We make healthcare’s knowledge compute.And show its work.
The operating layer to drive business performance through clinical value across programs, contracts, and parties.
A trustworthy foundation for AI and automation, with people in control.
“We don’t even know if we’re going to make or lose money until it’s all over.”
Healthcare is changing how it gets paid and how it organizes care, both at once. The systems underneath were built for neither.
Where we fit
The missing layer in healthcare’s stack.
The shared layer between healthcare’s data and its AI, for every party in a program.
Apps and workflows
EHR workflow, population health, engagement and communications, point solutions
AI and automation
Copilots, agents, and automation
On its own, sits directly on data or narrative guidance, so answers vary and are hard to trace or replay.
Knowledge, deterministic reasoning, and orchestration
CoEfficient
Today, each party hard-codes it in analytics, spreadsheets, custom software, and vendor rules and engines.
Data and analytics platforms
EHRs, claims, and other systems of record
Hold the records and report what happened via analytics and dashboards.
AI proposes and explains. Governed knowledge adjudicates. People decide.
What we are
A health knowledge, reasoning, and orchestration platform.
To change the economics
Unify
Clinical, business, and process knowledge in one governed reasoning layer, so every insight carries the context of the person, the program, and the contract.
How it’s different
A knowledge-driven system, so reasoning is personalized and one source serves every use.
To re-orient operations
Orchestrate
Payers, providers, and affiliates working from the same trusted, near real-time insights and the same evidence, at the same time.
How it’s different
Multi-entity by design, with every party keeping control.
To reduce many-to-many complexity
Empower
Control over your own performance and risk, confidence in negotiations and audits, and independence from fragmented vendors, systems, and teams.
How it’s different
Governance, evidence, and reproducibility are structural.
Our approach
Deterministic knowledge that computes, like a GPS.
Directions, arrival times, and rerouting all agree because they are computed from one digital map. Healthcare’s knowledge has never had shared, computable definitions, so each system has derived its own.
Written for people
A model of the real world to be queried and reasoned over
An operating system to interact with the model
Every use, derived
A GPS
how navigation works
A paper road atlas
One map
Every road, limit, and junction, with live traffic
The navigation system
Knows where you are and where you’re going and what you’re asking for
- Driving, walking, or transit
- Arrival time, with traffic
- Multi-stop trips
- Search along the route
- Avoid tolls or highways
- The next use case
- Voice assistant
- Autonomous driving
All connected and consistent.
CoEfficient
how healthcare’s knowledge can work
Guidelines, policies, and contracts
One governed expression
Clinical, business, and process knowledge, as its owners set it
The reasoning engine
Knows each patient’s case, plan, and the use case
- Plan quality measure
- Provider quality measure
- Prior authorization criteria
- Point-of-care decision support
- Care pathway tracking
- The next use case
- AI copilots and agents
- Workflow automation
All connected and consistent.
A GPS
how navigation works
CoEfficient
how healthcare’s knowledge can work
Written for people
A paper road atlas
Guidelines, policies, and contracts
A model of the real world to be queried and reasoned over
One map
Every road, limit, and junction, with live traffic
One governed expression
Clinical, business, and process knowledge, as its owners set it
An operating system to interact with the model
The navigation system
Knows where you are and where you’re going and what you’re asking for
The reasoning engine
Knows each patient’s case, plan, and the use case
Every use, derived
- Driving, walking, or transit
- Arrival time, with traffic
- Multi-stop trips
- Search along the route
- Avoid tolls or highways
- The next use case
- Voice assistant
- Autonomous driving
All connected and consistent.
- Plan quality measure
- Provider quality measure
- Prior authorization criteria
- Point-of-care decision support
- Care pathway tracking
- The next use case
- AI copilots and agents
- Workflow automation
All connected and consistent.
You can always get directions from a map, but can’t reconstruct the map from directions.
What you can do
Better results under every program, while reducing cost and complexity.
Every solution runs on the same governed knowledge, shared across the parties in a program and working with your existing systems. Each one you add reuses what’s already built.
Program design and governance
Programs launched and changed faster, with fewer disputes between parties
Populations, contracts, and incentives as computable rules every party shares
Performance management
Contract performance optimized continuously
Leading indicators computed from each contract’s own terms to forecast and steer
Care value management
Better outcomes, more first-pass approvals, and practical automation
Clinical guidelines and best practices agreed once and applied consistently across parties and policies
Network and ecosystem engagement
Networks that grow at falling marginal cost
Governed affiliate networks to share insights and rules without rebuilds
Data quality, compliance, and evidence
Evidence that stands up to audit and enables automation and AI governance
Any decision replayed exactly as it was made, with evidence
Why now
Outcome-based programs were missing a layer. It is now buildable.
The push for value tied to outcomes is only getting stronger.
The standards are real, and regulators now require them.
The AI is here. Its value and risk both depend on its foundation.
Founders
Brad Ryan, MD
Co-founder
More than twenty years helping payers and providers align business value to clinical value, and building large-scale platforms to make it work.
McKinsey & Company | IMS Health (IQVIA) | Apervita | NCQA | Johns Hopkins University
Matthew M. Burton, MD
Co-founder
More than twenty years taking healthcare knowledge-driven systems from academia into real-world use at institutions including Mayo Clinic.
Mayo Clinic | Apervita | Regenstrief Institute | Arizona State University
Contact
Request a briefing
We’re early, and working with a small group of co-development partners. Tell us what you’re working on, and we’ll be in touch.
Prefer email? Write to info@coefficienthealth.com.
Who we work with
- Program sponsors and health plans
- Health systems and practices
- Quality programs and measure developers
- AI and application builders
- Medical societies and registries