How much is OmniHealth Intelligence?

OmniHealth Intelligence is listed for sale at $200 USD.

OmniHealth Intelligence - Sell Project

Name: OmniHealth Intelligence
Price: 200 USD
Availability: SoldOut

Listed December 30, 2025

About OmniHealth Intelligence

An AI-powered operating system for hospitals that unifies care, ops, revenue.

Accepting all reasonable offers — motivated to close quickly. Project Description — OmniHealth Intelligence OmniHealth Intelligence is a 45-layer, enterprise-grade healthcare operating system designed to run hospitals, payers, telehealth networks, population health programs, genomics, neuro care, biosimulation, and revenue cycle operations from a single, AI-orchestrated platform. It is not a demo, not a dashboard, and not a narrow tool. It is a full healthcare OS where AI sits inside every workflow to assist → check → route → learn → improve, while remaining explainable, auditable, and clinician-controlled. This system is built as a complete platform foundation that buyers can deploy, extend, white-label, or commercialize as multiple products. 1) Patient Access & Front Door OmniHealth Intelligence manages the entire front door of care: Patient registration, identity matching, demographics, insurance capture Scheduling for clinics, imaging, labs, procedures Eligibility checks, appointment reminders, no-show risk flags Digital intake: symptoms, history, questionnaires, consents, forms Pre-visit triage and routing (urgent vs routine, specialty matching, risk signals) AI assists with intake summarization, risk flagging, and routing — never replacing clinical judgment. 2) Admissions, Transfers & Discharge (ADT) The platform supports full encounter lifecycle management: Create and manage admissions, transfers, and discharges Bed assignment logic, unit flow tracking, and handoff scaffolds Discharge readiness indicators and barrier tracking Follow-ups, referrals, discharge instructions, and transition coordination This layer reduces length of stay, improves throughput, and minimizes discharge delays. 3) Core EHR Clinical Workflows (MediCore) A complete EHR-grade clinical core is included: Clinical documentation (H&P, progress notes, consults, procedure notes) Orders & results workflows (labs, imaging, medications, procedures) Problem lists, allergies, medications, medical history Vitals timelines, task management, messaging, and notifications Role-based routing for clinicians, nurses, and ancillary staff AI supports documentation quality, safety checks, and completeness — never autonomous decision-making. 4) Nursing & Inpatient Operations Built specifically for inpatient nursing realities: Nursing care plans, vitals capture, rounding support Medication Administration Record (MAR) safety patterns Falls risk, pressure injury risk, bedside protocol checklists Shift-based task boards with escalation logic This layer improves handoffs, reduces missed tasks, and improves patient safety. 5) Pharmacy & Medication Management End-to-end medication intelligence scaffolds: Medication ordering workflows Drug interaction, allergy, duplicate therapy, and dose safety checks Medication reconciliation (admission → inpatient → discharge) Discharge medication lists and eRx handoff patterns AI acts as a safety net, not a prescriber. 6) Labs & Imaging Integration Patterns Designed to integrate with LIS, RIS, and PACS systems: Lab result ingestion and normalization patterns Imaging workflows with report attachment scaffolds Critical result routing and acknowledgment workflows Supports enterprise-scale diagnostic operations. 7) Specialty Care Workflows (Extensible) The system includes extensible scaffolds for: Emergency department workflows ICU monitoring patterns Procedural pathways Rehabilitation (PT/OT) Behavioral health flows Chronic care programs NeuroCare / NeuroNet for screening, symptom tracking, therapy planning Each specialty can be expanded without breaking the core. 8) Care Management & Transitions (CarePath) CarePath provides structured care coordination: Evidence-based care pathways Utilization review scaffolds Case management and discharge planning Referrals and authorization workflows Social determinants of health (SDOH) tracking Post-discharge follow-ups and readmission prevention AI highlights gaps, risks, and next steps — humans decide. 9) Telehealth Orchestration OmniHealth includes a full telehealth layer: Virtual visits (video, chat, async pathways) AI-assisted triage bots and scheduling routing eOrders and home test kit routing Device gateway patterns for wearables, BP cuffs, glucose monitors Telehealth is treated as a first-class care channel, not an add-on. 10) Population Health Analytics Population-scale intelligence includes: Cohort building and risk stratification Chronic disease program tracking Quality program measurement (HEDIS-like patterns) Outreach campaigns and care gap closure Forecasting and capacity planning Supports both providers and payers. 11) Clinical Decision Support (CDS) & Safety Surveillance Built-in safety intelligence: Rules engine scaffolds with ML hook points Sepsis, falls, and adverse drug event surveillance Guideline enforcement with clinician override and audit trails All AI outputs are explainable and traceable. 12) Genomics Platform (GeneGuard) Genomics workflows are natively support...

