Advocating that healthcare should be considered as a complex adaptive system (CAS), Kuziemsky indicates that an acknowledged shortcoming in much of the existing research is that it is descriptive in nature without guidance on how to study healthcare delivery as a CAS. Kuziemsky offers an informal system model that is intended to establish understanding of how the system works with respect to the relevant concepts and the relationships. He illustrates how various and costly unintended consequences have emerged from steps taken to reform healthcare systems due to the complexity of the pertinent healthcare processes. Before proceeding, we briefly review some relevant background on CAS. We then consider fundamental requirements for modelling and simulation of CAS in the context of health care.

Chapter Contents:

• 11.1 Background on complex adaptive systems and systems of systems
• 11.2 Fundamental requirements for M&S of complex adaptive systems and SoS
• 11.2.1 Deal with system-of-systems (SoS) M&S nature
• 11.2.2 Develop an organizational ontology for M&S-based applications
• 11.2.3 Enable the ontology to support combinatorial model compositions
• 11.2.4 Include the major facets at the top level to ensure macro behavior
• 11.2.5 Include a large spectrum of models for combinatorial composition
• 11.2.6 Instrument the system to support continuous on-going high-quality data
• 11.2.7 Include pervasive incremental automated learning
• 11.3 Summary
• References
• Appendix C.1 Case study of machine learning based assignment of pathways in care coordination

Inspec keywords: adaptive systems; health care; large-scale systems

Other keywords: complex adaptive systems; multiperspective modeling; healthcare delivery

Subjects: Systems theory applications in biology and medicine