Assessing communication quality of consultations in primary care: initial reliability of the Global Consultation Rating Scale, based on the Calgary-Cambridge Guide to the Medical Interview.

Abstract

OBJECTIVES: To investigate initial reliability of the Global Consultation Rating Scale (GCRS: an instrument to assess the effectiveness of communication across an entire doctor-patient consultation, based on the Calgary-Cambridge guide to the medical interview), in simulated patient consultations. DESIGN: Multiple ratings of simulated general practitioner (GP)-patient consultations by trained GP evaluators. SETTING: UK primary care. PARTICIPANTS: 21 GPs and six trained GP evaluators. OUTCOME MEASURES: GCRS score. METHODS: 6 GP raters used GCRS to rate randomly assigned video recordings of GP consultations with simulated patients. Each of the 42 consultations was rated separately by four raters. We considered whether a fixed difference between scores had the same meaning at all levels of performance. We then examined the reliability of GCRS using mixed linear regression models. We augmented our regression model to also examine whether there were systematic biases between the scores given by different raters and to look for possible order effects. RESULTS: Assessing the communication quality of individual consultations, GCRS achieved a reliability of 0.73 (95% CI 0.44 to 0.79) for two raters, 0.80 (0.54 to 0.85) for three and 0.85 (0.61 to 0.88) for four. We found an average difference of 1.65 (on a 0-10 scale) in the scores given by the least and most generous raters: adjusting for this evaluator bias increased reliability to 0.78 (0.53 to 0.83) for two raters; 0.85 (0.63 to 0.88) for three and 0.88 (0.69 to 0.91) for four. There were considerable order effects, with later consultations (after 15-20 ratings) receiving, on average, scores more than one point higher on a 0-10 scale. CONCLUSIONS: GCRS shows good reliability with three raters assessing each consultation. We are currently developing the scale further by assessing a large sample of real-world consultations.