TABLE 3.
Selected models proposed to address NBS expansion*.
| Type of Model | Description | References |
|---|---|---|
| Decision analytic model | A framework for compiling clinical and economic evidence in a systematic fashion, determining your product’s value, and communicating that value to decision makers. | Grosse et al. (2016); Prosser et al. (2013), Prosser et al. (2018) www.treeage.com |
| Markov Model | A mathematical model using the probabilities of different health states and the rates of transitions among them to recognize patterns, make predictions and to apply the statistics of sequential data. | Chan et al. (2011) www.treeage.com |
| Discrete Event Simulation Model | A method of simulating the behavior and performance of a real-life process, facility, or system. | Salleh et al. (2017) www.mathworks.com |
| Microsimulation model | A method of using individual-based state-transition models to reflect individual clinical pathways, incorporate the impact of history on future events, and capture the variation in patients’ characteristics at baseline. | Verkleij et al. (2021) www.treeage.com |
| Agent-based model | A computational model for simulating the actions and interactions of autonomous agents in order to understand the behavior of a system and what governs its outcomes. | Tracy et al. (2018) www.anylogic.com |
| System dynamic models | A computer-aided approach for strategy and policy design, which can portray processes of accumulation and feedback and that may be tested systematically to find effective policies for overcoming policy resistance. | Yu et al. (2019) https://systemdynamics.org |
| System thinking models | A way of approaching problems that asks how various elements within a system, (which could be an ecosystem, an organization, or something more dispersed such as a supply chain) can influence one another. | Carey et al. (2015) www.vensim.com |