Cost‐effective workforce planning: optimising the dental team skill‐mix for England

As increasing numbers of older people retain their teeth for longer, the result is a dramatic change in both the volume and type of dental treatment required. In response to the ageing population issues, changing dental needs, a shortage of NHS dentists, and the creation of new roles in the dental profession, both the UK Department of Health and British Dental Association have emphasised the importance of dental workforce planning and in particular to estimating the size and skill‐mix of the dental team. The dental team includes such professions as dentists, hygienists, therapists and technicians. The purpose of this paper is to present collaborative work between operational researchers and dental public health researchers, and as such is the first academic project to utilise operational research (OR) techniques to address issues surrounding predictions on demand and supply of dental activities in England, with recommendations on the necessary skill‐mix of the dental team.

A three‐stage model has been constructed to predict demand for dental treatment, dental workforce supply and optimisation of the skill‐mix of the dental workforce team over the next 20 years. A cost‐benefit study is included and Monte Carlo simulation is used for sensitivity analysis.

The findings reveal a significant shortage in dental workforce supply, both currently and projected for the short‐term future.

Demand for dental treatment is certain to rise over the next 20 or more years. An ageing population coupled with trends in increased tooth retention will have a significant impact on the need and demand for dental care amongst older people in the future. This research makes a series of recommendations in order to expand public care provision in a cost‐effective manner.

There is an urgent need to provide recommendations on the desirable skill‐mix of dental teams, and their cost‐effectiveness. This paper presents novel collaborative work between operational researchers and dental public health researchers, and as such is the first academic project to utilise OR techniques to address issues surrounding predictions on demand and supply of dental activities.