# Emocha Financial Model Digital Medication Adherence Program using video-based directly observed therapy (DOT) and a clinical adherence team to confirm dose-by-dose ingestion for transplant patients and other chronic condition populations. - Canonical: https://finamodel.com/startups/emocha - Excel download: https://finamodel.com/startup-models/emocha.xlsx - Category: Health-tech - Model type: SaaS ARR / Valuation - Funding round: N/A - Funding: $6.1M - Founded: 2020 - Geography: USA (Baltimore, MD HQ; partners across FL, VA; Medicaid populations in Baltimore) [DECK slides 2, 12, 16]. - Customer: B2B2C ## About the company emocha provides a digital medication-adherence programme using video-based directly observed therapy and a clinical adherence team. It helps transplant and chronic-condition patients confirm dose-by-dose medication use for health systems and care providers. The product is sold as a bundled institutional programme rather than a standalone consumer app. Its likely commercial structure is a per-patient-per-month fee that combines software, analytics, and human clinical support. The model should forecast transplant-centre customers, enrolled patients per centre, PPPM pricing, enrolment duration, and renewal. Clinical staffing, technology, onboarding, and outcomes-related economics should be separately modelled against recurring programme revenue. ## What's included - 5-year monthly revenue build with stage-appropriate growth assumptions - Full P&L, headcount plan, and operating-expense schedule - Cash-flow statement, runway, and burn-rate tracking - Valuation via exit multiple with a DCF cross-check - Returns analysis with MOIC and IRR - Unit economics including CAC, LTV, payback, and cohort retention ## Product & value proposition - Core product: emocha mobile app + clinical adherence team + analytics/reporting platform for transplant teams. - Patient side: Daily video selfie of medication ingestion, side effect reporting, in-app messaging with adherence coach, asynchronous and live video, reminders, 22 languages. - Clinical team side: Pharmacists do medication reconciliation at program outset; adherence coaches review all videos and provide daily support; registered nurses review symptoms and liaise with care teams. - Transplant team side: Weekly/monthly analytics reports, access to video check-ins, escalation alerts. - Mechanism: CDC-endorsed directly observed therapy (DOT) applied digitally - measures ingestion, not just possession. - Program structure: 3-month daily DOT → ongoing support & medication management. ## Market - Problem scale (transplant): Non-adherence ranges 20–70% across kidney, heart, and liver transplant patients. - 40% of rejections linked to medication non-adherence. - 2/3 of non-adherent patients experience graft failure. - Hospitalization costs from rejection episodes: $4K–$11K. - Non-adherent patients have 7x greater risk for late rejection. - Adjacent indications addressed: TB, Hepatitis C, Asthma, Type 2 Diabetes (per clinical evidence slides). - Existing traction: Standard of care for 450 health departments - likely from prior TB/public-health DOT use, predating the transplant pivot. ## Revenue model - Inferred model: B2B subscription or per-patient-per-month (PPPM) fee charged to transplant centers / health systems. Standard for digital health managed care services. - Service bundling: Platform (app + analytics) + managed clinical team (pharmacists, coaches, nurses) appear to be sold together as a program - not unbundled. - Channel: Direct sales to transplant programs at academic medical centers and health systems (named partners: Johns Hopkins, FSU, UF, UVA, U Miami). - Government funding channel: NIH SBIR grant (R44DK123978) - non-dilutive revenue/grant income. ## Traction & metrics - 450 health departments served (standard of care) - 50-person team - 15+ peer-reviewed studies validating the platform - Active transplant program metrics (pilot cohort, slide 17): - 75 total enrolled patients - 92% average adherence rate for active patients - 6.8% patients required escalation - 8,456 total observed video check-ins - 915 total hours of observed check-ins - 2,893 check-ins in past month / 257 hours - 125 escalations to nurse/pharmacist - 27 escalations to transplant team - 243 adherence challenges logged - Patient adherence breakdown: 60% at 81–100%, 30% at 61–80%, 2% at 41–60%, 5% at 21–40%, 3% at 0–20% ## Unit economics - TB DOT program: $8K saved per patient - cost-avoidance data point, not revenue/margin. ## Competition / moat - Differentiation stated: Only