Modelling the size and skill-mix of hospital nursing teams
P R Harper (),
N H Powell and
J E Williams
Additional contact information
P R Harper: Cardiff University
N H Powell: University of Southampton
J E Williams: Cardiff University
Journal of the Operational Research Society, 2010, vol. 61, issue 5, 768-779
Abstract:
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.
Keywords: simulation; stochastic programming; healthcare modelling; nurse skill-mix (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://link.springer.com/10.1057/jors.2009.43 Abstract (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:pal:jorsoc:v:61:y:2010:i:5:d:10.1057_jors.2009.43
Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/41274
DOI: 10.1057/jors.2009.43
Access Statistics for this article
Journal of the Operational Research Society is currently edited by Tom Archibald and Jonathan Crook
More articles in Journal of the Operational Research Society from Palgrave Macmillan, The OR Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().