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Evaluation method

System Dynamics

System Dynamics is a simulation approach for strategy and policy design devised by Professor J.W. Forrester of the Massachusetts Institute of Technology in the late 1950s. In System Dynamics, changes in a social system are modelled qualitatively by causal loop diagrams (Figure 1) and quantitatively by stock and flow diagrams (Figure 2). Non-linear changes, feedbacks, and temporal delays can be incorporated into simulation models with appropriate stocks and flows. The System Dynamics approach has been widely applied to simulation analyses in the field of public health with dedicated software.

因果ループ図

Figure 1.An example of a causal loop diagram.

The reinforcing loop shows that increased births lead to increased population,
and an increase the population leads to further increased births. The balancing loop shows that increased deaths lead to decreased population, and anincrease in the population in turn lead to increased deaths.


ストックフロー図

Figure 2. An example of a stock and flow diagram.

Population is a stock variable that can be increased or decreased over time. The stock of population is accumulated or depleted by births (inflows) and deaths (outflows). The birth rate and the death rate are constant.

 

Markov model

A Markov model is a stochastic method for simulating transitions of cohorts or individuals among multiple health states over time to calculate costs and effectiveness of interventions (Figure 3). Probabilities of transitions between health states are based on existing data such as cohort studies, publicly available databases, and published papers. Dedicated software is available for Markov model simulation.

markov_img

Figure 3. A Markov model diagram of patients with a disease A

References
  • The Japan Pharmaceutical Manufacturers Association Data Science Expert Committee 2014 Task Force 3. Current status and methodology of cost-effectiveness evaluation for data scientists, Ver 2.0. 2016
    (Accessed on January 19, 2022)
  • Ikeda S. Health economic evaluation and modelling analyses. Operations research as a management of science 2003;48(5):353-8.
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