Other Publications

Education Columns

Teaching About Patients With Complexity

Justin Osborn, MD, and Allison Cole, MD, Department of Family Medicine, University of Washington

Complexity in medicine can exist in an individual patient and in the delivery of health care in our complicated systems. When the standard and routine approach to diagnosing and caring for a patient doesn’t work, by definition, that patient is complex.1 Other individual factors can be inadequate social support, psychological issues, financial strain, difficulty making behavioral changes, and cultural reasons. System complexity includes the vast array of expanding medical knowledge, limitless diagnostic and treatment options, limitless variations in insurance coverage or lack thereof, and fractured delivery systems. All of these variables impact patient care.

Learning standard and routine medical care alone can overwhelm medical students and residents. Imagine how a learner feels when faced with the added uncertainty of complexity.2 Medical schools and residencies usually teach the diagnosis and treatment of conditions without teaching skills in identifying and managing complexity in an individual with the condition. To provide the best patient care and outcomes, issues that make a patient complex need to be defined and skills taught in the management of complexity.3-7 The Minnesota Complexity Assessment Method or MCAM is a tool for defining patient and system complexity.8

The Minnesota Complexity Assessment Method divides complexity into five domains. These domains provide a framework and common language to assess and discuss complex patients.8-9

The five domains are:

  • Illness (diagnostic uncertainty and functional impairment due to symptom severity)
  • Readiness to engage (a patient’s distress, distraction, and readiness to engage in treatment or behavior change)
  • Social (assessment of the patient’s social support network, safety, and stability)
  • Health system (organization and connection of care and the provider-patient relationship)
  • Resources for care (shared language with providers and adequacy of insurance coverage)

There is now an updated version of the MCAM after collaboration between clinicians and researchers at the University of Minnesota Department of Family Medicine and others in Scotland. The updated version is known as the Patient Centered Assessment Method or PCAM, and the developers are dedicated to keeping this tool available online for free.10

Medical students and residents interact regularly with patients who have complexity based on the above domains. The MCAM provides a map to identify the domains that make a person more complex then the straightforward condition or standard diagnosis. It humanizes the approach to look at the person, not the condition.

Complexity skills may also help prevent physician burnout by creating an understanding that fosters resiliency and improves care. Rather then label patients as “difficult” or “noncompliant,” medical students and residents can learn skills to assess areas of complexity. Then they can help address the real barriers a patient faces. Teaching skills in complexity earlier in their learning experience should improve coping and increase empathy. Having an improved approach and positive perception of one’s skills in dealing with complex care has a direct link to job satisfaction in practicing family physicians.11

Residents feel less overwhelmed with complex care after integrated use of the MCAM. They are introduced to the MCAM as interns and then spend a month in the second year dedicated to learning skills in complex care. Then they use the MCAM in monthly patient care clinical pod meetings to get input from interdisciplinary team members (nutritionist, social worker, nurse, medical assistants, front desk staff, and providers). They feel more confident, more empathic, and more likely to continue caring for patients with complexity in the future.12

Care management of chronic conditions is an area full of patients with complexity. Health care delivery systems and reimbursement are shifting to population management and improved patient outcomes. Having skills in helping patients with complexity reach healthier outcomes will be required.13,14 The MCAM is a model and tool that could help start preparing medical students and residents for the future.

References


1. Peek CJ, Baird MA, Coleman E. Primary care for patient complexity, not only disease. Families, Systems, & Health 2009;27(4):287-302.
2. Evans L, Trotter DR, Jones BG, et al. Epistemology and uncertainty: a follow-up study with third-year medical students. Fam Med 2012;44(1):14-21.
3. Martimianakis MA, Albert M. Confronting complexity: medical education, social theory and the "fate of our times." Med Educ 2013;47(1):3-5.
4. Dornan T, McKendree J, Robbe IJ. Medical education in an age of complexity, uncertainty and reflection. A coda to the Flexner centenary. Med Educ 2011;45(1):2-6.
5. McGaghie WC. Implementation science: addressing complexity in medical education. Med Teach 2011;33(2):97-8.
6. Mennin S. Complexity and health professions education: a basic glossary. J Eval Clin Pract 2010;16(4):838-40.
7. Mennin S. Complexity and health professions education. J Eval Clin Pract 2010;16(4):835-7.
8. Minnesota Complexity Assessment Method or MCAM form
http://www.mpho.org/resource/d/35993/MinnesotaComplexity AssessmentMethodBairdHandout.
9. Stiefel FC, Huyse FJ, Sollner W, et al. Operationalizing integrated care on a clinical level: The INTERMED project. Med Clin North Am 2006;90(4):713-58. doi: 10.1016/j.mcna.2006.05.006.
10. Link to the latest form (Patient Centered Assessment Method or PCAM) from the University of Minnesota. http://www.pcamonline.org.
11. Katerndahl D, Parchman M, Wood R. Perceived complexity of care, perceived autonomy, and career satisfaction among primary care physicians. J Am Board Fam Med 2009;22(1):24-33.
12. Osborn J, Charles C, Overstreet F, Ross V, Hale S. Training residents to care for complex patients: design, evaluation, and next steps. Presented at the 2011 Society of Teachers of Family Medicine Annual Spring Conference, New Orleans.
13. Sevick M, Trauth J, Ling B, et al. Patients with complex chronic diseases: perspectives on supporting self-management. J Gen Intern Med 2007;22(Suppl 3):438-44.
14. Borgermans L, De Maeseneer J, Wollersheim H, et al. A theoretical lens for revealing the complexity of chronic care. Perspectives in Biology and Medicine 2013;56(2):289-99.

