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Transform sleep-disordered breathing care with intelligent automation guiding patients from referral through diagnostic polysomnography, device titration, mask fitting, and continuous adherence monitoring — ensuring every patient achieves therapeutic compliance.
AI-driven patient orchestration from sleep study referral through CPAP optimization to long-term adherence
71%
Improvement in 90-day CPAP adherence rates
2.6min
Average referral-to-verification processing time
91%
First-call resolution for CPAP troubleshooting
98.8%
CMS compliance window monitoring coverage
Sleep medicine practices face a chronic adherence crisis. Referrals pile up waiting for sleep study slots, patients abandon CPAP therapy within weeks, mask fitting issues go unresolved, and CMS compliance windows pass without intervention. The result: untreated obstructive sleep apnea, cardiovascular risk escalation, and DME revenue loss from non-compliant patients.
Sleep study scheduling backlogs of 4-8 weeks cause patients to disengage before ever receiving a diagnosis
CPAP abandonment rates exceed 40% within the first month, often due to unresolved mask fit or pressure comfort issues
CMS requires documented CPAP usage of 4+ hours on 70% of nights within the first 90 days — practices miss intervention windows
Mask fitting issues create a cascade of complaints that overwhelm clinical staff with repetitive troubleshooting calls
Home sleep test data arrives in varied formats requiring manual interpretation and re-entry into practice systems
Coordination between sleep labs, DME suppliers, and insurance companies delays therapy initiation by weeks
Every workflow purpose-built for sleep-disordered breathing operations.
Referral intake with OCR extraction of Epworth Sleepiness Scale scores, BMI data, and prior sleep study results — patient matching and insurance verification in under 3 minutes
AI-driven scheduling matching patients to optimal sleep study slots based on clinical urgency, AHI severity indicators, and home vs. in-lab testing appropriateness
Smart waitlist that fills sleep study cancellations within minutes via automated SMS and voice outreach, prioritizing patients with high pre-test probability scores
Pre-study prep automation — sleep diary distribution, medication hold instructions, sleep hygiene guidelines, and equipment orientation with compliance confirmation
Multi-channel patient engagement: study night reminders, CPAP usage encouragement, mask troubleshooting tips, and compliance milestone celebrations via SMS, voice, and portal
Real-time CPAP adherence and efficacy monitoring with AI assessment of usage patterns, leak rates, and residual AHI — escalation for non-compliance before CMS deadlines
Post-titration AI triage with 91% first-call resolution — handling mask discomfort, pressure adjustment requests, humidity settings, and machine troubleshooting
Automated long-term adherence surveillance with CMS compliance tracking and annual reassessment scheduling — zero patients lost to follow-up after device initiation
Specialized AI employees that handle these workflows autonomously.
Extracts Epworth scores, BMI data, comorbidity profiles, and prior sleep study results from referrals using OCR. Determines home vs. in-lab study appropriateness and verifies insurance coverage for diagnostic and therapeutic pathways.
Optimizes sleep study scheduling based on clinical urgency and pre-test probability. Manages DME fitting appointments and follow-up titration visits. Fills cancellations within minutes, prioritizing high-AHI patients.
Delivers study prep instructions, CPAP usage encouragement, and mask troubleshooting guidance across SMS, voice, and portal. Sends proactive compliance nudges aligned with CMS adherence milestones.
Triages mask discomfort complaints, pressure adjustment requests, and machine errors with AI-driven troubleshooting. Monitors CPAP cloud data for adherence drops and escalates non-compliance before CMS deadline windows close.
Learn more about the platform, AI employees, and measurable outcomes powering modern healthcare practices.
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