Project details

Built with: Vite,React,css,jsx,Node.js,REST API,JSON,OAuth,RBAC,Audit Logging,Microservices,PostgreSQL,Redis

Website: https://omnihealth-intelligence.vercel.app/

Video 1: https://vimeo.com/1150405741?share=copy&fl=sv&fe=ci

Next step: <h2>How the Buyer Can Take This Project Further</h2>OmniHealth Intelligence is designed as a platform foundation, not a finished product. A buyer can take it further across deployment, commercialization, expansion, and specialization, depending on their goals and resources.<h2>1) Deploy It as an Internal Healthcare Operating System</h2>A buyer with access to a hospital, clinic network, or payer can:<ol><li data-list="bullet">Deploy the platform internally as a unified operating layer</li><li data-list="bullet">Integrate with existing EHR, LIS, RIS, PACS, billing, and payer systems</li><li data-list="bullet">Use AI-assisted workflows for:</li><li data-list="bullet" class="ql-indent-1">Clinical documentation support</li><li data-list="bullet" class="ql-indent-1">Care coordination</li><li data-list="bullet" class="ql-indent-1">Safety surveillance</li><li data-list="bullet" class="ql-indent-1">Revenue cycle optimization</li><li data-list="bullet">Gradually replace legacy point systems over time</li></ol>Result: Operational efficiency, better outcomes, and reduced vendor sprawl.<h2>2) Commercialize It as a SaaS or Enterprise Platform</h2>A health-tech company or founder can:<ol><li data-list="bullet">Productize the platform into multiple SaaS offerings:</li><li data-list="bullet" class="ql-indent-1">AI-first EHR</li><li data-list="bullet" class="ql-indent-1">Revenue Cycle Management platform</li><li data-list="bullet" class="ql-indent-1">Care management & population health</li><li data-list="bullet" class="ql-indent-1">Telehealth orchestration</li><li data-list="bullet" class="ql-indent-1">Biosimulation & research analytics</li><li data-list="bullet">Offer modular pricing (per facility, per provider, per member, per claim)</li><li data-list="bullet">White-label the platform for health systems or regional partners</li><li data-list="bullet">Build enterprise sales motion with multi-year contracts</li></ol>Result: Multiple revenue streams from one core platform.<h2>3) Spin Out High-Value Modules as Standalone Products</h2>The system can be decomposed into sellable products, such as:<ol><li data-list="bullet">AI-driven denial management & underpayment detection</li><li data-list="bullet">Discharge optimization & readmission prevention</li><li data-list="bullet">Population health risk stratification</li><li data-list="bullet">Telehealth triage & intake automation</li><li data-list="bullet">BioSim trial emulation tools</li><li data-list="bullet">Genomics decision support (PGx)</li></ol>Each module already has workflow and data scaffolds in place.Result: Faster time-to-market for niche healthcare tools.<h2>4) Extend AI Capabilities Safely</h2>A buyer can:<ol><li data-list="bullet">Plug in proprietary ML models or LLMs</li><li data-list="bullet">Train models on institution-specific data</li><li data-list="bullet">Tune alert thresholds and decision support rules</li><li data-list="bullet">Expand predictive analytics (LOS, readmissions, capacity, denials)</li><li data-list="bullet">Improve continuous learning loops using real outcomes</li></ol>All AI remains assistive, auditable, and clinician-controlled.Result: AI advantage without regulatory or ethical risk.<h2>5) Pursue Regulatory & Compliance Hardening</h2>Depending on region and use case, a buyer can:<ol><li data-list="bullet">Add HIPAA / regional privacy compliance controls</li><li data-list="bullet">Complete SOC 2 / ISO-style security certifications</li><li data-list="bullet">Validate clinical decision support governance</li><li data-list="bullet">Formalize model risk management and audit processes</li></ol>The platform already supports audit logging and traceability.Result: Enterprise and government-ready deployments.<h2>6) Integrate with Real-World Data Sources</h2>Buyers can integrate:<ol><li data-list="bullet">Live EHR systems (FHIR, HL7)</li><li data-list="bullet">Payer claims feeds</li><li data-list="bullet">Pharmacy benefit managers</li><li data-list="bullet">Wearables and remote monitoring devices</li><li data-list="bullet">Lab and imaging vendors</li><li data-list="bullet">Public health datasets</li></ol>The platform is built to ingest and normalize diverse data.Result: Real-time intelligence across the care continuum.<h2>7) Expand into New Markets & Regions</h2>The architecture supports:<ol><li data-list="bullet">Multi-region deployments</li><li data-list="bullet">Multi-language UI layers</li><li data-list="bullet">Regional billing and regulatory rules</li><li data-list="bullet">Public vs private healthcare models</li></ol>A buyer can localize and expand internationally.Result: Global healthcare platform potential.<h2>8) Build Partner & Ecosystem Integrations</h2>A buyer can:<ol><li data-list="bullet">Open APIs to partners</li><li data-list="bullet">Build app marketplaces on top of the platform</li><li data-list="bullet">Integrate pharma, device, and research partners</li><li data-list="bullet">Enable third-party analytics or reporting tools</li></ol>This turns OmniHealth into a platform ecosystem, not just a product.<h2>9) Use It as an Acquisition or Investment Asset</h2>The buyer can:<ol><li data-list="bullet">Bundle OmniHealth with other health-tech assets</li><li data-list="bullet">License components to enterprise customers</li><li data-list="bullet">Position it for acquisition by:</li><li data-list="bullet" class="ql-indent-1">EHR vendors</li><li data-list="bullet" class="ql-indent-1">Payers</li><li data-list="bullet" class="ql-indent-1">Large health-tech firms</li><li data-list="bullet" class="ql-indent-1">Private equity-backed rollups</li></ol>Result: Strategic exit opportunities.<h2>10) Long-Term Vision: A Living Healthcare OS</h2>With real usage data, OmniHealth Intelligence can become:<ol><li data-list="bullet">A continuously improving clinical intelligence system</li><li data-list="bullet">A self-optimizing operations platform</li><li data-list="bullet">A revenue protection engine</li><li data-list="bullet">A research and simulation backbone</li><li data-list="bullet">A digital twin of healthcare delivery</li></ol><h2>Final Thought for Buyers</h2>This project saves buyers years of development and millions in build cost. Instead of starting from scratch, they acquire a deep, realistic, AI-native healthcare platform and decide how far to take it.

