System dynamics modelling for health systems strengthening: Applications before and during the COVID-19 pandemic in Thailand
System dynamics (SD) modelling employs systems thinking to understand complex systems’ behaviors over time. SD is among the most popular modelling methods in health policy and healthcare research. But unlike agent-based models that aim to capture micro-level system behaviors such as human decision-making and heterogeneous interactions between individuals, SD models address macro-level system behaviors such as changes or movement of resources in complex systems over time.
Using differential equations to model changing variables over time while allowing for feedback and various interactions and delays, SD models also address the issues of simultaneity or the mutual causation of systems behaviors. The method allows for the model breadth to explore long-term effects of strategic changes in our complex health systems.
The George Institute for Global Health India is pleased to invite you to a webinar on “System dynamics modelling for health systems strengthening: Applications before and during the COVID-19 pandemic in Thailand”
Mark your calendars for 12th November 2021 | 13:30 PM IST
- Introducing the concept of systems thinking in the context of health systems strengthening
- Clarifying how 'systems dynamics modeling’ can be used as an applied system thinking methodology in health policy process
- Presenting an example of health policy and systems research using SD methodology in context of COVID – 19.
- Expanding the scope of SYSTAC – A global systems thinking accelerator launched by the Alliance for Health Policy and Systems Research
- Borwornsom Leerapan - Faculty of Medicine Ramathibodi Hospital, Mahidol University
- Dr. Sohana Shafique - Deputy Project Coordinator, Urban Health, icddr,b, Bangladesh Moderator
- Dr. Devaki Nambair – Program Head – Health Systems and Equity, The George Institute for Global Health
- Mr. Siddharth Srivastava - Research Assistant, The George Institute for Global Health
Use and impact of SD in the contexts of Thailand’ UHC and the COVID-19 pandemic
In the context of the COVID-19 pandemic, SD can be used for epidemiological modelling of the COVID-19 pandemic. In addition, the massive demands for COVID-19 vaccination by both vulnerable and general populations as well as rapid adoption of digital health solutions in care delivery models can also be modelled. This has implications for the demands and supply of the health workforce, both in the short and long term. Hence, updated policy options of workforce planning in new care delivery models can be simulated to keep the modelling relevant to the current policy process.
Take-aways the webinar will offer to the audience
- Synthesis of comprehensive policy options can potentially address the barriers of health systems strengthening, the root causes of increased demands for hospital care and a constant shortage of healthcare providers, and such an understanding can advance Universal Health Coverage (UHC)
- By group model building with policymakers and stakeholders and testing such policy options by simulation modelling, researchers can help not only the strategic planning health workforce at the national level but also the planning and evaluation of the ongoing UHC reforms
- Systems modelling process is important for informing policymakers and stakeholders about what data in health information systems is crucial to the strengthening of UHC governance - particularly regarding managing the health workforce and health systems performance
- During the COVID-19 pandemic, the existing care delivery systems can be disrupted, so updated policy options of workforce planning and the impacts of new care delivery systems can be modelled
- The iterative nature of data collection and data analysis of SD modelling could be important for the UHC policy process, not only in Thailand but also in other LMICs too