Primary care workforce: How can we identify those general practices at risk of a supply demand imbalance?

Talk Code: 
3D.3
Presenter: 
Gary Abel
Co-authors: 
Mayam Gomez Cano, Andi Smart, Nav Mustafee, Emily Fletcher, John Campbell
Author institutions: 
University of Exeter

Problem

British general practice has been described as being in crisis. Many GPs are close to retirement age and low levels of morale are potentially driving GPs to quit direct patient care. This, combined with a shortage of qualified GPs available to replace those leaving patient care, provides potential for some practices to find themselves in a situation where they do not have the supply of workforce to cope with the demands of patients. Strategies and interventions exist to aid retention of existing workforce. In order to apply these in the most effective manner it would be beneficial to first identify those practices at highest risk of facing a supply demand imbalance.

Approach

We first define a conceptual framework whereby practices in supply demand imbalance are those where workload is high, resulting in poor access for patients. We operationalise this concept using GP Patient survey scores and routine data on practice registered populations and workforce, and identify those practice currently in imbalance according to our framework. A hybrid modelling approach was used to predict imbalance based on practice factors including current workload, current GP Patient Survey scores, nurse workforce, projected populations and the projected fraction of current GP Full Time Equivalents (FTEs) expected to remain in direct patient care in 5-years’ time. For the latter we use two approaches; 1) using age and gender profiles of practice staff along with information on mean retirement rates at different ages 2) results from our own survey of GPs career intentions in south-west England. The predictive model was developed using national data from 2012 and subsequently applied to current data for practices in south-west England.

Findings

The strongest predictors of a practice’s future status were existing access and workload. There was some evidence that the projected fraction of current GP FTE expected to remain in direct patient care mattered more when the ratio of nurse to GP FTE was higher. Scenario modelling was conducted where a) the future population was projected to be higher than expected and b) the effect of GPs leaving patient care was enhanced (simulating increased difficulty in recruitment). These changed the ordering of practices found to be at highest risk of future supply demand imbalance, but only when substantial changes were made.

Consequences

Whilst it is possible to construct models around GP workforce for individual practices, the gain from doing so is marginal except in the situation where extreme changes are to be seen, for example very large expansions in patient population or extreme difficulty in recruiting new GPs. The majority of previous modelling has been done at a system level where uncertainties pertaining to individual practices are not an issue and may still hold value.

Submitted by: 
Gary Abel
Funding acknowledgement: 
The project was funded by the National Institute for Health Research, Health Service and Delivery Research programme (project 14/196/02). The views and opinions expressed herein are those of the authors and do not necessarily reflect those of the Health Service and Delivery Research programme, the National Institute for Health Research, the National Health Service, or the Department of Health.