Referral Decision Making of General Practitioners: A Signal Detection Study

Olga Kostopoulou, Martine Nurek, Simona Cantarella, Grace Okoli, Francesca Fiorentino and Brendan C. Delaney
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Olga Kostopoulou: Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK
Martine Nurek: Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK
Simona Cantarella: Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK
Grace Okoli: School of Population Health and Environmental Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, UK
Francesca Fiorentino: Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK
Brendan C. Delaney: Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK

Medical Decision Making, 2019, vol. 39, issue 1, 21-31

Abstract: Background. Signal detection theory (SDT) describes how respondents categorize ambiguous stimuli over repeated trials. It measures separately “discrimination†(ability to recognize a signal amid noise) and “criterion†(inclination to respond “signal†v. “noise†). This is important because respondents may produce the same accuracy rate for different reasons. We employed SDT to measure the referral decision making of general practitioners (GPs) in cases of possible lung cancer. Methods. We constructed 44 vignettes of patients for whom lung cancer could be considered and estimated their 1-year risk. Under UK risk-based guidelines, half of the vignettes required urgent referral. We recruited 216 GPs from practices across England. Practices differed in the positive predictive value (PPV) of their urgent referrals (chance of referrals identifying cancer) and the sensitivity (chance of cancer patients being picked up via urgent referral from their practice). Participants saw the vignettes online and indicated whether they would refer each patient urgently or not. We calculated each GP’s discrimination ( d  ′) and criterion ( c ) and regressed these on practice PPV and sensitivity, as well as on GP experience and gender. Results. Criterion was associated with practice PPV: as PPV increased, GPs’ c also increased, indicating lower inclination to refer ( b = 0.06 [0.02–0.09]; P = 0.001). Female GPs were more inclined to refer than male GPs ( b = −0.20 [−0.40 to −0.001]; P = 0.049). Average discrimination was modest ( d ′ = 0.77), highly variable (range, −0.28 to 1.91), and not associated with practice referral performance. Conclusions. High referral PPV at the organizational level indicates GPs’ inclination to avoid false positives, not better discrimination. Rather than bluntly mandating increases in practice PPV via more referrals, it is necessary to increase discrimination by improving the evidence base for cancer referral decisions.

Keywords: cancer referral; conversion rate; detection rate; primary care; signal detection theory (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:39:y:2019:i:1:p:21-31

DOI: 10.1177/0272989X18813357

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