A controlled trial of three referral methods for patients with third molars.

Aim To evaluate the accuracy, sensitivity and specificity of three primary to secondary care referral strategies. Method Thirtytwo primary care dental practitioners (GDPs) were randomly allocated one of three referral strategies: current practice (control strategy); a neural network embedded within a computer program and a paper-based clinical algorithm. One hundred and seven patients were assessed for lower third molar treatment: 47, 30 and 30 in each group, respectively. Clinical details were assessed by a panel of experts against a gold standard for third molar removal (the National Institutes of Health criteria). The accuracy sensitivity, specificity, positive and negative predictive values were calculated for each strategy. Results The referral decisions made by the GDPs in the control group displayed greater accuracy and sensitivity but poorer specificity (0.83; 4.97; 0.22) compared with the neural network (0.67; 0.56; 0.79) and clinical algorithm (0.73; 0.56; 0.93). Conclusions It was concluded that incorporation of the clinical algorithm into primary care was the most appropriate option. The computer neural network performed less well than either current practice or the clinical algorithm.