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A modelling tool for capacity planning in acute and community stroke services

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A modelling tool for capacity planning in acute and community stroke services. / Monks, Thomas; Worthington, David John; Allen, Michael et al.
In: BMC Health Services Research, Vol. 16, 530, 29.09.2016.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Monks, T, Worthington, DJ, Allen, M, Pitt, M, Stein, K & James, MA 2016, 'A modelling tool for capacity planning in acute and community stroke services', BMC Health Services Research, vol. 16, 530. https://doi.org/10.1186/s12913-016-1789-4

APA

Monks, T., Worthington, D. J., Allen, M., Pitt, M., Stein, K., & James, M. A. (2016). A modelling tool for capacity planning in acute and community stroke services. BMC Health Services Research, 16, Article 530. https://doi.org/10.1186/s12913-016-1789-4

Vancouver

Monks T, Worthington DJ, Allen M, Pitt M, Stein K, James MA. A modelling tool for capacity planning in acute and community stroke services. BMC Health Services Research. 2016 Sept 29;16:530. doi: 10.1186/s12913-016-1789-4

Author

Monks, Thomas ; Worthington, David John ; Allen, Michael et al. / A modelling tool for capacity planning in acute and community stroke services. In: BMC Health Services Research. 2016 ; Vol. 16.

Bibtex

@article{b12bcc4d5d7a424a9fdd6302415e5d79,
title = "A modelling tool for capacity planning in acute and community stroke services",
abstract = "BackgroundMathematical capacity planning methods that can take account of variations in patient complexity, admission rates and delayed discharges have long been available, but their implementation in complex pathways such as stroke care remains limited. Instead simple average based estimates are commonplace. These methods often substantially underestimate capacity requirements.We analyse the capacity requirements for acute and community stroke services in a pathway with over 630 admissions per year. We sought to identify current capacity bottlenecks affecting patient flow, future capacity requirements in the presence of increased admissions, the impact of co-location and pooling of the acute and rehabilitation units and the impact of patient subgroups on capacity requirements. We contrast these results to the often used method of planning by average occupancy, often with arbitrary uplifts to cater for variability.MethodsWe developed a discrete-event simulation model using aggregate parameter values derived from routine administrative data on over 2000 anonymised admission and discharge timestamps. The model mimicked the flow of stroke, high risk TIA and complex neurological patients from admission to an acute ward through to community rehab and early supported discharge, and predicted the probability of admission delays.ResultsAn increase from 10 to 14 acute beds reduces the number of patients experiencing a delay to the acute stroke unit from 1 in every 7 to 1 in 50. Co-location of the acute and rehabilitation units and pooling eight beds out of a total bed stock of 26 reduce the number of delayed acute admissions to 1 in every 29 and the number of delayed rehabilitation admissions to 1 in every 20. Planning by average occupancy would resulted in delays for one in every five patients in the acute stroke unit.ConclusionsPlanning by average occupancy fails to provide appropriate reserve capacity to manage the variations seen in stroke pathways to desired service levels. An appropriate uplift from the average cannot be based simply on occupancy figures. Our method draws on long available, intuitive, but underused mathematical techniques for capacity planning. Implementation via simulation at our study hospital provided valuable decision support for planners to assess future bed numbers and organisation of the acute and rehabilitation services.",
keywords = "stroke, capacity planning, simulation, average occupancy",
author = "Thomas Monks and Worthington, {David John} and Michael Allen and Martin Pitt and Ken Stein and James, {Martin A.}",
year = "2016",
month = sep,
day = "29",
doi = "10.1186/s12913-016-1789-4",
language = "English",
volume = "16",
journal = "BMC Health Services Research",
issn = "1472-6963",
publisher = "BMC",

}

RIS

TY - JOUR

T1 - A modelling tool for capacity planning in acute and community stroke services

AU - Monks, Thomas

AU - Worthington, David John

AU - Allen, Michael

AU - Pitt, Martin

AU - Stein, Ken

AU - James, Martin A.

