Fusia provides health systems with a shared operating layer that visualizes capacity, discharge readiness, and escalation bottlenecks, enabling teams to coordinate actions and free up beds more efficiently.
Funding
Funding not disclosed
Founders
Product
Problem
Hospital inpatient units often experience hidden discharge delays and bottlenecks that obscure capacity constraints, leading to prolonged bed occupancy and inefficient patient flow. Decision makers lack a unified, real‑time view of discharge readiness, escalation points, and bed pressure, resulting in ambiguous handoffs and slower interventions.
Solution
Fusia offers a shared operating layer that aggregates data on discharge readiness, placement bottlenecks, and capacity escalation into a single, real‑time dashboard. The platform visualizes the entire inpatient flow picture, highlighting where momentum stalls and which actions will free the most beds. By presenting a coordinated operational story, it reduces ambiguity for COOs, CMOs, and nursing leaders, enabling faster, confident decisions without adding handoff risk. The system routes escalations to the appropriate owners and surfaces early discharge signals, allowing teams to prioritize interventions that directly improve throughput.
Target Audience
Primary customers are hospital executives (COOs, CMOs) and nursing leaders responsible for inpatient capacity, as well as case‑management and bed‑control teams that manage daily discharge and flow operations.
Features
- Unified real‑time dashboard displaying bed pressure, discharge barriers, and active escalations in one view
- Early identification of discharge readiness with visual cues for pending actions
- Automated routing of escalation alerts to the responsible case‑management or bed‑control owner
- Integrated capacity analytics that prioritize interventions based on potential bed recovery impact
- Role‑based access ensuring leadership, throughput teams, and case managers see the same operational truth
- Designed specifically for inpatient flow, aligning with existing hospital workflows and constraints