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Modelling the size and skill-mix of hospital nursing teams

Harper, Paul Robert, Powell, N. H. and Williams, Janet Elizabeth 2009. Modelling the size and skill-mix of hospital nursing teams. Journal of the Operational Research Society 61 (5) , pp. 768-779. 10.1057/jors.2009.43

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Abstract

Previously published work has described the development of a hospital capacity simulation tool, PROMPT. PROMPT has now been adopted by a number of hospitals in the UK and is used for both strategic and operational planning and management of key hospital resources. The work, as presented here, extends the PROMPT functionality to consider in more detail workforce issues. In particular, working with some of the current hospital users, the research has focussed on detailed planning for calculating the size and skill-mix of inpatient nursing teams. The chosen methodology utilizes both simulation and optimization. Outputs from the PROMPT three-phase discrete event simulation are fed into a stochastic programme which suggests the optimal number of nurses to employ (whole time equivalents) by skill-mix and the corresponding numbers by shift. A novel feature of the tool is the ability to predict and compare nursing needs based on different methods of capturing patient-to-nurse ratios as currently adopted across the UK National Health Service. Illustrative results from one hospital demonstrate that although the overall sizes of nursing teams on different wards are of an acceptable level and comparable to the outputs from the simulation phase of the work, often the number of nurses employed at different grades is not well matched to patient needs and the skill-mix should be reconsidered. Results from the optimization phase of the work suggest that it is cost beneficial to increase the number of permanently employed nurses to account for fluctuations in demand and corresponding high costs of temporary (agency) nurses. The scenario functionality of the tool permits for the study of changing size and skill-mix as a consequence of changes in patient volumes, patient case-mix, numbers of beds and length of stay.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Mathematics
Subjects: Q Science > QA Mathematics
Uncontrolled Keywords: simulation; stochastic programming; healthcare modelling; nurse skill-mix
Publisher: Palgrave Macmillan
ISSN: 0160-5682
Last Modified: 04 Jun 2017 02:57
URI: http://orca.cf.ac.uk/id/eprint/14599

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