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Doctor Yes® is the AI infrastructure for continuous chronic disease management — closing the 90-day care gap between quarterly visits with always-on adherence and behavioral intelligence. The AI doctor that never leaves the room.
“What would it take for a person with a chronic condition to feel like they had a doctor available every single day — not just four times a year? That’s the question I built Doctor Yes® to answer.”Samuel R. Homer, PhD Founder & CEO · Applied Health Intelligence, LLC
Today’s healthcare system was never designed for continuous care. It was built for sparse appointments. Three to four visits a year, each lasting 15 minutes. The other 8,706 hours? Patients are on their own — and that is where chronic disease wins in the silence between.
To medication non-adherence alone. 350,000 health apps exist. The root cause goes unaddressed.
The exam room is missing everything from 2,000+ hours since the last visit. No platform fixes this — until now.
$200–$400 per patient per month. Programs end. Results disappear. 147M patients can’t afford a coach.
Wearables, pharmacy records, lab results, conversations — no platform connects them into one picture.
Rule-based alerts don’t understand the patient behind the data. Everyone mutes the same notification.
Chronic Disease Cost is the biggest gas guzzler of our time. But nothing has worked so far to improve its efficiency!
Not where the technology is most convenient. Whatever channel feels natural — a conversation, a photograph, a wearable, a lab result — becomes a clinical signal.
CGM glucose, HRV, blood pressure, sleep architecture, activity — passively, continuously
Change-talk, illness-label avoidance, sentiment — extracted from every message
Lab slips, handwritten specialist notes, food labels — OCR-parsed instantly
Surescripts fill records, PDC per medication, late-fill and gap detection
FHIR R4, HL7 v2 — HbA1c, eGFR, diagnoses, medication lists
App engagement, response latency, notification patterns — all diagnostic
No specific device required. No form to fill in. The inference engine maintains ≥75% accuracy even when some input channels are missing.
The inference engine synthesizes all available patient channels. No specific device stack required. The platform meets the patient where they are.
5-layer ML — Bayesian PGM → XGBoost → ensemble fusion → uncertainty quantification. All channels synthesized into s_t every observation cycle.
Full posterior over 11 phenotypes. NLP late-fusion. Cultural calibration κ(k_t, φ_k). Updated in real time by every intervention outcome.
Rule Engine: 8 deterministic constraint classes. Thompson Sampling bandit + PPO RL. ~60–120 feasible actions per patient state after Rule Engine filtering.
1,000 Monte Carlo trajectories per patient per 24h. T_horizon = 90 days. Current path vs ACTIVE policy side-by-side. Policy pre-validated on 10,000 virtual patients before deployment.
24h divergence detection. Root-cause attribution. Automatic program correction. Clinical alerts <15 minutes for threshold crossings (HbA1c >10.5%, SBP >180, PHQ-9 >18).
Nutrition, Exercise, Sleep, Stress, Behavior, Medical Risk (VETO authority). Orchestrator conflict resolution. One precisely matched interaction every time.
Vitals · Biometrics · Lab trends · Phenotype + Z-codes · Behavioral state · Coaching log (Epic SmartText) · Clinical alerts · Medication adherence · Digital twin projections · Pre-visit summary T-48h. Not a parallel system. The clinical workflow itself.
Doctor Yes® classifies each patient into one of eleven psychologically distinct non-adherence mechanisms and delivers the matched intervention from nearly 2,000 possible responses. No other platform does this.
1,000 Monte Carlo simulations every 24 hours. Not a population average — your specific health trajectory under two scenarios, updated daily with your latest data.
Every intervention is pre-validated against your digital twin before delivery. If the simulation shows it won’t help you specifically, it isn’t sent.
Policy pre-validation: N_sim = 10,000 virtual patients. Deploy only if VMC(π*) > VMC(π_current) at p < 0.05 AND no cultural subgroup k_t degrades. Blue-green deployment on 10% enrolled before full rollout.
Every conversation, every lab result, every biometric, every document — your AI doctor knows your full story and responds to what’s actually happening with you today.
Builds long-term rapport. References prior conversations and milestones naturally. Available at 2am when the anxiety hits. Makes patients feel genuinely known.
Leads with numbers. Minimal small talk. Gets to the point. Treats patients as intelligent partners in their own care. Respects their time and analytical capacity.
Patient-as-protagonist. Low task pressure. Creates safety to explore ambivalence without judgment. Uses the patient’s own words back to them. Never pushes.
Every competitor requires clinicians to log into a separate dashboard. Doctor Yes® writes structured clinical data directly into the physician’s existing EHR — automatically, without any clinician action required.
Non-destructive. Source-tagged. Idempotent. Consent-gated. ONC 21st Century Cures Act compliant. 7-year HIPAA audit logging on every write.
Auto-written to the physician’s chart 48h before every scheduled appointment. Phenotype, adherence trends, digital twin projections, outstanding safety flags, and suggested discussion points. Your patient’s story — waiting in the chart before they walk in.
BP · HR · weight · BMI · 7-day rolling average · daily
CGM TIR · estimated HbA1c · HRV · sleep duration · step count
HbA1c velocity · adherence-adjusted note · predicted value at next visit
Ambivalence φ_k · TTM stage · ICD-10 Z-codes for SDOH barriers
α_diet · α_med · α_exer · α_sleep · c_t capability · μ_t mood
Weekly physician note · Epic SmartText compatible · intervention outcomes
HbA1c >10.5% · SBP >180 · PHQ-9 >18 · <15 min · escalates 24h
PDC per drug · late-fill events · Flag on PDC <0.80 critical meds
HbA1c/SBP p10/p50/p90 at 30/60/90d · Framingham ASCVD · current vs ACTIVE
Doctor Yes® is built to serve health plans, employer groups, and value-based care organizations that bear the financial consequences of the 8,706-hour care gap. When chronic disease compounds between quarterly visits, your covered population pays the cost in avoidable hospitalizations, ER utilization, and accelerated disease progression.
