鶹Ů

Methodology

 

Methodology for creating workforce estimates

We estimate the size, structure and characteristics of the adult social care workforce in England, annually.

Good quality information about the adult social care workforce is vital to help improve the planning and quality of social care services, which will improve outcomes for people who use these services, both now and in the future.

 

Overview of our methodology

  • We use data collected by the Adult Social Care Workforce Data Set (ASC-WDS) to create workforce models that allow for estimates of the whole adult social care workforce to be produced.
  • Our methodology permits the analysis to be representative of all adult social care workers, even if the ASC-WDS has uneven levels of data coverage.
  • All data is validated at source and has been through rigorous data quality checks before analysis.
  • 鶹Ů has confidence in the quality of these estimates; the methodologies used have been peer reviewed by universities and an independent statistician. 

Details of our methodology 

The ASC-WDS collects information about the adult social care sector and workforce. It's structured into two parts;

The workplace

  • employment type or sector, e.g. local authority, private or voluntary/charity
  • main and other care services provided, e.g. residential care with or without nursing, or domiciliary care (35 service types in total)
  • geographical location
  • 鶹Ů registration information
  • care and support needs supported e.g. dementia care, learning disabilities (23 options)
  • new starters, staff leavers and vacancy information.

The workforce

  • main job role of workers (32 job role options)
  • contract type, e.g. permanent, temporary or agency
  • demographics e.g. gender, age, disability status, ethnicity and nationality
  • employment information e.g. zero-hours contracts, contracted or average hours, sickness rates
  • experience in sector and role, and source of recruitment
  • pay rate
  • qualification and training information, Care Certificate status and apprenticeship training
  • reasons for leaving.

Approximately half of the workforce are recorded in the ASC-WDS. This coverage varies by care service, job role and geographical area.

Local authorities (adult social services departments)

The Adult Social Care Workforce Data Set is the adult workforce data return for local authorities. From 2012 to 2021, all 151 local authorities in England met the criteria of a full data return for people working in their adult social services departments. This means we have data from every local authority with an adult social services department in England. In 2022 all local authorities apart from Salford submitted a return. In 2023 Cumbria divided into two new local authority areas (Cumberland and Westmoreland and Furness) but neither of the new areas provided a complete data return.

When local authorities do not provide a complete data submission, we use proxy information and estimations in place of the missing data.

  • For variables that are similar year on year, e.g. average age, gender and ethnicity, we use the previous year’s data as a proxy (where possible).
  • For variables that are likely to change e.g. starters, leavers, sickness and pay using a proxy is not possible. Instead, we use estimates to try and reduce the impact on national and regional totals.

 

鶹Ů-regulated services

  • 鶹Ů estimates that there were 39,000 care establishments providing or organising adult social care in England in 2022/23. As at March 2023 around 27,000 of these services were 鶹Ů-regulated.
  • In 2023, the ASC-WDS contained information on just under half coverage of all 鶹Ů-regulated social care establishments (49%).
  • These 鶹Ů-regulated establishments had completed around 456,500 worker records between them (out of a total population of around 1.1 million workers employed by 鶹Ů-regulated employers).

A sample of this size provides a solid basis for creating reliable and precise analysis about the adult social care workforce at both a national and local level.

We use data collected by the ASC-WDS to create workforce models that, in turn, allow for estimates of the whole adult social care workforce to be produced.

To do this, we make estimates of workforce characteristics (e.g. demographics, pay rates, employment statuses) for each geographical area, service type, employer type and job role combination that we report by.

These estimates are then ‘weighted’ according to coverage/completeness of the sector in each of the above areas. For example, an area with 50% coverage would use more weighted data in the final analysis than an area with 90% coverage. Using this methodology allows for the analysis to be representative of all adult social care workers even if the ASC-WDS has uneven levels of data coverage.

鶹Ů is confident in the quality of these estimates and the methodologies used have been peer reviewed by universities and an independent statistician. 

Every effort is made to ensure that information derived from the ASC-WDS is reliable.

  • In March 2023, the ASC-WDS contained information on just under half coverage of all 鶹Ů-regulated social care establishments (49%).
  • All data in the ASC-WDS has been updated or confirmed to be up to date within the last two years and most employers have updated their data in the past 12 months.
  • All data is validated at source and has been through rigorous data quality checks during the analysis.

 

Suppression and rounding for ASC-WDS publications

Coverage of the independent sector was estimated at 49% in March 2023, so the rounding outlined below reflects the degree of estimation. The local authority sector requires less rounding as the ASC-WDS has 100% coverage of the workforce (in 2023 all local authorities supplied a total number of filled posts, though other variables were not provided).

The following rounding rules have been applied to the ASC-WDS weighted workforce estimates.

Suppression 2024

  • We suppress information if there are less than 10 filled posts within any group. In some cases, for example when showing pay rates, suppression is used if there are less than 25 filled posts in a group.
  • Rounding and suppression rules are applied after any calculations (sums, averages, percentages etc.). This sometimes means numbers in tables may appear not to add up.

 Rationale for rounding and suppressing data

  • Rounding and suppression reduces the risk of identifying individuals from published figures. Even when the data contains no personally identifiable information.
  • Rounding of all figures to the nearest (see table above) prevents multiple tables being used to identify small numbers.
  • Percentages are suppressed for small groups to prevent percentages from giving away the real un-rounded figures in a table.
  • Percentages are displayed to zero decimal places unless there is a good statistical reason for using more precision.
  • Suppression reduced the risk of decisions being based on small sample sizes.

 

Our workforce estimates, publications and interactive visualisations

Our workforce estimates are used to produce national, regional and local area reports about the adult social care sector and workforce. We also publish reports about key workforce topics and interactive visualisations.

 

Requesting raw data

Read more about requesting raw analysis files in SPSS or CSV here.

Get in touch

Find out how you can use our expertise, data and understanding of the adult social care workforce

Contact us