Stockholm County, Sweden was in the process of building a new, highly specialized hospital. The Health Administration of the county questioned whether they would get an acceptable level of care production with the current investments and reasoning concerning various operational and strategic issues. To find the answers, they used simulation modeling in AnyLogic.
An initiative by the Department of Mechanical and Industrial Engineering at the University of Toronto, the Centre for Research in Healthcare Engineering (CRHE), was in response to the immediate and compelling desire for efficiency and quality improvements in the Canadian healthcare system.
The County of Stockholm (Sweden), like any country or region, experiences a continuous need to handle the healthcare necessities of various patient groups. Each group can be seen as a subpopulation, with its own distinctive traits, characteristics, and challenges. The discussed simulation project focused on the dialysis patients, a group who needs to visit caregiving facilities frequently.
Despite extensive emergency coverage, some rural areas still don’t have access to all the necessary resources for good public health. Engineers from Lean Business Services, a government-owned company in Saudi Arabia and the leader in developing innovations for the health sector, used AnyLogic simulation modeling to improve the process of emergency patient transportation.
In order to make better decisions to deal with COVID-19, the Saskatchewan Health Authority decided to integrate a trust model, in real time, into the decision-making approach within their health policy. The model would be able to look at the whole system and not just individual parts.
When the planning for surgery is not effective and efficient, patients suffer, face stress and anxiety, and may even become inoperable if the wait is too long. It is necessary to transform this process which will enable patients to have their surgery on time and surgical service teams will be able to achieve maximum capacity.
Diseases that spread very rapidly such as acute myeloid leukemia (AML) are very hard to treat and can progress extremely quickly, often resulting in death. Simulating this disease progression and patient treatment could help to understand the behavior of it better, leading to improved outcomes for patients.
Hong Kong has very unique conditions and attempting to understand the spread of COVID-19 and then how to combat it was very challenging. Using agent-based modeling and publicly available data, researchers tried to understand this spread and identify vulnerable areas and at-risk populations, as well as evaluating government interventions.