A participative and facilitative conceptual modelling framework for discrete event simulation studies in healthcare

Existing approaches to conceptual modelling (CM) in discrete-event simulation (DES) do not formally support the participation of a group of stakeholders. Simulation in healthcare can benefit from stakeholder participation as it makes possible to share multiple views and tacit knowledge from different parts of the system. We put forward a framework tailored to healthcare that supports the interaction of simulation modellers with a group of stakeholders to arrive at a common conceptual model. The framework incorporates two facilitated workshops. It consists of a package including: three key stages and sub-stages; activities and guidance; tools and prescribed outputs. The CM framework is tested in a real case study of an obesity system. The benefits of using this framework in healthcare studies and more widely in simulation are discussed. The paper also considers how the framework meets the conceptual modeling requirements

Modeling patient waiting times for an obesity service: a computer simulation study

Objective: To investigate the impact of alternative resource configurations on patient waiting times for obesity centers experiencing high referral rates. Study design: We developed a computer simulation model of an obesity service in an Academic Health Science Centre (AHSC) providing lifestyle, pharmacotherapy and surgery treatment options for the UK’s National Health Service (NHS). Data collection: Model parameters on existing and projected demand and supply of treatments offered at an obesity service were collected. Principal findings: Simulation results showed that the introduction of an additional surgeon improves patient waiting times for surgery. The addition of one physician reduces the waiting list for pharmacotherapy clinics, but without an additional surgeon, the surgical part of the pathway experiences long waiting times. Demand for the obesity treatments can be met by adding new resources, but also by managing demand for services and reducing referrals into the service. A phased implementation of resources was also modeled to guide decisions. Conclusions: Simulation models can be used to identify resource configurations required to meet maximum waiting time targets from referral to treatment such as the UK’s NHS 18 week target. This is achieved by considering a number of future scenarios