Moretto, Nicole and Comans, Tracy A. and Chang, Angela T. and O'Leary, Shaun P. and Osborne, Sonya and Carter, Hannah E. and Smith, David and Cavanagh, Tania and Blond, Dean and Raymer, Maree (2019) Implementation of simulation modelling to improve service planning in specialist orthopaedic and neurosurgical outpatient services. Implementation Science, 14 (1). pp. 1-11.
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Moretta et al 2019_simulation modelling.pdf Available under License Creative Commons Attribution 4.0. Download (660kB) | Preview |
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.
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| Item Type: | Article (Commonwealth Reporting Category C) |
|---|---|
| Refereed: | Yes |
| Item Status: | Live Archive |
| Faculty/School / Institute/Centre: | Current - Faculty of Health, Engineering and Sciences - School of Nursing and Midwifery (1 Jan 2015 -) |
| Faculty/School / Institute/Centre: | Current - Faculty of Health, Engineering and Sciences - School of Nursing and Midwifery (1 Jan 2015 -) |
| Date Deposited: | 22 Jan 2020 01:08 |
| Last Modified: | 07 Feb 2020 01:41 |
| Uncontrolled Keywords: | Implementation; Discrete event simulation; Orthopaedics; Neurosurgery; Physiotherapy; Hospital; Costs; Economic evaluation |
| Fields of Research : | 11 Medical and Health Sciences > 1117 Public Health and Health Services > 111709 Health Care Administration |
| Socio-Economic Objective: | E Expanding Knowledge > 97 Expanding Knowledge > 970111 Expanding Knowledge in the Medical and Health Sciences |
| Funding Details: | |
| Identification Number or DOI: | 10.1186/s13012-019-0923-1 |
| URI: | http://eprints.usq.edu.au/id/eprint/37337 |
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