Clinical Reasoning Education

Family Refusing Recommended Treatment — Patient Cannot Speak, Surrogate Decision

Clinical reasoning simulation for healthcare students and educators

General Medicine Urgent 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 family refusing recommended treatment / patient cannot speak / surrogate decision in a general medicine context. Learners work through a structured 10-phase simulation covering initial differential, history-taking, physical examination, labs and imaging, and management planning.

"Your 88yo patient with severe dementia has aspiration pneumonia. The palliative care team recommended comfort care. The patient's son, who holds healthcare proxy, insists on full aggressive treatment including intubation if needed. The patient has no advance directive. What is the ethical framework — and what is your nursing role versus the physician's role in this conversation?"

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 general medicine.

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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.