Ask a Question
AI Chatbot Tips

Tips for Using STFM's AI Assistant

STFM's AI Assistant is designed to help you find information and answers about Family Medicine education. While it's a powerful tool, getting the best results depends on how you phrase your questions. Here's how to make the most of your interactions:

1. Avoid Ambiguous Language

Be Clear and Specific: Use precise terms and avoid vague words like "it" or "that" without clear references.

Example:
Instead of: "Can you help me with that?"
Try: "Can you help me update our Family Medicine clerkship curriculum?"
Why this is important: Ambiguous language can confuse the AI, leading to irrelevant or unclear responses. Clear references help the chatbot understand exactly what you're asking.

2. Use Specific Terms

Identify the Subject Clearly: Clearly state the subject or area you need information about.

Example:
Instead of: "What resources does STFM provide?"
Try: "I'm a new program coordinator for a Family Medicine clerkship. What STFM resources are available to help me design or update clerkship curricula?"
Why this is better: Providing details about your role ("program coordinator") and your goal ("design or update clerkship curricula") gives the chatbot enough context to offer more targeted information.

3. Don't Assume the AI Knows Everything

Provide Necessary Details:The STFM AI Assistant has been trained on STFM's business and resources. The AI can only use the information you provide or that it has been trained on.

Example:
Instead of: "How can I improve my program?"
Try: "As a program coordinator for a Family Medicine clerkship, what resources does STFM provide to help me improve student engagement and learning outcomes?"
Why this is important: Including relevant details helps the AI understand your specific situation, leading to more accurate and useful responses.

4. Reset if You Change Topics

Clear Chat History When Switching Topics:

If you move to a completely new topic and the chatbot doesn't recognize the change, click the Clear Chat History button and restate your question.
Note: Clearing your chat history removes all previous context from the chatbot's memory.
Why this is important: Resetting ensures the AI does not carry over irrelevant information, which could lead to confusion or inaccurate answers.

5. Provide Enough Context

Include Background Information: The more context you provide, the better the chatbot can understand and respond to your question.

Example:
Instead of: "What are the best practices?"
Try: "In the context of Family Medicine education, what are the best practices for integrating clinical simulations into the curriculum?"
Why this is important: Specific goals, constraints, or preferences allow the AI to tailor its responses to your unique needs.

6. Ask One Question at a Time

Break Down Complex Queries: If you have multiple questions, ask them separately.

Example:
Instead of: "What are the requirements for faculty development, how do I register for conferences, and what grants are available?"
Try: Start with "What are the faculty development requirements for Family Medicine educators?" Then follow up with your other questions after receiving the response.
Why this is important: This approach ensures each question gets full attention and a complete answer.

Examples of Good vs. Bad Prompts

Bad Prompt

"What type of membership is best for me?"

Why it's bad: The AI Chat Assistant has no information about your background or needs.

Good Prompt

"I'm the chair of the Department of Family Medicine at a major university, and I plan to retire next year. I'd like to stay involved with Family Medicine education. What type of membership is best for me?"

Why it's good: The AI Chat Assistant knows your role, your future plans, and your interest in staying involved, enabling it to provide more relevant advice.

Double Check Important Information

While the AI Chat Assistant is a helpful tool, it can still produce inaccurate or incomplete responses. Always verify critical information with reliable sources or colleagues before taking action.

Technical Limitations

The Chat Assistant:

  • Cannot access external websites or open links
  • Cannot process or view images
  • Cannot make changes to STFM systems or process transactions
  • Cannot access real-time information (like your STFM Member Profile information)

STFM AI Assistant
Disclaimer: The STFM Assistant can make mistakes. Check important information.