Implementation of simulation modelling to improve service planning in specialist orthopaedic and neurosurgical outpatien
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RESEARCH
Open Access
Implementation of simulation modelling to improve service planning in specialist orthopaedic and neurosurgical outpatient services Nicole Moretto1,2* , Tracy A. Comans1,2, Angela T. Chang2, Shaun P. O’Leary2,3, Sonya Osborne4,5, Hannah E. Carter5, David Smith6, Tania Cavanagh7, Dean Blond8 and Maree Raymer2
Abstract Background: Advanced physiotherapist-led services have been embedded in specialist orthopaedic and neurosurgical outpatient departments across Queensland, Australia, to ameliorate capacity constraints. Simulation modelling has been used to inform the optimal scale and professional mix of services required to match patient demand. The context and the value of simulation modelling in service planning remain unclear. We aimed to examine the adoption, context and costs of using simulation modelling recommendations to inform service planning. Methods: Using an implementation science approach, we undertook a prospective, qualitative evaluation to assess the use of discrete event simulation modelling recommendations for service re-design and to explore stakeholder perspectives about the role of simulation modelling in service planning. Five orthopaedic and neurosurgical services in Queensland, Australia, were selected to maximise variation in implementation effectiveness. We used the consolidated framework for implementation research (CFIR) to guide the facilitation and analysis of the stakeholder focus group discussions. We conducted a prospective costing analysis in each service to estimate the costs associated with using simulation modelling to inform service planning. Results: Four of the five services demonstrated adoption by inclusion of modelling recommendations into proposals for service re-design. Four CFIR constructs distinguished and two CFIR constructs did not distinguish between high versus mixed implementation effectiveness. We identified additional constructs that did not map onto CFIR. The mean cost of implementation was AU$34,553 per site (standard deviation = AU$737). Conclusions: To our knowledge, this is the first time the context of implementing simulation modelling recommendations in a health care setting, using a validated framework, has been examined. Our findings may provide valuable insights to increase the uptake of healthcare modelling recommendations in service planning. Keywords: Implementation, Discrete event simulation, Orthopaedics, Neurosurgery, Physiotherapy, Hospital, Costs, Economic evaluation
* Correspondence: [email protected] 1 Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Princess Alexandra Hospital campus, Woolloongabba, Queensland 4102, Australia 2 Metro North Hospital and Health Service, Royal Brisbane and Women’s Hospital, Butterfield Street, Herston, Queensland 4029, Australia Full list of author information is available at the end of the article © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creat
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