Clinical reasoning is the ability to gather and interpret patients’ information to make diagnostic and treatment decisions. Despite knowing that the development of clinical reasoning is different for each student, we currently teach all students in a logic of “one size fits all”, contributing to frustration and vulnerability among trainees and patients. We want to change it.
Technology advancements, especially Artificial Intelligence, have created opportunities to personalize learning trajectories while it is, simultaneously, reshaping the way medical doctors reason. By connecting teachers, educationalists, tech experts and researchers, we want move clinical reasoning education towards:
As individuals, we want well-trained health care professionals to support us during sensitive moments when we or our loved ones face illness. As a society, we want this to happen at an affordable cost. Connecting research, education, and technology can help us increase efficiency while maintaining high standards of training and nurturing the joy of caring.
Clinical reasoning is vital for patient safety, as it drives accurate diagnoses and effective treatment plans. While we have extensive knowledge about how clinical reasoning develops and have tested strategies to teach it, this evidence isn't fully applied in educational practices. Promising methods like self-explanation and reflective practice are not consistently integrated into training programs. To enhance patient safety, we must bridge this gap by more effectively incorporating these evidence-based strategies into clinical education, ensuring healthcare professionals are better equipped for real-world decision-making. In the group’s monthly meetings, lecturers, academic teachers, professors and researchers discuss the teaching of clinical reasoning with a focus on evidence-informed practice.
The group also produces evidence on best strategies to teach clinical reasoning, for example, how to facilitate learning of information relevant to clinical reasoning and to prevent medical error.
The teaching of clinical reasoning must consider that training healthcare professionals is a complex and costly process, requiring significant time and resources. This challenge is further intensified by the current workforce crisis, where many, after years of education, are abandoning their healthcare careers. This not only worsens the shortage of skilled workers but also raises concerns about the sustainability of healthcare systems. By carefully applying evidence-based technological tools, we can make the clinical reasoning training process more efficient, reducing costs while maintaining high standards of education. In doing so, we can attract more students to the field, ensuring they are well-prepared and motivated to continue their careers in healthcare in the long run.
The group has studied and implemented the teaching of clinical reasoning in on-line environments. One of the outcomes is a very successful approach to teach clinical reasoning in the context of emergency medicine. Currently, all research projects we are conducting in clinical reasoning are mediated by technology. We are exploring, for example, the automation of students’ assessment of illness scripts, the use of podcasts to facilitate learning and chatbots-mediated adaptive learning strategies.
We collaborate with iMERR, Institute for Medical Education Research Rotterdam, Erasmus MC.
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Antonius Deusinglann 1
9713 AV Groningen
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Antonius Deusinglann 1
building 3219, room 0293
9713 AV Groningen
