Chapter 8 - Assured Decision and Meta-Governance for Mobile Medical Support Systems

Abstract

The use of mobile decision support systems in clinical practice is becoming more prevalent. That is not to say that such systems are replacing clinician-based diagnosis or analysis but rather these systems are used as part of the process. Nevertheless, it is necessary that decision support in a medical context be conducted in a provably assured and consistent manner: these systems ought to be treated, from a software engineering perspective, as (safety-) critical systems. Thus, it is necessary to imbue the mobile decision support process with effective governance, accountability, and robustness. This work is seeking to imbue clinical decision support with such features as a consequence of a more formal approach to their definition, design, testing, and implementation. Thus, governance of both the process and the system itself is handled by software. Accountability is maintained through a formal design audit process, whereas robustness of decision analysis and system operation is autonomously handled by the system itself. This is extremely important in mobile decision support use by clinicians and in increasing confidence in the use of such systems. It can be noted, from the foregoing discussion, that there are (at least) two separate concerns to be handled, namely, concerns of system operation governance, accountability, and robustness and concerns of decision process governance, accountability, and robustness. Traditionally such concerns would be divided and handled separately in the software development process. In this case, however, there are evidently many cross-cutting concerns, such as decision outcomes, for example, that do not fit neatly into one or the other concern. In addition, in a mobile setting, the role of a decision support system is not limited to presenting data analysis; it may also present relevant documentation and online information or provide alerts using the Internet. Current attempts at facilitating such systems necessarily focus on a complete design time solution for all events; this is unfeasible for the required complexity of the system. Accordingly the work, reported here, proposes, analyses, and assesses a formal representation and reasoning technique for mobile medical decision support systems that handles the separate and cross-cutting concerns of the systems by using a formal calculus of first order logic. Thus, a complete design time solution is not required; rather, true system values are used to evaluate and validate any current run time state encountered. The work is evaluated using a breast cancer prognosis system previously developed in partnership with health care professionals.