Clinical Reasoning Education

Robert Diaz — T2DM, Admitted for Pneumonia, Glucose 387 on Morning Labs, On Insul...

Clinical reasoning simulation for healthcare students and educators

Endocrinology Intermediate Nursing

Practice This Case

Work through the full clinical encounter with AI patient and attending. Free, no signup required.

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About This Case

This clinical reasoning case presents a patient with robert diaz / t2dm / admitted for pneumonia / glucose 387 on morning labs / on insulin drip in a endocrinology context. Learners work through a structured 10-phase simulation covering initial differential, history-taking, physical examination, labs and imaging, and management planning.

"Robert was admitted for pneumonia. This morning his glucose is 387 on an insulin drip protocol. He is eating a full diet. His home medications include glipizide. The physician orders sliding scale insulin in addition to the drip. What is the most dangerous element of this order — and what does your inpatient diabetes management education need to cover before discharge?"

How the Simulation Works

  1. Read the patient presentation and form your initial differential diagnosis
  2. Interview the AI patient to gather history and explore your hypotheses
  3. Perform a focused physical examination based on your differential
  4. Order appropriate labs and imaging, then interpret the results
  5. Revise your diagnosis and develop a management plan
  6. Receive personalized teaching feedback from your AI attending, Dr. Patel

What You'll Learn

This case builds skills in systematic clinical reasoning, hypothesis-driven history-taking, appropriate test ordering, and evidence-based management. It is designed for Nursing students and practicing clinicians seeking to sharpen diagnostic thinking in endocrinology.

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About ReasonDx

ReasonDx is an AI-powered clinical reasoning education platform developed by Dr. Lauren Fine, MD, FAAAAI, Associate Professor and Assistant Dean of Clinical Skills Education at NSU Dr. Kiran C. Patel College of Allopathic Medicine. The platform features 394 simulation cases across 10 health professions, designed to train the cognitive processes underlying accurate diagnosis.