Workforce predictive risk modelling: development of a model to identify general practices at risk of a supply−demand imbalance

Extract from abstract:

Objective
This study aimed to develop a risk prediction model identifying general practices at risk of workforce supply–demand imbalance.

Results
Based on historical data, the predictive model had fair to good discriminatory ability to predict which practices faced supply–demand imbalance (area under receiver operating characteristic curve=0.755). Predictions using current data suggested that, on average, practices at highest risk of future supply–demand imbalance are currently characterised by having larger patient lists, employing more nurses, serving more deprived and younger populations, and having considerably worse patient experience ratings when compared with other practices. Incorporating findings from a survey of GP’s career intentions made little difference to predictions of future supply–demand risk status when compared with expected future workforce projections based only on routinely available data on GPs’ gender and age.

Conclusions
It is possible to make reasonable predictions of an individual general practice’s future risk of undersupply of GP workforce with respect to its patient population. However, the predictions are inherently limited by the data available.

This article is open access.