- A census forecast gives you a predicted bed count by facility and unit for each day of a horizon you choose, refreshed as new admissions and discharges arrive.
- A large healthcare provider runs a 15-day census forecast in production across every facility in North America.
- H2O Driverless AI automates the time series feature engineering and model search, and explains which drivers moved each forecast.
- Protected health information never has to leave your boundary across four deployment options.
You staff today for patients who arrive next week
Your staffing grid, your agency requests and your elective schedule are all set days before the patients who fill them arrive. When the plan rests on last year's average and a charge nurse's instinct, the gap shows up as boarding in the emergency department, delayed discharges and unbudgeted overtime.
Most health systems already run some form of census report, but it looks backward, one facility at a time, and rarely reaches the unit level where staffing decisions are made. A forecast that covers every facility, every unit and every day of the horizon gives operations, patient flow and nursing leadership the same view of demand.
How hospital census forecasting works
The forecast predicts future occupancy from past occupancy, the calendar and the scheduled work you already know about.
Step 1: connect the history
Pull admissions, discharges, transfers and length of stay by facility and unit from the EMR you already run. The forecast sits on top of the EMR; it does not replace it.
Step 2: set the horizon
Choose how many days ahead each forecast looks and at what level: system, facility or unit.
Step 3: build and compare models
H2O Driverless AI creates lag, rolling and calendar features through automatic feature engineering and ranks candidate models on held-out days.
Step 4: explain the forecast
Interpretability methods show which drivers moved each forecast, so your planners can check it against what they see on the floor.
Step 5: run it in shadow mode
Run the forecast beside your current planning process first, and compare it with actual census every day before anyone acts on it.
Step 6: deploy and monitor
H2O MLOps serves the forecast on a schedule, watches for model drift and flags when a model needs retraining.
An operational tool, not a clinical one
A census forecast changes where your planners start, not who decides. Protected health information never has to leave your boundary, in any of four deployment options: on-premises, air-gapped, private cloud or cloud.
Results
A large healthcare provider runs a 15-day census forecast in production across every facility in North America.