📊 See It In Action
Inside the AequiPath Dashboard
One-click audits, live disparity-ratio trend lines, and auto-generated disclosure packages, built for the compliance and quality teams who have to act on what it finds.
AequiPath watches four ordinary-looking fields in Epic's prior-authorization and scheduling data, and flags when they quietly reproduce discrimination no one coded in.
Fairer Pathways. Healthier Communities.
To advance systemic fairness, structural transparency, and algorithmic governance across healthcare infrastructure.
A healthcare system where every person, in every community, has equitable access to timely, high-quality care, powered by trustworthy technology.
Do what is right, always.
People over profit.
Fairness in every decision.
Remove barriers. Expand access.
Build better. Go further.
Use data. Drive lasting impact.
"Let justice roll on like a river, righteousness like a never-failing stream!" — Amos 5:24 (NIV)Aequitas sicut torrens fortis (Vulgate)
Prior authorization queues and scheduling systems routinely use claim density, zip code, Medicaid coverage, and missed-appointment history to decide who gets expedited and who waits. None of these variables mention race or income. All four are well-documented statistical proxies for them.
A prioritization rule built on these inputs can produce a discriminatory outcome without a single protected characteristic ever appearing in the code, which is exactly what makes it hard to catch, and easy to defend as "just operations."
Runs continuously against Epic's prior-authorization and scheduling data, risk-adjusted against clinical acuity, so it isolates the part of any gap acuity can't explain.
Sits alongside a live prior-authorization decision and flags it for human review the moment it lands in a known disparity pattern, before the patient feels the delay.
Output: a disparity report and a compliance-ready disclosure package for your quality and compliance teams, not just an alert, a paper trail.
One-click audits, live disparity-ratio trend lines, and auto-generated disclosure packages, built for the compliance and quality teams who have to act on what it finds.
AequiPath runs on Epic's Da Vinci and native FHIR APIs, nothing proprietary, nothing that requires custom Epic configuration.
No protected-class attribute is ever used as a model input, only claims, coverage, and scheduling data Epic already exposes.
January Montaño is the founder of Aequitas Technologies, Inc. She served as Deputy Director of Sourcing on Colorado's COVID-19 Innovation Response Team, where she helped secure 27.8 million PPE items internationally, and later helped architect equity-driven policy for the 1.3 million members of Health First Colorado, the state's Medicaid program. She has testified before the Colorado General Assembly on algorithmic bias in AI systems.
A 30-minute consultation to understand your Epic build and current prior-auth and scheduling workflows.
AequiPath runs against sandbox data to validate the API connections and the disparity model.
Runs against your live data with your compliance team, producing the first real disparity report.
Full deployment with ongoing monitoring, reporting, and Aequitas Technologies as your engineering partner.
AequiPath is built for a health plan, hospital system, or Medicaid MCO ready to see what its own prior-authorization and scheduling data actually shows.