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Discrete Event Simulation-Based Resource Modelling in Health Technology Assessment

Author

Listed:
  • Syed Salleh

    (University of Sheffield)

  • Praveen Thokala

    (University of Sheffield)

  • Alan Brennan

    (University of Sheffield)

  • Ruby Hughes

    (University of Sheffield)

  • Simon Dixon

    (University of Sheffield)

Abstract

Objective The objective of this article was to conduct a systematic review of published research on the use of discrete event simulation (DES) for resource modelling (RM) in health technology assessment (HTA). RM is broadly defined as incorporating and measuring effects of constraints on physical resources (e.g. beds, doctors, nurses) in HTA models. Methods Systematic literature searches were conducted in academic databases (JSTOR, SAGE, SPRINGER, SCOPUS, IEEE, Science Direct, PubMed, EMBASE) and grey literature (Google Scholar, NHS journal library), enhanced by manual searchers (i.e. reference list checking, citation searching and hand-searching techniques). Results The search strategy yielded 4117 potentially relevant citations. Following the screening and manual searches, ten articles were included. Reviewing these articles provided insights into the applications of RM: firstly, different types of economic analyses, model settings, RM and cost-effectiveness analysis (CEA) outcomes were identified. Secondly, variation in the characteristics of the constraints such as types and nature of constraints and sources of data for the constraints were identified. Thirdly, it was found that including the effects of constraints caused the CEA results to change in these articles. Conclusion The review found that DES proved to be an effective technique for RM but there were only a small number of studies applied in HTA. However, these studies showed the important consequences of modelling physical constraints and point to the need for a framework to be developed to guide future applications of this approach.

Suggested Citation

  • Syed Salleh & Praveen Thokala & Alan Brennan & Ruby Hughes & Simon Dixon, 2017. "Discrete Event Simulation-Based Resource Modelling in Health Technology Assessment," PharmacoEconomics, Springer, vol. 35(10), pages 989-1006, October.
    • Handle: RePEc:spr:pharme:v:35:y:2017:i:10:d:10.1007_s40273-017-0533-1
    DOI: 10.1007/s40273-017-0533-1
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    References listed on IDEAS

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    1. L. Standfield & T. Comans & M. Raymer & S. O’Leary & N. Moretto & P. Scuffham, 2016. "The Efficiency of Increasing the Capacity of Physiotherapy Screening Clinics or Traditional Medical Services to Address Unmet Demand in Orthopaedic Outpatients: A Practical Application of Discrete Eve," Applied Health Economics and Health Policy, Springer, vol. 14(4), pages 479-491, August.
    2. Syed Salleh & Praveen Thokala & Alan Brennan & Ruby Hughes & Andrew Booth, 2017. "Simulation Modelling in Healthcare: An Umbrella Review of Systematic Literature Reviews," PharmacoEconomics, Springer, vol. 35(9), pages 937-949, September.
    3. L. B. Standfield & T. A. Comans & P. A. Scuffham, 2017. "An empirical comparison of Markov cohort modeling and discrete event simulation in a capacity-constrained health care setting," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(1), pages 33-47, January.
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    Cited by:

    1. Carmen María Yago & Francisco Javier Díez, 2023. "DESnets: A Graphical Representation for Discrete Event Simulation and Cost-Effectiveness Analysis," Mathematics, MDPI, vol. 11(7), pages 1-24, March.

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