Predicting diagnoses from illness experiences with common cold symptoms before physician consultation: a mixed-methods research

Objectives We aimed to explore whether patients’ illness experiences with common cold symptoms could help with predicting the final diagnosis before consultation. Design Exploratory sequential design of mixed methods: Qualitative and quantitative studies used inductive qualitative content analysis and multinomial regression analysis, respectively. Setting Consecutive patients at the primary care clinic of a general hospital. Participants New patients aged 15 years or older were included in the study. Of the 1512 eligible patients who received the questionnaire sheet, 408 selected the common cold as their reason for visiting. All 408 patients responded to the questionnaire. Main outcome measures First, factors representing illness experiences in patients with common cold symptoms were explored. Second, variables with significant relative risk ratio (RRR) were used to diagnose common cold, influenza or other diseases. Results A total of 171 codes were identified from the responses of 408 patients, which were visually mapped to show their frequencies and occurrence in the same person according to their final diagnoses. Of the 171 codes, 22 found in over nine patients represented the variables for the three independent final diagnoses. The adjusted final model revealed that (1) ‘worry about influenza infection’, ‘want influenza test’ and ‘transmission from a colleague at school or workplace’ predicted the influenza rather than the common cold, when other predicting variables were constant (RRR, 6.20 p<0.001; RRR, 26.1 p<0.01; and RRR, 4.69 p<0.05, respectively); (2) ‘want further examination’ predicted other diseases (RRR, 2.84 p<0.05); and (3) the combination of ‘worry about influenza infection’ and ‘want influenza test’, which predicted the opposite diagnosis: the common cold rather than influenza (RRR, 0.01 p<0.001). Conclusion These findings provide useful information on how illness experiences before consultation can predict final diagnoses for patients with common cold symptoms.