Diabetes Chronic Care Enrollment Checklist | APCM & A1C Monitoring

Confirm the patient has two or more chronic conditions, such as Diabetes and Hypertension or CKD, expected to last at least 12 months.

Document the most recent A1C level within the last 12 months to establish a clinical baseline for the care plan.

Secure and document verbal or written consent for APCM services, explaining cost-sharing and the ability to terminate at any time.

Ensure the patient is actively enrolled in Medicare Part B or a Medicare Advantage plan to qualify for reimbursement.

Screen for existing diabetic complications such as neuropathy, retinopathy, or nephropathy to prioritize care coordination.

Evaluate Social Determinants of Health, including access to healthy food and transportation for lab appointments.

Define individualized A1C goals based on patient age, duration of diabetes, and presence of cardiovascular disease.

For insulin-dependent patients, document the specific titration schedule and hypoglycemia emergency protocols.

Coordinate dates for annual dilated eye exams, monofilament foot exams, and urine albumin-to-creatinine ratio tests.

Set a schedule for reviewing Continuous Glucose Monitor (CGM) data and adjusting medications based on Time in Range (TIR).

Incorporate medical nutrition therapy (MNT) goals, focusing on carbohydrate counting or the plate method.

List all diabetic medications (GLP-1, SGLT2 inhibitors, metformin) and identify potential barriers to adherence.

Set up automated AI calls to perform monthly care plan reviews and assess for any new symptoms or barriers to care.

Deploy AI voice assistants to remind patients of upcoming A1C and lipid panel blood work to ensure data continuity.

Program AI check-ins to specifically ask about episodes of dizziness or sweating that may indicate poor glycemic control.

Use AI to call patients 5 days before their insulin or oral meds run out to facilitate timely pharmacy refills.

Schedule AI-driven educational snippets to remind patients of daily foot inspections and proper footwear.

Enable AI to collect and transcribe verbal glucose readings from patients who do not use digital syncing devices.