IntelliHealth™ is our clinical decision-support system. It analyzes the patient record, proposes protocol options, and flags issues worth a second look — and it routes every significant call to a pharmacist for sign-off.
The problem
Personalized care is hard to scale. As patient volume grows, the time per patient shrinks, and quality is usually what gives. We wanted a system that protected the clinician’s attention — handling the gathering and the first pass so the human could spend their judgment where it matters.
How it’s built
Three layers do the work. None of them act on their own; each one prepares the ground for a person to make the call.
Decision engine
Models that surface and rank protocol options for review — never auto-prescribe.
Data layer
A patient record that assembles the context a pharmacist needs in one place.
Integration
Connections into the systems clinicians already use, so the work fits the workflow.
What it handles
What we learned
The hardest part was never the modeling. It was drawing a clear line between what the system suggests and what a person approves — and holding that line as volume grew. The value of the tool turned out to be the time it gave back to clinicians, not the decisions it could make on its own.
A fuller technical write-up — architecture choices, the trade-offs, and the failure modes we designed around — is in progress and will land here.