PY - 2016/9/29

Y1 - 2016/9/29

N2 - BackgroundMathematical capacity planning methods that can take account of variations in patient complexity, admission rates and delayed discharges have long been available, but their implementation in complex pathways such as stroke care remains limited. Instead simple average based estimates are commonplace. These methods often substantially underestimate capacity requirements.We analyse the capacity requirements for acute and community stroke services in a pathway with over 630 admissions per year. We sought to identify current capacity bottlenecks affecting patient flow, future capacity requirements in the presence of increased admissions, the impact of co-location and pooling of the acute and rehabilitation units and the impact of patient subgroups on capacity requirements. We contrast these results to the often used method of planning by average occupancy, often with arbitrary uplifts to cater for variability.MethodsWe developed a discrete-event simulation model using aggregate parameter values derived from routine administrative data on over 2000 anonymised admission and discharge timestamps. The model mimicked the flow of stroke, high risk TIA and complex neurological patients from admission to an acute ward through to community rehab and early supported discharge, and predicted the probability of admission delays.ResultsAn increase from 10 to 14 acute beds reduces the number of patients experiencing a delay to the acute stroke unit from 1 in every 7 to 1 in 50. Co-location of the acute and rehabilitation units and pooling eight beds out of a total bed stock of 26 reduce the number of delayed acute admissions to 1 in every 29 and the number of delayed rehabilitation admissions to 1 in every 20. Planning by average occupancy would resulted in delays for one in every five patients in the acute stroke unit.ConclusionsPlanning by average occupancy fails to provide appropriate reserve capacity to manage the variations seen in stroke pathways to desired service levels. An appropriate uplift from the average cannot be based simply on occupancy figures. Our method draws on long available, intuitive, but underused mathematical techniques for capacity planning. Implementation via simulation at our study hospital provided valuable decision support for planners to assess future bed numbers and organisation of the acute and rehabilitation services.

AB - BackgroundMathematical capacity planning methods that can take account of variations in patient complexity, admission rates and delayed discharges have long been available, but their implementation in complex pathways such as stroke care remains limited. Instead simple average based estimates are commonplace. These methods often substantially underestimate capacity requirements.We analyse the capacity requirements for acute and community stroke services in a pathway with over 630 admissions per year. We sought to identify current capacity bottlenecks affecting patient flow, future capacity requirements in the presence of increased admissions, the impact of co-location and pooling of the acute and rehabilitation units and the impact of patient subgroups on capacity requirements. We contrast these results to the often used method of planning by average occupancy, often with arbitrary uplifts to cater for variability.MethodsWe developed a discrete-event simulation model using aggregate parameter values derived from routine administrative data on over 2000 anonymised admission and discharge timestamps. The model mimicked the flow of stroke, high risk TIA and complex neurological patients from admission to an acute ward through to community rehab and early supported discharge, and predicted the probability of admission delays.ResultsAn increase from 10 to 14 acute beds reduces the number of patients experiencing a delay to the acute stroke unit from 1 in every 7 to 1 in 50. Co-location of the acute and rehabilitation units and pooling eight beds out of a total bed stock of 26 reduce the number of delayed acute admissions to 1 in every 29 and the number of delayed rehabilitation admissions to 1 in every 20. Planning by average occupancy would resulted in delays for one in every five patients in the acute stroke unit.ConclusionsPlanning by average occupancy fails to provide appropriate reserve capacity to manage the variations seen in stroke pathways to desired service levels. An appropriate uplift from the average cannot be based simply on occupancy figures. Our method draws on long available, intuitive, but underused mathematical techniques for capacity planning. Implementation via simulation at our study hospital provided valuable decision support for planners to assess future bed numbers and organisation of the acute and rehabilitation services.

KW - stroke

KW - capacity planning

KW - simulation

KW - average occupancy

U2 - 10.1186/s12913-016-1789-4

DO - 10.1186/s12913-016-1789-4

M3 - Journal article

VL - 16

JO - BMC Health Services Research

JF - BMC Health Services Research

SN - 1472-6963

M1 - 530

ER -