Modelling the future supply of vets and vet nurses

A report for the Royal College of Veterinary Surgeons

This report presents the results of the workforce modelling exercise for veterinary surgeons and veterinary nurses, undertaken by the Institute for Employment Studies for the Royal College of Veterinary Surgeons.

The aim of the work was to forecast the likely number of vets and vet nurses in the future, by a range of personal and sector characteristics, out to 2035. The forecasts were derived on the basis of a continuation of recent trends in numbers, and using latest forecasts of new entrants from vet schools. The model also allows for assumptions to be adjusted, so that alternative future scenarios can be developed.

Methodology overview: Vet surgeons modelling

RCVS provided IES with individual level data on vet surgeons who were on the Register at some point between 2017 and 2023 – a total of 43,933 vets. Separate datasets provided details of status changes (moves on and off the Register) and on changes in category (moving between UK practising and other statuses e.g. non-practising, overseas practising etc.). These datasets could include multiple entries for each vet, depending upon their career trajectory.

IES undertook a cleaning and merging process to prepare the dataset for analysis of trends over 2017 to 2023, to be used as the basis for the modelling. Details of status and category changes were used to define vets’ statuses as at 31 July 2017 (for those whose initial registration date was before then), and then these status and category changes were tracked forward to define vets’ statuses as at 31 July in each subsequent year. So vets might leave the Register or change category out of UK practising between 31 July 2017 and 31 July 2018, while others might be restored to the Register, change category into UK practising, and join the Register as newly qualified vets between the two timepoints.

The modelling exercise was then undertaken using an inflow/outflow approach, where the number of vets in each year is calculated as the number in the previous year, minus those who were removed from the Register or who moved out of UK practising status, plus those who joined the Register, were restored to the Register following a break in registration, and those who moved in to UK practising. There are also flows between age groups as the vet population ages over time. While the flow rates are relatively high (on average over the last 6 years, 5% of vets leave each year while in-flows represent 9% of the previous year’s total number), a large proportion of the future supply will be those who are already in the profession – more than half of UK national vets aged under 60 in 10 years’ time are those currently on the Register as UK practising.

Methodology overview: Vet nurses modelling

For the vet nurses modelling, RCVS provided IES with a dataset containing details of vet nurses who were on the Register at some point between 2017 and 2023 – a total of 25,772 vet nurses. A separate dataset provided details of moves off and onto the Register.

The vet nurses dataset went through a similar cleaning process as the vet surgeons data to identify vet nurses on the Register each year, flows from and onto the Register.

The modelling approach used age and field of work only, as data were not available for nationality, there are too few male and ethnic minority vet nurses to provide meaningful breakdowns, and data on species type was missing for 98% of vet nurses.

Estimates of vet nurses in the future by age group and field of work were calculated using the inflow/outflow approach for 42 combinations of variables (7 age bands x 6 fields of work).