An ontology-driven framework to support the dynamic formation of an interdisciplinary healthcare team

Teamwork has become a modus operandi in healthcare and delivery of patient care by an interdisciplinary healthcare team (IHT) is now a prevailing modality of care. We argue that a formal and automated support framework is needed for an IHT to properly leverage information technology resources. Such a framework should allow for patient preferences and expand a representation of a clinical workflow with a formal model of dynamic formation of a team, especially with regards to team leader- and membership, and the assignment of tasks to team members. Our goal was to develop such a support framework, present its prototype software implementation and verify the implementation using a proof-of-concept use case. Specifically, we focused on clinical workflows for in-patient tertiary care and on patient preferences with regards to selecting team members and team leaders.

Drawing on the research on clinical teamwork we defined the conceptual foundations for the proposed framework. Then, we designed its architecture and used ontology-driven design and first-order logic with associated reasoning methods to create and operationalize architectural elements. Finally, we incorporated existing solutions for business workflow modeling and execution as a backend for implementing the proposed framework.

We developed a Team and Workflow Management Framework (TWMF) with semantic components that allow for formalizing and operationalizing team formation in in-patient tertiary care setting and support provider-related patient preferences. We also created a prototype software implementation of TWMF using the IBM Business Process Manager platform. This implementation was evaluated in several simulated patient scenarios.

TWMF integrates existing workflow technologies and extends them with the capabilities to support dynamic formation of an IHT. Results of this research can be used to support real-time execution of clinical workflows, or to simulate their execution in order to assess the impact of various conditions (e.g., patterns of work shifts, staffing) on IHT operations.