Diabetes in pregnancy is increasing, and this is challenging the capacity of diabetes services.
The application of systems science and simulation modelling to the decision-making process is an innovative area with great potential value for those responsible for allocating resources.
Simulation modelling to support decision making in gestational diabetes careProject title
What is the issue?
This PhD project tackled the growing problem of diabetes in pregnancy against the backdrop of increasing interest in systems science methods to examine complex problems.
Health systems are under continual pressure to provide accessible and effective health services with limited budgets. In this context, decisions regarding the best investment of health funds need to be well informed, reviewed regularly and aimed at achieving the greatest health gain for the investment.
The development and testing of methods and tools to inform decision-making processes is critical. The application of systems science and simulation modelling to the decision-making process is an innovative area with great potential value for those responsible for allocating resources.
Diabetes in pregnancy includes diabetes that develops, or is first diagnosed, during pregnancy and pre-existing type 1 and type 2 diabetes. Babies born to women who have diabetes during pregnancy are at short-term risk of high birthweight, birth complications and hypoglycaemia and at long-term risk of sustained impaired glucose tolerance. Women who have gestational diabetes are at higher risk of developing type 2 diabetes later in life.
Diabetes in pregnancy is increasing, and this is challenging the capacity of diabetes services. The increase is associated with an increase in risk factors such as overweight and obesity, older maternal age and increasing numbers of women from high-risk groups. New guidelines introduced in 2015 recommend that women who are high risk of developing diabetes in pregnancy should be screened in the first trimester. Consequently, these women are diagnosed with diabetes earlier in their pregnancy and need services for longer. Also, women are more frequently presenting with a combination of risk factors resulting in more complex care needs.
This all means that diabetes in pregnancy is having a significant impact on health service demand and resources, and the need to “do things differently”.
How did the project address the issue?
This project applied systems science and simulation modelling to the problem of diabetes in pregnancy in the ACT as a case study.
Systems science is emerging as an effective way to examine both complex health problems and their context. It can be used to synthesise evidence, examine and compare the potential outcomes of interventions and guide the best use of limited resources through methods such as simulation modelling.
The project used case study methodology to illustrate the strengths and weaknesses of simulation modelling as a tool to inform policy and program decision making.
Simulation modelling is being used to explore strategies for gestational diabetes diagnosis, early intervention and management. The modelling includes interaction between risk factors, the short-and long-term outcomes for mother and baby, and potential modes and timing of intervention.
Involving key decision-makers and experts in the model development and validation process increases the validity of the model for the local context. The model is therefore more likely to be useful to inform decisions about priority interventions and policies.
Relevance for practice
The project evaluated the effectiveness of participatory dynamic simulation modelling to inform program and policy decision-making. It produced a simulation model for diabetes in pregnancy that will inform investments for intervention in diabetes in pregnancy. The model considers the short-, intermediate- and long-term implications of the increasing prevalence of risk factors for diabetes in pregnancy.
What were the expected outcomes?
- Produced a model that will be a functioning simulation tool to explore possible scenarios and the likely impact over time of each scenario on health outcomes for the mother and baby as well as service impacts for the health system
- Engaged with the stakeholder group to use the model to inform decision-making
- Evaluated the use of participatory dynamic simulation modelling as a decision-support tool.
News and media
Other news and media
- Freebairn L and Kelly P. Harnessing new technologies to inform health decision making: Dynamic simulation modelling as a decision support tool for diabetes in pregnancy. ACT Population Health Bulletin. Volume 6, Issue 2, May 2017, p, 31-32.
- Freebairn L. Simulation Modelling to Inform Decision Making for Diabetes in Pregnancy in the ACT. International Congress on Modelling and Simulation, Hobart, December, 2017.
- Freebairn L. Simulation modelling as a tool for knowledge translation in health policy settings: a case study protocol. School of Medicine, University of Notre Dame, Research Conference 2016. 23 March 2016. Sydney.
- Freebairn L. Simulation modelling: A systems approach to optimising the use of evidence to inform decision making in gestational diabetes care MODISM – 21st International Congress on Modelling and Simulation. 29 November 2015. Gold Coast.
- Freebairn L. Gestational diabetes through a systems science lens. Centre for Health Stewardship Research Group. Australian National University. 19 November 2015. Canberra.