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Resources

Ideas on the future of patient disposition.

Research, guides, and conversations on capacity, coordination, and AI in the hospital. More arriving as we approach launch.

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Whitepaper

The $2.7B problem: why discharge delays are a coordination failure, not a clinical one.

A data-driven look at where bed-days are really lost — and how predictive orchestration changes the math.

Read the paper →
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Guide

A buyer's guide to EHR-agnostic AI

What to ask vendors before you sign — integration timeline, data access, and the BAA.

Read the guide →
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Webinar

Predicting readiness 48 hours out

A walkthrough of the clinical signals behind disposition prediction, with live Q&A.

COMING SOON
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Case study

Your pilot results here

We'll publish bed-day and length-of-stay outcomes from our first hospital partners.

COMING SOON
FAQ

Questions we hear most.

Which EHRs do you integrate with?

DispoHealth.ai is being built to be EHR-agnostic. We're designing it to connect via API to Epic, Cerner, MEDITECH, athenahealth, and other major systems — no rip-and-replace — with the goal of bringing most connections live in weeks.

How is patient data protected?

We're building DispoHealth to be HIPAA-compliant from day one, with a BAA signed for every customer. The platform is being designed to encrypt data in transit and at rest, with role-based access, SSO, and full audit logging.

How far ahead can you predict disposition?

Our models are being built to forecast disposition readiness 24–48 hours in advance, using lab trajectories, vital trends, medication patterns, and clinical notes — so teams will have time to act before a delay.

How long does implementation take?

Our goal is weeks, not the 12–18 months legacy integration-first vendors require. We're designing the platform so a typical pilot can be live on a single unit within a few weeks of kickoff.

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We'll send research and product updates as we head toward launch — no noise.

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