Automate and optimize hospital bed allocation
Every hospital has a system that records admissions and a bed board that shows what's free. Few have anything that decides which bed each incoming patient gets, so that the right equipment, specialty, and room rules are respected for the whole stay. Let's solve that.
One solve assigns every stay to a bed for every night
Timefold assigns patient stays to beds across departments and rooms as one optimization problem. Overlapping stays, gender room rules, department age limits, and required equipment are enforced as hard constraints, so every assignment is safe. Within those rules, the model assigns as many patients as possible, then matches specialty, preferred equipment, and preferred room size.
Where Timefold goes beyond the bed board
Four things decide whether a bed plan works. Timefold bakes them into the model.
Safe by construction
Age limits, gender rules, and required equipment are hard rules, so no plan puts a patient in a room that can't care for them.
The whole stay, not just tonight
Each stay is planned across all of its nights, so a free bed today doesn't block an incoming patient tomorrow.
Specialty where it matters
Patients go to departments that treat their specialty first, and to rooms with the equipment they prefer.
Gaps you can see
When beds run out, stays are left unassigned and visible instead of being squeezed into the wrong room.
Hospital beds are a scarce, shared resource
Every admission competes for the same beds, rooms, and equipment. A bed assigned without the full picture blocks the next admission, splits a department, or leaves a patient waiting elsewhere.
Per bed, per night
Overlapping stays need a different bed, so one early decision limits every later one.
Admissions and discharges change the picture
A plan that worked this morning can block an admission this afternoon.
Apply to every stay
Gender, age, equipment, and specialty all have to fit, which is slow to check by hand.
A full ward backs up the hospital
When the right bed isn't free, patients wait in the emergency department or a hallway.
Constraints the model expresses today
One patient per bed per night
Two stays never share a bed on overlapping nights.
Gender room rules
Female patients never land in male-only rooms and male patients never land in female-only rooms. In same-gender rooms, patients of different genders never share the room on overlapping nights.
Department age limits
A patient is only placed in a department whose minimum and maximum age they fall within.
Required equipment in the room
A patient only gets a room that has every piece of equipment they require, such as oxygen or telemetry.
Every patient gets a bed where possible
The model assigns as many stays as it can. A stay with no legal bed is left unassigned instead of breaking a hard rule, weighted by its number of nights.
Right specialty department
Patients go to a department that offers their specialty, preferably one where that specialty is the first priority.
Preferred equipment
Rooms with the equipment a patient prefers win over rooms that lack it, weighted by how many nights the patient stays.
Preferred room size
Patients who prefer a smaller room avoid rooms with more beds than their preferred maximum.
Admitted patients stay put
Stays marked as pinned, such as patients who are already in a bed, keep that bed while the model plans everyone else around them.
When scheduling works, everything works.
Less waste. More control. Teams that trust the plan.