Key takeaways
- A capacity simulator projects patient-occupied beds and resources for each facility over a horizon you choose, from current occupancy trends and expected demand.
- Scenario runs show how capacity holds up if admissions rise, length of stay changes, or a unit closes, so you can plan before a surge.
- H2O Driverless AI builds the census and length-of-stay forecasts that feed the simulation.
- A capacity simulator is an operational planning tool, not a clinical one, and patient data never has to leave your boundary.
Plan beds and staff before a surge arrives
Your bed plan, staffing grid, and elective schedule are set days or weeks ahead. When demand rises faster than expected, from a seasonal wave, an outbreak, or a regional event, the gap shows up as boarding, delayed transfers, and overtime.
A single forecast is not enough when the future is uncertain. You need to see a range: what occupancy looks like if admissions rise, if patients stay longer, or if a unit has to close.
Most capacity reports look backward, one facility at a time. Operations, nursing, and patient-flow leaders need the same forward view, and the chance to test decisions against it.