Research, guides, and conversations on capacity, coordination, and AI in the hospital. More arriving as we approach launch.
A data-driven look at where bed-days are really lost — and how predictive orchestration changes the math.
Read the paper →What to ask vendors before you sign — integration timeline, data access, and the BAA.
A walkthrough of the clinical signals behind disposition prediction, with live Q&A.
We'll publish bed-day and length-of-stay outcomes from our first hospital partners.
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.
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.
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.
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.
We'll send research and product updates as we head toward launch — no noise.
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