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

ABSTRACT: 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.

SUBMITTER: Buchan J

PROVIDER: S-EPMC3459709 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

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

Buchan James J Seccombe Ian I

Human resources for health 20120712

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 varyin ...[more]

PMID: 22788264

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Project description:ObjectivesAn initial report of findings from 1.14 million SARS CoV-2 serology tests in National Health Service (NHS) staff to compare NHS staff seroconversion with community seroconversion rates at a regional level.DesignA national cross-sectional survey.SettingA SARS-CoV-2 antibody testing programme offered across all NHS Trusts.Participants1.14 million NHS staff.InterventionSARS-CoV-2 antibody testing.Primary and secondary outcome measuresSARS-CoV-2 antibody testing was used to estimate the seroprevalence of SARS-CoV-2 in NHS staff by region, compared with community seroprevalence as determined by the COVID-19 Infection Survey (Office for National Statistics). We also explored seroprevalence trends by regional COVID-19 activity, using regional death rates as a proxy for COVID-19 'activity'.Results1 146 310 tests were undertaken on NHS staff between 26 May and 31 August 2020. 186 897 NHS tests were positive giving a seroconversion rate of 16.3% (95% CI 16.2% to 16.4%), in contrast to the national community seroconversion rate of 5.9% (95% CI 5.3% to 6.6%). There was significant geographical regional variation, which mirrored the trends seen in community prevalence rates. NHS staff were infected at a higher rate than the general population (OR 3.1, 95% CI 2.8 to 3.5). NHS seroconversion by regional death rate suggested a trend towards higher seroconversion rates in the areas with higher COVID-19 'activity'.ConclusionsThis is the first cross-sectional survey assessing the risk of COVID-19 disease in healthcare workers at a national level. It is the largest study of its kind. It suggests that NHS staff have a significantly higher rate of COVID-19 seroconversion compared with the general population in England, with regional variation across the country which matches the background population prevalence trends. There was also a trend towards higher seroconversion rates in areas which had experienced high COVID-19 clinical activity. This work has global significance in terms of the value of such a testing programme and contributing to the understanding of healthcare worker seroconversion at a national level.

Project description:Development of land resources can contribute to increased economic productivity but can also negatively affect the extent and condition of native vegetation, jeopardize the persistence of native species, reduce water quality, and erode ecosystem services. Spatial planning must therefore balance outcomes for conservation, development, and social goals. One approach to evaluating these trade-offs is scenario planning. In this paper we demonstrate methods for incorporating stakeholder preferences into scenario planning through both defining scenario objectives and evaluating the scenarios that emerge. In this way, we aim to develop spatial plans capable of informing actual land-use decisions. We used a novel approach to scenario planning that couples optimal land-use design and social evaluation of environmental outcomes. Four land-use scenarios combined differences in total clearing levels (10% and 20%) in our study region, the Daly Catchment Australia, with the presence or absence of spatial precincts to concentrate irrigated agriculture. We used the systematic conservation planning tool Marxan with Zones to optimally plan for multiple land-uses that met objectives for both conservation and development. We assessed the performance of the scenarios in terms of the number of objectives met and the degree to which existing land-use policies were compromised (e.g., whether clearing limits in existing guidelines were exceeded or not). We also assessed the land-use scenarios using expected stakeholder satisfaction with changes in the catchment to explore how the scenarios performed against social preferences. There were a small fraction of conservation objectives with high conservation targets (100%) that could not be met due to current land uses; all other conservation and development objectives were met in all scenarios. Most scenarios adhered to the existing clearing guidelines with only marginal exceedances of limits, indicating that the scenario objectives were compatible with existing policy. We found that two key stakeholder groups, agricultural and Indigenous residents, had divergent satisfaction levels with the amount of clearing and agricultural development. Based on the range of benefits and potential adverse impacts of each scenario, we suggest that the 10% clearing scenarios are most aligned with stakeholder preferences and best balance preferences across stakeholder groups. Our approach to scenario planning is applicable generally to exploring the potential conflicts between goals for conservation and development. Our case study is particularly relevant to current discussion about increased agricultural and pastoral development in northern Australia.

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

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

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