comprehensive Digital MAP combining video technology + human engagement + CDC-endorsed DOT methodology. - Evidence moat: 15+ peer-reviewed studies (NIH, CDC, Johns Hopkins partnerships). - Clinical proof points across 5 conditions: TB (92–95% adherence, $8K saved/patient), TB-CDC (87–92% adherence, 100% treatment completion), Hepatitis C (98% adherence in drug-using population), Asthma (92% adoption, 73% reduction in ED visits*), Type 2 Diabetes (86% adherence, 50% reduction ED visits, 27% reduction hospital admissions*). *Pending publication. - Existing competitors: Not named in deck. - Network/switching moat: Integration with transplant team workflows; playbook specificity to transplant; branded clinical team. ## Team & funding ask / use of funds - Team: 50-person multidisciplinary team - nurses, pharmacists, public health technologists. - Origin: Johns Hopkins spin-out, Baltimore-based. - Founding/leadership team: Not individually named in deck. - NIH SBIR grant: Award R44DK123978 (National Institute of Diabetes and Digestive and Kidney Diseases). - Institutional partners: Johns Hopkins University, Florida State University, University of Florida, University of Virginia, University of Miami, NIDDK. --- ## Recommended financial model - **Archetype + why:** B2B Digital Health SaaS / Managed Care Services - per-patient-per-month (PPPM) revenue model. The business sells a bundled program (app + clinical team + analytics) to transplant centers under an institutional contract. Revenue is best modeled as: (# transplant center clients) × (avg enrolled patients per center) × (PPPM fee). The clinical team is a meaningful COGS driver (labor-intensive: coaches, nurses, pharmacists), making gross margin and headcount modeling critical. This is not a pure SaaS play - the human services layer makes it closer to a tech-enabled services business with ~40–60% gross margins. - **Forecast horizon & granularity:** 5-year annual model (Year 1–5), with Year 1 monthly for cash/headcount planning. Given NIH grant dependency and early commercial stage, monthly burn visibility in Year 1 is important. - **Key drivers & assumptions:** | Driver | Value | Source | | -- | -- | -- | | Active transplant center clients (Y1) | 5 | handful of named partners, early commercial | | Active transplant center clients (Y5) | 50–100 | ~900 transplant programs in US | | Avg enrolled patients per center | 75 | - | | Patient ramp per center (months to fill) | 6–12 | - | | Program duration per patient (months) | 3–6 (DOT phase) + ongoing | - | | PPPM fee | $150–$300 | digital health managed care services range; not in deck | | Clinical team labor (COGS % of revenue) | 45–55% | high-touch model with nurses/coaches/pharmacists | | Platform/tech COGS | 5–10% | - | | Gross margin | 35–50% | - | | Operating team (current) | 50 FTEs | - | | NIH grant revenue (non-dilutive) | Not quantified | - | | Patient adherence rate (clinical outcome) | 92% | - | | Escalation rate (nurse/pharmacist) | 6.8% | - | | Churn (center-level annual) | 10–15% | - | | NRR | 90–110% | expansion via more patients per center | | $8K cost savings per TB patient | use as ROI proof for sales/pricing model | - **Scenarios (Base / Bull / Bear - which variables flex):** - **Bear:** Slow enterprise sales cycles; only 3 new centers/year; low PPPM ($150); gross margin pressure from labor costs; NIH grant not renewed. - **Base:** 8–10 new centers/year; PPPM ~$200; gross margin 40–45%; NIH grant continues through R44 period. - **Bull:** Payer reimbursement unlocked (Medicaid/CMS coverage for DOT); PPPM ~$275+; expansion to non-transplant indications (asthma, diabetes per slide 12); 20+ new centers/year. - **Required sheets / outputs:** 1. **Assumptions** - PPPM, patient volumes, center ramp, headcount ratios, grant income 2. **Revenue build** - centers × patients × PPPM; grant revenue line 3. **P&L** - Revenue, COGS (clinical labor, platform), gross profit, OpEx (S&M, R&D, G&A), EBITDA 4. **Headcount model** - clinical team scales with patients; sales/admin scales with centers 5. **Cash flow / runway** - monthly burn in Year 1; NIH grant receipts; fundraise timing 6. **Unit economics summary** - LTV/CAC by cohort; payback period; gross margin per patient 7. **Sensitivity table** - PPPM vs. patients per center; gross margin vs. labor cost rate ## Frequently asked questions ### Is the Emocha financial model free? Yes. The Emocha model is a free Excel download with live formulas. ### Can I change the assumptions? Yes. The workbook is editable and its live formulas recalculate when assumptions change.