179 Classifying study participants in clinical trials an independent technical chairman and keeping a research log. This process and its detailed reporting further contributed to consistency. A limitation of the study is that the diagnosis of the expert panel was considered the “true” diagnosis. When assessing disagreement cases in a qualitative matter, we observed several “overdiagnoses” of an URTI by the students and residents. However, an alternative interpretation might be that there is underdiagnosis of these URTIs by experts. Furthermore, the results of the validity of this study cannot be generalised to other conditions and settings. The participating medical students, residents and medical specialists were all trained in a Dutch healthcare setting. Prevalence and degree of exposure to the spectrum of medical conditions presenting at the ED likely influenced their assessment of the cases. However, our structure was designed to include general high-volume diseases and addresses a common problem: how to classify patients in large scale clinical trials? This methodology to classify patients could be used in other settings, after development of a local guideline with diagnostic criteria and an internal validation of these guidelines. In conclusion, we developed a valid and efficient method to classify the diagnosis of patients suspected of pulmonary disease at the ED, using the expertise of medical students, residents, and medical specialists. We hope that the description of the methods used in our study will inspire other study authors to be equally informative in terms of their description of methods. We believe that the structured approach presented here offers a viable option for classifying study participants in large-scale clinical trials. 8
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