Does longer roster lead-time reduce temporary staff usage? A regression analysis of e-rostering data from 77 hospital units

DRAKE, Robert (2018). Does longer roster lead-time reduce temporary staff usage? A regression analysis of e-rostering data from 77 hospital units. Journal of Advanced Nursing, 74 (8), 1831-1838.

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Abstract

Aims Utilisation of temporary nursing staff is contentious and expensive. Using e-rostering data from 77 hospital units, this research investigates whether longer roster lead-times reduce temporary staff usage. Background It is commonly assumed that longer roster approval lead-times, the time from when a roster is approved, to when it is worked, result in better, more cost-effective rosters. Consequently, many hospitals target lead-times of six weeks, a figure recommended for the UK National Health Service (NHS) in a recent governmental review. This contrasts with the minimum lead-time advocated by New South Wales Ministry of Health, which advises a shorter lead-time of two weeks. Using data from 77 hospital units, this paper explores this assumed relationship. Design Using data extracted from the e-rostering system of an NHS Acute Foundation Trust, this study uses linear regression analysis to explore the relationship between roster approval lead-time and temporary staff usage. The data were captured over a period of nine months from 15th February 2016 to 23rd October 2016, a total of 693 rosters. Results/Findings This research suggests that late roster approval may contribute to as much as 37% of temporary staff usage, while approval 4-6 weeks prior to the roster being worked reduces this to approximately 15%. However, this is only relevant under specific conditions. Importantly, this should be considered before mandating lead times across all units. Conclusions This research implies that the optimum approval lead-time lies between four to six weeks, however, given other challenges, achieving this in practice may prove difficult.

Item Type:	Article
Departments - Does NOT include content added after October 2018:	Faculty of Science, Technology and Arts > Department of Computing
Identification Number:	https://doi.org/10.1111/jan.13578
Page Range:	1831-1838
Depositing User:	Robert Drake
Date Deposited:	15 Mar 2018 09:51
Last Modified:	18 Mar 2021 05:16
URI:	https://shura.shu.ac.uk/id/eprint/18942

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