Case Study 2: Fatigue and Sleep Disturbance
This is the case study you are required to use for your Week 9 Use of AI in Evidence-Based Plan Management assignment.
Chief Complaint
“I can’t sleep and feel exhausted all the time.”
History of Present Illness
A 45-year-old male reports 6 months of fatigue, poor concentration, and difficulty sleeping. He feels “tired but wired,” often lying awake for hours. His appetite has decreased, and he has lost 8 pounds unintentionally. He describes feeling “hopeless” and states that work stress feels overwhelming.
He denies suicidal ideation, hallucinations, or substance use.
Past Medical History
Hypertension, well controlled on lisinopril
Family History
Father had depression in his 50s
Social History
Divorced
Works in IT
Lives alone
Drinks 1–2 beers on weekends
No tobacco or drug use
Limited exercise
Review of Systems
Positive: Low mood, insomnia, poor appetite, fatigue, decreased motivation
Negative: Chest pain, shortness of breath, suicidal thoughts, hallucinations
Objective Findings
BP: 122/80 mmHg
HR: 84 bpm
Afebrile
Appearance: Mildly disheveled, flat affect, minimal eye contact
Speech: Soft and slowed
Affect: Depressed and congruent with mood
Cognitive: Alert and oriented ×3; memory intact
PHQ-9: 19
GAD-7: 6
DSM-5 Diagnostic Criteria Screening
The patient meets five or more criteria for Major Depressive Disorder, including depressed mood, anhedonia, fatigue, insomnia, weight loss, poor concentration, and hopelessness for longer than two weeks.
Week 9 Assignment: Use of AI in Evidence-Based Plan Management
This assignment is designed to strengthen your clinical reasoning while exploring the ethical and responsible use of artificial intelligence (AI) in advanced practice nursing.
For this assignment, you will use an AI tool, such as ChatGPT, Grok, or another AI platform of your choice, as a learning partner to assist you in developing an evidence-based management plan.
🚨 Required Case Study
All students must use Case Study 2: Fatigue and Sleep Disturbance, provided below, for the Week 9 AI assignment.
Do not select a different case study. Your differential diagnoses, final diagnosis, problem statement, evidence-based management plan, AI prompts and outputs, and reflection should all be based on Case Study 2 provided in this announcement.
Your completed assignment should include:
3–5 differential diagnoses with supporting rationale
A final diagnosis supported by subjective, objective, and pertinent history findings
A clear problem statement
An evidence-based management plan, including:
Diagnostics
Medications with complete prescriptions
Referrals and/or consultations
Patient education
Follow-up recommendations
A reflection on the use of AI, including its accuracy, usefulness, and limitations
An appendix containing your AI prompts and outputs
⚠️ Important AI Assignment Reminders
AI is required for this assignment.
AI should be used as a learning partner, not as a replacement for your clinical judgment.
Every AI-generated recommendation must be verified using current evidence-based clinical practice guidelines and your own clinical reasoning.
Support your work with 3–5 peer-reviewed scholarly references published within the last five years.
Use the provided assignment template and carefully review the grading rubric before beginning.
You must use Case Study 2: Fatigue and Sleep Disturbance provided below.
Submit your completed assignment by Day 7 of Week 9.
Remember, the goal is not simply to use AI. You are expected to critically evaluate AI-generated recommendations, validate them against current evidence-based guidelines, identify potential limitations or inaccuracies, and apply your own clinical judgment to develop a safe and comprehensive management plan.
This assignment uses a case (45-year-old male with fatigue, sleep disturbance, low mood, weight loss) to build an evidence-based management plan with AI assistance that you then verify against clinical guidelines and your own judgment. The key is using AI as a tool while owning the clinical reasoning.
Key takeaways
- Use the case to generate differentials, then narrow to a working diagnosis.
- The presentation suggests major depressive disorder — verify against criteria.
- Use AI to assist, but verify everything against current guidelines.
- Build a comprehensive, evidence-based management plan.
- Address AI’s accuracy, limitations, and ethical use.
Reason through the case
From the presentation — 6 months of fatigue, insomnia, poor concentration, decreased appetite, 8-lb unintentional weight loss, hopelessness, work stress, no SI/psychosis/substance use — generate a differential (major depressive disorder, generalized anxiety, a sleep disorder, medical causes like thyroid) and narrow to a working diagnosis. The picture fits MDD; confirm against DSM-5-TR criteria.
Use AI, then verify
Describe using an AI tool to help generate differentials and plan elements — then verify each against current clinical practice guidelines and your own clinical judgment. Flag anything the AI got wrong or oversimplified.
Build the management plan
Create a comprehensive plan: diagnostics (labs to rule out medical causes), evidence-based treatment (psychotherapy, pharmacotherapy as indicated), safety screening, follow-up, and patient education.
Address AI ethics
Discuss AI’s accuracy, limitations, privacy, and the clinician’s responsibility to verify. Document in APA with citations.
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