Workflow GuideNeurology

Neurology Chronic Care Risk Stratification Workflow Guide

Optimize neurology patient outcomes with AI-driven chronic care risk stratification for Alzheimer's, Parkinson's, and Epilepsy management.

Effective risk stratification in neurology ensures that high-acuity patients, such as those with advancing dementia or refractory epilepsy, receive proactive outreach. By leveraging AI to analyze patient data and caregiver feedback, practices can prioritize interventions, improve APCM enrollment, and reduce emergency department visits through structured symptom monitoring and early crisis detec...

The Challenge

Neurology practices often struggle to identify which patients are at highest risk for falls, status epilepticus, or caregiver burnout, leading to reactive care models and significant lost revenue from missed APCM opportunities.

Step-by-Step Workflow

1

Categorize Patients by Diagnostic Complexity

Filter your EHR for high-value ICD-10 codes including G30.9 (Alzheimer's), G20 (Parkinson's), and G40 (Epilepsy). AI call systems can then segment these groups for targeted symptom surveys.

Best Practices
  • Prioritize patients on more than three neurological medications
  • Include patients with recent 'off' period complaints
Common Pitfalls
  • Overlooking patients with 'mild' cognitive impairment who are at high risk of rapid decline
2

Automate Caregiver Stability Screenings

Use AI-powered phone automation to conduct regular caregiver burden assessments. Since many neurology patients cannot self-advocate, the caregiver's health is a primary indicator of patient risk.

Best Practices
  • Ask specific questions about caregiver sleep quality and respite access
  • Flag households where the primary caregiver is also over age 75
Common Pitfalls
  • Assuming every patient has a 24/7 support system in place
3

Monitor Medication Adherence and Titration

For Parkinson's and Epilepsy, monitor adherence to complex dosing schedules. AI logs missed doses in real-time, flagging patients for immediate clinical review before breakthrough symptoms occur.

Best Practices
  • Focus on 'off' periods for Parkinson's medication timing
  • Automate check-ins for the first 30 days of a new AED
Common Pitfalls
  • Relying solely on pharmacy refill data which doesn't capture actual ingestion
4

Analyze Fall Frequency and Mobility Trends

Implement automated mobility check-ins for MS and Parkinson's patients. Identifying a pattern of near-misses or minor falls allows for early PT/OT intervention and home safety adjustments.

Best Practices
  • Use standardized questions regarding recent stumbles or near-falls
  • Trigger a risk alert if a patient reports more than one fall in 30 days
Common Pitfalls
  • Ignoring minor trips that often precede major hip fractures
5

Quantify Neuropsychiatric and Behavioral Changes

Screen for rapid cognitive decline or new behavioral symptoms in dementia patients. AI-driven voice analysis can help detect subtle changes in patient or caregiver stress levels.

Best Practices
  • Monitor for new-onset wandering or sundowning behaviors
  • Use validated scales like the PHQ-9 for MS-related depression
Common Pitfalls
  • Dismissing behavioral changes as 'normal' progression without clinical review
6

Integrate Social Determinants of Health (SDOH)

Factor in transportation barriers and pharmacy access, which often prevent neurology patients from attending follow-ups or receiving disease-modifying therapies (DMTs).

Best Practices
  • Check for proximity to specialized infusion centers for MS patients
  • Screen for food insecurity which impacts medication metabolism
Common Pitfalls
  • Failing to document SDOH barriers in the formal APCM care plan

Expected Outcomes

1

Increased APCM enrollment by identifying eligible high-risk candidates

2

Reduction in avoidable ER visits for epilepsy and fall-related injuries

3

Enhanced caregiver satisfaction through proactive support and check-ins

4

Improved medication titration accuracy for Parkinson's patients

5

Lowered administrative burden via automated risk data collection

Frequently Asked Questions

AI call systems automatically transcribe and summarize patient/caregiver interactions, ensuring all 20 minutes of required monthly care management are documented with clinical specificity for billing.

Yes, the automated system can verify and document caregiver consent for communication, which is a critical regulatory requirement in dementia and Alzheimer's care.

By identifying low-risk patients who can be managed via APCM and telehealth, practices free up in-office slots for high-risk urgent referrals and new patient evaluations.

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Neurology Chronic Care Risk Stratification Workflow Guide | Tile Health