating those devices via the network. Plug & play devices would let the clinicians build new medical systems compositionally. Unfortunately, safety is not considered a compositional property in general. For example, two independently "safe" devices may interact in unsafe ways. Indeed, even the definition of "safe" may differ between two device types. In this dissertation we propose a framework and define some conditions that permit reasoning about the safety of plug & play medical systems. The framework includes a logical formalism that permits formal reasoning about the safety of many device combinations at once, as well as a platform that actively prevents unintended timing interactions between devices or applications via a shared resource such as a network or CPU. We describe the various pieces of the framework, report some experimental results, and show how the pieces work together to enable the safety assessment of plug & play medical systems via a two case-studies.
Health care management|Computer science
King, Andrew L, "Foundations for safety-critical on-demand medical systems" (2016). Dissertations available from ProQuest. AAI10189922.