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One of the challenges that healthcare systems face today in many developed countries is insufficient capacity. Issues such as increased demand, rising costs, limited capacity, limits in technology and informatics as well as lack in industrial engineering tools and methods are key drivers to hospital capacity problems (Williams, 2006). Capacity problems create delays in healthcare delivery, and according to Hall et al. (2006), successful work in reducing delays depends on collaboration between administrative and clinical processes, ability to see healthcare as a system and find bottlenecks and system failures in patient flows.
Simulation modeling, along with other operations research methods have been applied in healthcare management since the 1950s (Royston, 2009) and can help dealing with complex and dynamic nature of healthcare capacity management (Green, 2004). During the last few decades there has been a growth of interest in this area resulting in a significant increase of published studies (Fone et al., 2003; Brailsford et al., 2009). Despite the vast amount of literature describing applications of simulation in different healthcare settings there is little evidence on how the results of simulations are actually implemented (Fone et al., 2003) and what exactly the contribution of simulation to healthcare improvement is. Several authors (Brailsford, 2005; Eldabi, 2009; Harper & Pitt, 2004; Roberts, 2011) have proposed possible causes for this lack of reported implementations. One of the most recent studies on simulation implementation issues by van Lent, VanBerkel & van Harten (2012) concludes that more research into the perceived success factors is necessary.
The aim of this paper is therefore to identify factors that contribute to successful implementation of simulation results in healthcare. The research method used for data collection and analysis, apart from simulation modeling itself, has been a longitudinal case study research. The method was chosen primarily because of the unique opportunity to follow a successful simulation project for a prolonged period of time and also because this method allows to study the implementation phenomenon within its organizational context. This approach also allows researchers to gain additional, deeper insight into a problem situation when compared to survey research. Data was collected through interviews and on-site observations and then analyzed using a framework of implementation facilitators and obstacles identified in the earlier research on simulation implementation.
Specifically, the paper describes a case study in operating room planning at a Swedish regional hospital where simulation has been used in a project consisting of several different sub-projects over a time period of more than six years. The description is focused on the aspects related to implementation and does not include a complete account of model details and results in each stage. The simulation model of the operating department, its development, validation and experiments are described in more detail in a paper by Steins, Persson & Holmer (2010).
Given a set of potential obstacles for implementation which have been summarized and reported elsewhere on the one hand and the successful simulation project on other hand, it is possible to identify which strategies have been used to neutralize the obstacles. Looking for the obstacles and finding strategies to neutralize them, used with awareness or without, provides a list of examples of what can be done to ensure a successful implementation of simulation results in healthcare.