For sale

Asking price: $200 USD

What's included

Source code, All related data

What Is Included in This Sale (Full Details) This is a complete intellectual property (IP) transfer of a 45-layer, enterprise healthcare operating system. The buyer receives everything required to own, extend, deploy, and commercialize the platform. 1) Full Platform Architecture & System Design Complete 45-layer system architecture documentation Clear separation of clinical, operational, financial, analytics, and AI layers End-to-end workflow maps for hospitals, payers, telehealth, genomics, BioSim, and population health Domain models for: Patient access & ADT Core EHR workflows Nursing, pharmacy, labs, imaging Care management & transitions Revenue cycle (claims → payments → denials → collections) Genomics, neuro, biosimulation Enterprise ops & audit This allows buyers to understand how the system works as a whole, not just individual features. 2) Source Code & Platform Scaffolds Frontend UI code (React/Vite) Backend service scaffolds (Node.js, APIs, microservices patterns) Workflow engines and routing logic scaffolds Rules engine and AI hook points Telehealth orchestration patterns RCM pipelines (claims, ERA, denials, appeals, underpayments, billing) Population health, cohort analytics, and reporting scaffolds The code is production-structured, modular, and designed for extension. 3) AI & Intelligence Frameworks (Non-Autonomous) Clinical decision support (CDS) scaffolds Safety surveillance patterns (sepsis, falls, ADEs) MedIntel operational analytics Revenue intelligence (denial prediction, underpayment detection logic) BioSim modeling and trial emulation hooks Continuous improvement feedback loops All AI is assistive, explainable, auditable, and overrideable — suitable for regulated environments. 4) Revenue Cycle Management (RCM) System (Layers 43–45) Claims and clearinghouse integration scaffolds ERA / 835 ingestion and normalization Auto-posting ledger rules Reconciliation queues Denials ingestion and categorization (CARC/RARC) Appeal packet builders and auto-le...

Reason for selling

I built OmniHealth Intelligence as a foundational, enterprise-level healthcare operating system, with the intention of creating real infrastructure rather than a quick MVP or demo. Over time, the scope of the platform grew into a full 45-layer system capable of supporting hospitals, payers, telehealth, population health, genomics, biosimulation, and revenue cycle operations from one unified architecture. At this point, my personal focus and health priorities require me to concentrate on a smaller number of active projects. Taking a platform of this depth into live healthcare environments demands sustained operational, regulatory, and commercialization effort that is best handled by a dedicated organization or team. Rather than letting this system sit unused, I’ve chosen to make it available as a clean, complete IP asset so it can be deployed, extended, or commercialized by someone who is positioned to take it to market. This decision is not due to technical shortcomings or lack of belief in the platform. The architecture, workflows, and AI frameworks are complete, thoughtfully designed, and built for real-world healthcare complexity. My goal with this sale is to see OmniHealth Intelligence reach its full potential and real-world impact under ownership that can fully invest in its next phase.

Project metrics

Average Monthly Revenue: Undisclosed