- Compounding-activePatients with at least one active interaction between their conditions.
- 31%
- Re-rankedPatients who move higher on the priority list once those interactions are counted.
- 17%
Who we serve · Health systems
The admissions you can prevent are already in your record.
Your record already documents her conditions. What it doesn’t weigh is how they interact — and that is where the avoidable admission lives.
- Day 0Discharged home
Her chartSix conditions, each controlled. Nothing due.
Patient 3-D firesCompounding flagged at discharge. Her protocol opens.
- Day 3Transitional-care visit due
Her chartNot scheduled.
Patient 3-D firesVisit booked; her care team notified; a monitoring kit ships.
- Day 9Nephrology referral
Her chartNot placed.
Patient 3-D firesReferral routed with the reason; medication reconciliation done.
- Day 21The readmission her chart didn’t flag
Her chartBack through the emergency room.
Patient 3-D firesHer weight and blood pressure reached a nurse days earlier. The nurse called.
- Day 30The month closes
Her chartA readmission on the record.
Patient 3-D firesShe is home.
What you get.
The patients, ranked
A list of the patients whose conditions are compounding, with the interaction named for each one.
The protocol, fired
Chronic care management, transitional care, remote monitoring — services already covered, routed to the roles that own them.
One queue, closed
Your care team works one queue, ordered by the protocol, with every action documented and closed.
Measured on an academic health system.
1 in 31complex patients carries an interaction no risk score weighs.
The same engine, the same release, run on a synthetic cohort calibrated to a two-region academic health system.
Her path, where you meet it.
The steps of the platform that land on your desk. Every one is a service already covered.
She is seen.
Her record arrives — the same record everyone had. The engine reads her conditions as one compounding trajectory and names what no single-disease guideline was watching for.
Her physician opens the chart.
The protocol is already there: nephrology within 48 hours, a medication reconciliation, a transitional-care visit — fired by her interactions, routed to the roles that own them, documented with the codes that pay for them.
Her care team runs on one queue.
A Care Captain, a nurse triage line that never closes, a community health worker for the ride she couldn’t get — dispatched by the protocol, not by whoever noticed first.
She stays home.
That’s the outcome. Everything else is the machinery.
Built by people who ran the systems it fixes — twenty years inside government health programs, PMO leadership across twenty-five-plus health plan launches, and a fourteen-seat clinical bench. Meet the team →
How it starts.
A proof of value: one extract under a data use agreement and your clinicians’ judgment, with nothing installed on your side. In production, Patient 3-D runs inside your environment, and your data never leaves it.
One extract under a data use agreement, delivered once.
A flat-file extract you already know how to produce, limited to the fields the analysis needs. We send the column spec; you send the file once.
A sealed U.S. environment.
The proof of value runs in a sealed environment in the United States, with no connection to your systems.
Your clinicians at the review table.
Your named clinical reviewers see every figure before any figure is released.
Results in weeks.
Your population measured in three dimensions — what each patient has, how severe, how it compounds. Weeks, not a program.
Destroyed, with a certificate.
When the work ends the environment is destroyed, and you receive a certificate of destruction.
See it on your data.
A flat-file extract, a sealed environment, your clinicians at the review table, results in weeks.