Medication adherence tracking (PDC) and HbA1c control measures addressed continuously between visits, not just at the point-of-care encounter.
24-hour divergence detection and clinical alerts <15 minutes intercept deteriorating patients before they become inpatient admissions or ER visits.
CMS ACO and MSSP shared-savings arrangements reward exactly the longitudinal adherence and outcome improvements Doctor Yes® is engineered to produce.
The phenotype classification layer surfaces which members are most at-risk of non-adherence and why — allowing care management teams to prioritize interventions at the member level.
Poorly managed T2DM and hypertension cost employers an estimated $20B+ annually in reduced productivity. Continuous adherence intelligence directly addresses the behavioral gap driving that cost.
For self-insured employer groups, every avoided complication and every prevented hospitalization is a direct reduction in claims expense. Doctor Yes® generates measurable ROI on a per-member basis.
Offering an always-on AI doctor as a benefits feature signals genuine investment in employee health — differentiating the employer brand in competitive talent markets.
1 in 3 working-age adults in the U.S. has hypertension. 1 in 10 has T2DM. For any employer with 500+ employees, continuous chronic disease management is not a wellness benefit — it is a workforce health imperative.
For pharmaceutical companies, the gap between a dispensed medication and a patient who consistently takes it correctly is where clinical and commercial value erodes. Doctor Yes® is the first platform purpose-built to detect, understand, and resolve medication non-adherence at the individual patient level — and to generate the real-world evidence that proves it.
License the Doctor Yes® adherence engine to monitor and improve real-world adherence to your specific drug, in your target patient population, at scale.
Understand which of the 11 ambivalence phenotypes most commonly drives non-adherence to your drug — and deploy matched behavioral interventions that address the actual mechanism, not a generic reminder.
Every adherence intervention is pre-validated against the patient's personal digital twin. No intervention deploys unless simulation projects a positive outcome for that specific patient.
Proportion of Days Covered tracked continuously per patient, per drug — with automatic clinical alerts to the prescribing physician when PDC drops below 0.80 on critical medications.
Longitudinal, FHIR R4-structured data on medication adherence, behavioral state, biometrics, and clinical outcomes — the behavioral RWE profile of your drug in actual patient populations.
Continuous monitoring of adherence patterns across enrolled populations supports post-approval safety monitoring, with structured EHR write-back enabling integration into pharmacovigilance workflows.
Understand adherence by phenotype, demographic, comorbidity, and concurrent medication — granular behavioral segmentation that trial data cannot provide and that shapes label strategy and patient support programs.
License the Doctor Yes® behavioral inference engine as a white-label patient support platform under your brand, or access adherence intelligence via API to power your existing patient engagement infrastructure.
Clinical trials are won or lost on two variables: who you enroll and whether they stay on protocol. Doctor Yes® addresses both — continuously, behaviorally, and at the individual patient level.
Doctor Yes® continuously identifies and risk-stratifies patients by their ambivalence phenotype before enrollment begins. Sponsors receive a pre-screened cohort already profiled for behavioral compliance likelihood — reducing screen failure rates and shortening the enrollment window.
Every dose, every dosing window, every adherence gap is detected and logged as structured FHIR R4 clinical data. Investigators receive real-time PDC dashboards per patient, per arm — enabling protocol deviation alerts before they become ITT integrity problems.
The behavioral inference engine flags dropout risk 14–21 days before a patient withdraws — based on conversation patterns, biometric drift, and engagement decay signals. Targeted retention interventions are deployed automatically, matched to each patient's specific ambivalence driver.
Wearable biometrics, CGM streams, and daily behavioral signals are captured passively and written into each patient's EHR — enabling decentralized trial designs with continuous, objective endpoint measurement that traditional site visits cannot match.
Every Doctor Yes® trial deployment generates a parallel behavioral RWE dataset — longitudinal, FHIR R4-structured, audit-ready — documenting exactly how patients interacted with the drug in real-world conditions alongside the trial arm. This dataset accelerates label expansion, informs label language on adherence, and provides the behavioral substrate for post-approval commitments.
LLMs and multi-agent systems now understand natural conversations, photographs, documents, and behavioral signals at scale. The infrastructure to build an always-on AI doctor finally exists.
CGMs, Apple Watch, Fitbit, and connected monitors generate continuous biometric streams for more than 100 million Americans — raw material for behavioral inference that didn’t exist three years ago.
Siri, Alexa, ChatGPT, and Claude have normalized conversational AI for hundreds of millions — eliminating the technology-adoption barrier that once blocked digital health engagement.
$4.9T in annual chronic disease spend, 90% preventable. CMS value-based care mandates creating urgent demand. Patients who cannot afford their premiums. The cost of inaction now exceeds the cost of the solution.
FDA PDURS framework opens a prescription drug companion app pathway — converting DoctorYes® from a wellness tool to a prescribed, reimbursable clinical instrument. The 2024 FDA Final Guidance on Decentralized Clinical Trials explicitly endorses digital health tools as trial elements, unlocking RPM billing codes (CPT 99453–99458).
*All financial projections are forward-looking statements and are not guarantees of future performance. Pilot results are preliminary from a 31-patient feasibility study.
Join the founding members bringing Doctor Yes® to the 147 million Americans managing chronic conditions — and to the physicians who care for them.
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Hello@DoctorYes.ai · Applied Health Intelligence, LLC
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