Quantitative modelling for wait time reduction: A comprehensive simulation applied in general surgery

Peter T. Vanberkel, J.T. Blake

Research output: Book/ReportBookAcademic

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Abstract

This thesis describes the use of operational research techniques to analyze the wait list for the division of general surgery at the Capital District Health Authority (CDHA) in Halifax, Nova Scotia, Canada. A comprehensive simulation model was developed to facilitate capacity planning decisions and to analyze the performance of the division. At the time of the study the wait list for elective general surgery patients was observed to be growing by approximately 13.2 days per year with no concrete plan to address it. The analysis examined the consequences of redistributing beds between sites, assigning operating room time by surgeon demand, and achieving standard patient lengths of stay, while contrasting them to current and additional resource options. From the results, multiple independent and combined options for stabilizing and decreasing waits for elective procedures were proposed.
Original languageUndefined
Place of PublicationSaarbrücken, Germany
PublisherVDM Verlag Dr. Müller
Number of pages100
ISBN (Print)978-3-63909-370-4
Publication statusPublished - 2008

Keywords

  • EWI-17671

Cite this

Vanberkel, P. T., & Blake, J. T. (2008). Quantitative modelling for wait time reduction: A comprehensive simulation applied in general surgery. Saarbrücken, Germany: VDM Verlag Dr. Müller.
Vanberkel, Peter T. ; Blake, J.T. / Quantitative modelling for wait time reduction: A comprehensive simulation applied in general surgery. Saarbrücken, Germany : VDM Verlag Dr. Müller, 2008. 100 p.
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Vanberkel, PT & Blake, JT 2008, Quantitative modelling for wait time reduction: A comprehensive simulation applied in general surgery. VDM Verlag Dr. Müller, Saarbrücken, Germany.

Quantitative modelling for wait time reduction: A comprehensive simulation applied in general surgery. / Vanberkel, Peter T.; Blake, J.T.

Saarbrücken, Germany : VDM Verlag Dr. Müller, 2008. 100 p.

Research output: Book/ReportBookAcademic

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N2 - This thesis describes the use of operational research techniques to analyze the wait list for the division of general surgery at the Capital District Health Authority (CDHA) in Halifax, Nova Scotia, Canada. A comprehensive simulation model was developed to facilitate capacity planning decisions and to analyze the performance of the division. At the time of the study the wait list for elective general surgery patients was observed to be growing by approximately 13.2 days per year with no concrete plan to address it. The analysis examined the consequences of redistributing beds between sites, assigning operating room time by surgeon demand, and achieving standard patient lengths of stay, while contrasting them to current and additional resource options. From the results, multiple independent and combined options for stabilizing and decreasing waits for elective procedures were proposed.

AB - This thesis describes the use of operational research techniques to analyze the wait list for the division of general surgery at the Capital District Health Authority (CDHA) in Halifax, Nova Scotia, Canada. A comprehensive simulation model was developed to facilitate capacity planning decisions and to analyze the performance of the division. At the time of the study the wait list for elective general surgery patients was observed to be growing by approximately 13.2 days per year with no concrete plan to address it. The analysis examined the consequences of redistributing beds between sites, assigning operating room time by surgeon demand, and achieving standard patient lengths of stay, while contrasting them to current and additional resource options. From the results, multiple independent and combined options for stabilizing and decreasing waits for elective procedures were proposed.

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Vanberkel PT, Blake JT. Quantitative modelling for wait time reduction: A comprehensive simulation applied in general surgery. Saarbrücken, Germany: VDM Verlag Dr. Müller, 2008. 100 p.