Improving patient waiting times: a simulation study of an obesity care service

Journal article


Tako, A., Kotiadis, K., Vasilakis, C., Miras, A. and Roux, C. 2014. Improving patient waiting times: a simulation study of an obesity care service. BMJ Quality & Safety. 23 (5), pp. 373-381. https://doi.org/10.1136/bmjqs-2013-002107
AuthorsTako, A., Kotiadis, K., Vasilakis, C., Miras, A. and Roux, C.
Abstract

Background Obesity care services are often faced with the need to adapt their resources to rising levels of demand. The main focus of thisstudy was to help prioritise planned investments in new capacity allowing the service to improve patient experience and meet future anticipated demand. Methods We developed computer models of patient flows in an obesity service in an Academic Health Science Centre that provides lifestyle, pharmacotherapy and surgery treatment options for the UK?s National Health Service. Using these models we experiment with different scenarios to investigate the likely impact of alternative resource configurations on patient waiting times. Results Simulation results show that the timing and combination of adding extra resources (eg, surgeons and physicians) to the service are important. For example, increasing the capacity of the pharmacotherapy clinics equivalent to adding one physician reduced the relevant waiting list size and waiting times, but it then led to increased waiting times for surgical patients. Better service levels were achieved when the service operates with the resource capacity of two physicians and three surgeons. The results obtained from this study had an impact on the planning and organisation of the obesity service. Conclusions Resource configuration combined with demand management (reduction in referral rates) along the care service can help improve patient waiting time targets for obesity services, such as the 18 week target of UK?s National Health Service. The use of simulation models can help stakeholders understand the interconnectedness of the multiple microsystems (eg, clinics) comprising a complex clinical service for the same patient population, therefore, making stakeholders aware of the likely impact of resourcing decisions on the different microsystems.

KeywordsSimulation
Year2014
JournalBMJ Quality & Safety
Journal citation23 (5), pp. 373-381
PublisherBMJ Publishing Group
ISSN2044-5415
Digital Object Identifier (DOI)https://doi.org/10.1136/bmjqs-2013-002107
Publication dates
PrintOct 2014
Online19 Sep 2013
Publication process dates
Deposited08 Dec 2016
Output statusPublished
Permalink -

https://repository.canterbury.ac.uk/item/87z98/improving-patient-waiting-times-a-simulation-study-of-an-obesity-care-service

  • 49
    total views
  • 0
    total downloads
  • 0
    views this month
  • 0
    downloads this month

Export as

Related outputs

Facilitated post-model coding in discrete event simulation (DES): a case study in healthcare
Kotiadis, K. and Tako, A. 2017. Facilitated post-model coding in discrete event simulation (DES): a case study in healthcare. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2017.10.047
Learning from discrete-event simulation: exploring the high involvement hypothesis
Monks, T., Robinson, S. and Kotiadis, K. 2014. Learning from discrete-event simulation: exploring the high involvement hypothesis. European Journal of Operational Research. 235 (1), pp. 195-205. https://doi.org/10.1016/j.ejor.2013.10.003
PartiSim: a framework for participative simulation modelling
Tako, A. and Kotiadis, K. 2015. PartiSim: a framework for participative simulation modelling. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2015.01.046
Can involving clients in simulation studies help them solve their future problems? A transfer of learning experiment
Monks, T., Robinson, S. and Kotiadis, K. 2015. Can involving clients in simulation studies help them solve their future problems? A transfer of learning experiment. European Journal of Operational Research. 249 (3), pp. 919-930. https://doi.org/10.1016/j.ejor.2015.08.037
A participative and facilitative conceptual modelling framework for discrete event simulation studies in healthcare
Kotiadis, K., Tako, A. and Vasilakis, C. 2014. A participative and facilitative conceptual modelling framework for discrete event simulation studies in healthcare. Journal of the Operation Research Society. 65 (2), pp. 197-213. https://doi.org/10.1057/jors.2012.176
Addressing the sample size problem in behavioural operational research: simulating the newsvendor problem
Robinson, S., Dimitriou, S. and Kotiadis, K. 2016. Addressing the sample size problem in behavioural operational research: simulating the newsvendor problem. Journal of the Operational Research Society. https://doi.org/10.1057/s41274-016-0016-3
Combining problem structuring methods with simulation: the philosophical and practical challenges
Kotiadis, K. and Mingers, J. 2014. Combining problem structuring methods with simulation: the philosophical and practical challenges. in: Discrete Event Simulation and System Dynamics for Management Decision Making Chichester Wiley. pp. 52-75