RESUMO
The Script Concordance Tests (SCTs) are an examination modality introduced by decree in the French National Ranking Exam for medical students in 2024. Their objective is to evaluate clinical reasoning in situations of uncertainty. In practice, SCTs assess the impact of new information on the probability of a hypothesis formulated a priori based on an authentic clinical scenario. This approach resembles probabilistic (or Bayesian) reasoning. Due to the uncertainty associated with the explored clinical situation, SCTs do not compare the student's response to an expected one in a theoretical knowledge reference. Instead, the distribution of responses from a panel of experienced physicians is used to establish the question's scoring scale. Literature data suggest that physicians, even experienced ones, like most humans, often exhibit biased intuitive probabilistic reasoning. These biases raise questions about the relevance of using expert panel responses as scoring scales for SCTs.
RESUMO
Although paper-based transmission of medical information might seem outdated, it has proven efficient, and remains structurally safe from massive data leaks. As part of the ICIPEMIR project for improving medical imaging report, we explored the idea of structured data storage within a medical report, by embedding the data themselves in a QR-Code (and no URL-to-the-data). Three different datasets from ICIPEMIR were serialized, then encoded in a QR-Code. We compared 4 compression algorithms to reduce file size before QR-Encoding. YAML was the most concise format (character sparing), and allowed for embedding of a 2633-character serialized file within a QR-Code. The best compression rate was obtained with gzip, with a compression ratio of 2.32 in 15.7ms. Data were easily extracted and decompressed from a digital QR-Code using a simple command line. YAML file was also successfully recovered from the printed QR-Code with both Android and iOS smartphone. Minimal detected size was 3*3cm.
