Understanding the Changes in Adult Social Care Workforce Estimation
Skills for Care regularly publishes estimates on the size and structure of the adult social care workforce in England. Yet, as methodologies evolve and new information arises, they’ve made key improvements to ensure the reliability and comparability of their data over time. Here, we outline the significant methodology updates for the 2022/23 report and their implications.
Methodological Enhancements Impacting Historical Data:
- Dormant Locations:
For the first time, Skills for Care has accounted for ‘dormant’ service locations, such as temporarily closed care homes or domiciliary care providers without active contracts. This distinction was based on data from the Care Quality Commission (CQC). Incorporating these dormant locations into their modeling has slightly reduced staffing estimates. To maintain consistency, adjustments for dormancy levels have been retrospective, affecting past years’ figures as well. - Estimating Individual Employers and Personal Assistants:
The process for estimating the number of individual employers and personal assistants has been refined using a sophisticated data engineering pipeline. This pipeline introduces mean imputation, extrapolation, and interpolation techniques to better estimate data gaps. Additionally, a rolling average and enhanced logic have been utilized to account for anomalies and maintain data integrity.
Implications for Workforce Data:
- Changes in Workforce Size Estimates:
The revisions, especially regarding dormant locations and personal assistants, have created new historical estimates for the size of the workforce, which then affect the characteristics attributed to the workforce data. - Sickness Data Refinement:
Upon user feedback, Skills for Care learned some sickness data inaccuracies were due to misreported days. To address this, they’ve implemented a filter capping the number of sickness days based on estimated annual working days. This correction has been back-applied to improve the accuracy of historical sickness trends. - Turnover Analysis Improvement:
By fine-tuning the factors affecting turnover, including a new filter to exclude workplaces not updating leaver data accurately, Skills for Care has greatly improved the quality of their analysis. This does, however, mean the updated turnover figures can no longer be directly compared to previously published data.
Conclusion:
The 2022/23 report by Skills for Care marks a significant step in enhancing the accuracy and usefulness of adult social care workforce data. The methodological advancements, while impacting past data, enable a more precise reflection of the workforce’s status. Such improvements are pivotal to shaping effective care policies, funding decisions, and support mechanisms within the sector.
For further details on the new methodologies and their effects, reach out to Skills for Care at analysis@skillsforcare.org.uk, or visit their Workforce Intelligence webpage.
