Orchestrators / Provider / AI Lost to Follow Up

Provider

AI Lost to Follow Up

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Section 01

Problem

Thousands of patients are overdue for care, and no one has the capacity to bring them back.

Every system carries these lists: the repeat CT for a lung nodule, the colonoscopy after a positive stool test, the cardiac stress test, the behavioral health referral. Completion rates vary by test, but many sit well below half. Closing the loop on an ordered test is a recognized patient-safety obligation, and it is one many organizations are quietly failing.

These patients are easy to identify and hard to reach. Bringing one back takes repeated attempts over months and a conversation that finds the actual barrier and removes it. Staffed with people, that has never been affordable at the size of the list. So the lists sit.

Both sides lose. The patient waits months or years for a diagnosis from a study that was already ordered — among the leading causes of preventable harm and malpractice exposure. The system forgoes revenue on care it already ordered and interpreted.

Capacity was the only thing in the way. In one lung screening program, 5,000 overdue patients were called, 49% accepted a live transfer to scheduling, and roughly 50 cancers were found.

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Section 02

Use Cases

  • Lung Nodule Follow-Up CT
  • Cardiac Stress
  • Sleep Study
  • FIT to Colo
  • LDCT Lung Screen
  • Cardio Referral
  • BH Referral
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Section 03

Features

Features:

  • Recall outreach with in-call scheduling (Advanced Scheduling 99.44%) and Specialty Appointment Scheduling supervisor model.
  • Open-recommendation tracking across long intervals with Multi-call Memory, so attempt eleven doesn’t sound like attempt one.
  • Get Callback Info handling for patients who have gone quiet.
  • Motivational Interviewing supervisor model to surface the actual barrier.
  • Trust Building supervisor model for AI hesitancy (96.2% vs. 72.2% for the best frontier model) and for patients carrying a bad past experience.
  • Health Literacy supervisor model to explain why the follow-up matters without causing alarm.
  • Checklist-driven eligibility and prep conversations at 99.3% intake accuracy.
  • Post-procedure result delivery per disclosure rules with guideline-based surveillance intervals.
  • Tangent and Emotional Safety supervisor models, benchmarked on HEART.
  • Mid-call language switching at 98.8% to reach the populations recall letters never reach.
  • Structured EHR write-back so the closed loop is documented.

Potential features:

  • FIT-to-colonoscopy conversion counseling.
  • Transportation coordination.
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Section 04

ROI

SAMPLE USE CASE: LDCT Lung Screen (lost to follow-up) → ROI: ~$14.3M downstream revenue per $1B NPR
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Section 05

Demo Calls

CT Scan (Patient Reluctance) 2.mp3
Patient Education (Colo Screen Kit)