Building Clinical Reasoning Skills

Research shows that physicians who are able to provide a semantically rich summarization of a case are much more accurate in making a clinical diagnosis.

Teaching clinical reasoning is one of Aquifer’s foremost educational goals. In following a virtual patient from presentation to outcome, students hone their skills in recognizing and interpreting clinical signs and symptoms. Each of our cases follows a structure that highlights the components of clinical reasoning––from gathering knowledge of the patient’s history and risk factors to making an informed opinion of the patient’s clinical status to developing a differential diagnosis, selecting diagnostic studies, and implementing a management plan. Through active engagement your learners can use deliberate practice to cultivate their clinical reasoning skills.

How is clinical reasoning learned?

Contribution by Valerie Lang, MD, MHE

Medical knowledge is essential, but insufficient, for effective clinical reasoning. Students need to organize their knowledge in a way that allows them to identify and solve clinical problems. (Norman, Charlin, et al.) The “dual-processing” model of clinical reasoning identifies two processes: Type 1 (fast, “instinctive,” heuristic) and Type 2 (slow, analytical). (Norman) There is much debate over which type is more error-prone (Norman, Eva, Croskerry), but it is generally acknowledged that experts use Type 1 reasoning when faced with problems in their field, but switch to Type 2 reasoning when faced with unfamiliar problems. Novices tend to use Type 2 but tend toward Type 1 reasoning as they develop experience. (Norman, Eva, et al.)

To develop skills in clinical reasoning, students need deliberate practice applying their knowledge to clinical cases (Eva, Norman), either virtual (e.g. paper, on-line, standardized patient) or real (e.g., patient care), and have the opportunity to reflect on the diagnostic and treatment decisions they make. Real clinical experience is essential, but idiosyncratic. Students may not encounter patients with the ideal breadth of conditions or at a stage of their illness that is most helpful for developing reasoning skills. With the increase in hand-offs in inpatient settings, students are more likely to meet their patients after a diagnosis has already been established. The lost opportunity to evaluate “fresh” patients is associated with decreased learning. (Lang)

How do Aquifer cases help students learn clinical reasoning?

Aquifer cases provide students with the opportunity for deliberate practice in clinical reasoning. The context in which clinical reasoning is learned is important. Students are more likely to correctly solve a case if it is presented in the same context in which it was learned. (Durning, et al.) The real clinical environment is highly complex and data-heavy, and can cognitively overload the novice learner. (Merrienboer) By providing an authentic clinical and social context for cases, while reducing the amount of cognitive overload, Aquifer virtual patient cases give students a robust opportunity to develop their clinical reasoning skills in a setting that is specifically designed for their level.

Most of the Aquifer virtual patients present with an undifferentiated complaint or lab abnormality, such as cough or anemia. Students practice identifying the key findings from the history, physical exam, and test data. They synthesize the case into a concise summary statement, identify a differential diagnosis, and learn the relative diagnostic value of each of the key findings. They make decisions about what tests and treatments are important for identifying and resolving the patient’s problem. At each step, they must commit to a decision, then receive feedback and explanations about the correct and incorrect responses. This provides practice in a safe, but interactive environment. It gives students a framework to approach real patients with similar problems in a more sophisticated manner. (Edelbring, et al.)

Norman G. Research in clinical reasoning: past history and current trends. Medical Education 2005;39:418-27.

Liaison Committee on Medical Education. Standards for Accreditation of Medical Education Programs Leading to the M.D. Degree. May 2012.

Charlin B, Boshuizen HP, Custers EJ, Feltovich PJ. Scripts and clinical reasoning. Medical Education 2007;41:1178-84.

Boshuizen HP, Schmidt HG. The development of clinical reasoning expertise. Clinical Reasoning in the Health Professions2008:113-21.

Norman G. Dual processing and diagnostic errors. Advances in Health Sciences Education: Theory and Practice 2009;14 Suppl 1:37-49.

Norman GR, Eva KW. Diagnostic error and clinical reasoning. Medical Education 2010;44:94-100.

Croskerry P. Clinical cognition and diagnostic error: applications of a dual process model of reasoning. Advances in Health Sciences Education 2009;14:27-35.

Norman G, Young M, Brooks L. Non-analytical models of clinical reasoning: the role of experience. Medical Education 2007;41:1140-5.

Lang VJ, Mooney CJ, O’Connor AB, Bordley DR, Lurie SJ. Association between hand-off patients and subject exam performance in medicine clerkship students. Journal of General Internal Medicine 2009;24:1018-22.

Edelbring S, Dastmalchi M, Hult H, Lundberg IE, Dahlgren LO. Experiencing virtual patients in clinical learning: a phenomenological study. Advances in Health Sciences Education: Theory and Practice 2011;16:331-45.

Koens F, Mann KV, Custers EJ, Ten Cate OT. Analysing the concept of context in medical education. Medical Education2005;39:1243-9.

van Merrienboer JJ, Sweller J. Cognitive load theory in health professional education: design principles and strategies. Medical Education 2010;44:85-93.