Healthcare systems modeling and simulation has a broad application around different disciplines such as clinical simulation, operational simulation, managerial simulation, and educational simulation. However, the domain of healthcare is characterized by a high degree of complexity and a diversity of facets, and modelers are often confronted with the challenge of formulating a simulation model that captures this complexity in a systematic and manageable manner. This chapter reviews frequently used M&S-related concepts to address the problem, concluding clinical and epidemiologic simulations are predominant in the literature.

Chapter Contents:

• 1.1 Review of healthcare systems simulation
• 1.1.1 Levels of care
• 1.1.2 Contextual challenges
• 1.1.2.1 Health demand and supply
• 1.1.2.2 Tensions on health systems
• 1.1.3 Care objectives
• 1.1.4 Observed abstractions
• 1.1.5 Measured/computed outcomes
• 1.1.6 Modeling approaches
• 1.1.7 Simulation techniques
• 1.1.8 Browsing the web of contributions
• 1.2 Lessons learnt in a nutshell
• 1.3 Ontology for healthcare systems simulation
• 1.3.1 Ontology in M&S
• 1.3.2 Ontology in healthcare M&S
• 1.3.3 System entity structure ontological framework
• 1.3.4 Ontology for healthcare systems simulation
• 1.3.4.1 Health consumption
• 1.3.4.2 Health production
• 1.3.4.3 Health coordination
• 1.4 Model base for healthcare systems M&S
• 1.5 Summary
• References

Inspec keywords: digital simulation; health care; medical administrative data processing; medical computing; epidemics

Other keywords: clinical simulation; epidemiologic simulation; healthcare systems modeling; healthcare systems simulation; complexity

Subjects: Biology and medical computing; Medical administration