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Using scenarios to assess the future supply of NHS nursing staff in England

Overview of attention for article published in Human Resources for Health, July 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

1 policy source
2 tweeters


5 Dimensions

Readers on

35 Mendeley
Using scenarios to assess the future supply of NHS nursing staff in England
Published in
Human Resources for Health, July 2012
DOI 10.1186/1478-4491-10-16
Pubmed ID

James Buchan, Ian Seccombe


This paper examines issues related to the future supply of registered nursing staff, midwives and health visitors in the National Health Service (NHS) in England at a time when there are major public sector funding constraints and as more of these staff are reaching retirement age. Based on available workforce data, the paper reviews different possible scenarios for the supply of NHS nurses over a ten year period, assessing the impact of different numbers of new staff being trained and of varying retirement patterns from the ageing profession.The government in England has more policy levers available than is the case in many other countries. It determines the number of pre-registration training places that are commissioned and funded, it is the major employer, and it also controls the inflow of nurses from other countries through migration policies. Scenario models provide a picture of what the future might look like under various assumptions. These outcomes can be quantified and the results used to assess the risks and opportunities of alternate policy decisions. The approach used in this paper is that of the aggregate deterministic supply model.As part of this exercise, eight scenarios were selected and modelled. These were:A. "No change"- current inflows and outflowsB. "Redundancies" - current inflow with higher outflowC. "Improved retention" - current inflow with lower outflowD. "Reduced training intakes A" - lower inflows with lower outflowE. "Reduced training intakes B" - lower inflow with higher outflowsF. "Pension time-bomb"- current inflow with a higher rate of retirementG. "Pension delayed"- current inflow with a lower rate of retirementH. "Worst case" - lower inflow and higher outflow including higher retirementMost of the scenarios indicate that a reduction in the supply of nursing staff to NHS England is possible over the next ten years. Small changes in assumptions can make a substantial difference to outcomes and therefore emphasize the point that it is unwise to base policy decisions on a single projection. It is important that different scenarios are considered that may be regarded as possible futures, based on a realistic assessment of the available workforce data, policies and broader labour market and funding outlook.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 3%
United Kingdom 1 3%
Unknown 33 94%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 29%
Researcher 5 14%
Unspecified 4 11%
Student > Doctoral Student 4 11%
Other 3 9%
Other 9 26%
Readers by discipline Count As %
Unspecified 6 17%
Medicine and Dentistry 6 17%
Social Sciences 5 14%
Nursing and Health Professions 5 14%
Business, Management and Accounting 4 11%
Other 9 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 January 2017.
All research outputs
of 12,440,173 outputs
Outputs from Human Resources for Health
of 665 outputs
Outputs of similar age
of 119,943 outputs
Outputs of similar age from Human Resources for Health
of 9 outputs
Altmetric has tracked 12,440,173 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 665 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.8. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 119,943 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 7 of them.