Exploring variation in referral decisions in primary care
Research type
Research Study
Full title
Exploring variation in referral decisions in primary care using Signal Detection Theory
IRAS ID
162493
Contact name
Olga Kostopoulou
Contact email
Research summary
GPs’ suspicion of serious disease, such as cancer, and patient referral to secondary care can be thought of as classic Signal Detection problems. Signal Detection Theory (SDT) can be applied when a stimulus (‘signal’) must be detected during a succession of trials, some of which contain the stimulus (‘signal’ trials) and some of which do not (‘noise’ trials). GPs seek to detect possible serious disease (‘signal’) out of a population of patients without serious disease (‘noise’). The reason diseases are missed or patients without disease get referred is that the evidence available for referral decisions is weak or ambiguous. In primary care, where diseases can present early and with non-specific symptoms, there is an inherent difficulty with detection and referral decisions for serious diseases, such as cancer. SDT allows us to calculate measures such as threshold and discrimination ability for individual decision makers casting their decisions on a large number of simulated cases (vignettes). GPs may differ in either their threshold (liberal vs. conservative) or their discrimination ability (ability to discriminate between ‘signal’ and ‘noise’, as defined above) or both. We aim to calculate these indices for a sizeable group of GPs and then look for their determinants, e.g. age, gender, experience, and practice demographics.
REC name
East of Scotland Research Ethics Service REC 1
REC reference
14/ES/1063
Date of REC Opinion
20 Aug 2014
REC opinion
Favourable Opinion