Semantic based model of Conceptual Work Products for formal verification of complex interactive systems

TL;DR

This paper presents a semantic-based formal verification approach for complex conceptual work products in clinical workflows, using UML diagrams, ontologies, and SPIN logic to ensure correctness and solvability.

Contribution

It introduces a novel method combining UML, ontologies, and SPIN for verifying the correctness of abstract work product specifications in healthcare systems.

Findings

Successfully modeled MS case management specifications

Proved consistency of UML diagram interactions using SPIN

Demonstrated the approach's applicability to complex clinical workflows

Abstract

Many clinical workflows depend on interactive computer systems for highly technical, conceptual work products, such as diagnoses, treatment plans, care coordination, and case management. We describe an automatic logic reasoner to verify objective specifications for these highly technical, but abstract, work products that are essential to care. The conceptual work products specifications serve as a fundamental output requirement, which must be clearly stated, correct and solvable. There is strategic importance for such specifications because, in turn, they enable system model checking to verify that machine functions taken with user procedures are actually able to achieve these abstract products. We chose case management of Multiple Sclerosis (MS) outpatients as our use case for its challenging complexity. As a first step, we illustrate how graphical class and state diagrams from UML can be developed and critiqued with subject matter experts to serve as specifications of the conceptual work product of case management. A key feature is that the specification must be declarative and thus independent of any process or technology. Our Work Domain Ontology with tools from Semantic Web is needed to translate UML class and state diagrams for verification of solvability with automatic reasoning. The solvable model will then be ready for subsequent use with model checking on the system of human procedures and machine functions. We used the expressive rule language SPARQL Inferencing Notation (SPIN) to develop formal representations of the UML class diagram, the state machine, and their interactions. Using SPIN, we proved the consistency of the interactions of static and dynamic concepts. We discussed how the new SPIN rule engine could be incorporated in the Object Management Group (OMG) Ontology Definition Metamodel (ODM)