Build a living care map with fictional records
Practice turning scattered information into a reviewable map of goals, context, uncertainties and follow-through.
Use Maya’s teaching packet
Maya is an entirely fictional 54-year-old postmenopausal patient. Her goals are energy for work, time for her mother and staying strong. Use the downloadable S1–S8 packet for the first draft; add S9 only after you have reviewed it. No real patient information is needed for this exercise.
Ask for one HTML file that opens in a browser. Put the patient’s goals first, then a dated source timeline, relevant context, unresolved questions and a proposed follow-through table. Give every factual statement a source ID. Label inference separately from documented fact; leave clinical decisions for review.
Preserve the contradictions
The medication list includes atorvastatin, while a later message says Maya stopped it. Keep that discrepancy open for reconciliation. Four overnight CGM readings below 70 are unconfirmed sensor readings, not established hypoglycemia. Nine recorded nights and five missing nights are incomplete wearable data, not proof of five sleepless nights.
S9 adds caregiving four nights a week and charging the watch on some nights. This can change the feasibility of a plan and explain some missing data. It does not settle the medication question, the low readings or the cause of fatigue.
Review the file and request one change
Open the generated file, compare it with the packet and ask for one concrete revision. For each clinician-approved next step, identify an owner and review date. Keep the draft and approved version distinguishable.
This is a prepared case walkthrough. It does not connect to an EHR, perform clinical monitoring or require a live AI demonstration. Before adapting it to clinical use, evaluate the entire data path and test the intended integration.