What is bed occupancy?

Bed occupancy shows what fraction of a hospital's beds hold patients. It is a simple measure of how busy a hospital is and how much room it has for sudden arrivals. Managers watch it because very high occupancy brings delays and risk, while very low occupancy means resources are being paid for and not used.

How it works

The formula is occupancy = occupied beds / available beds, often averaged over a period. Occupancy is linked to arrivals and length of stay: if patients arrive faster, or stay longer, more beds are filled at any moment. This follows Little's law, where the average number in the system equals the arrival rate times the average time spent.

Waiting and delay grow quickly as occupancy nears 100%. With random arrivals, a hospital running at 95% has little room to absorb a surge, so patients wait in emergency departments and planned procedures get cancelled. For this reason many planners aim well below full, balancing cost against safety.

Example

Say a ward has 50 beds, receives 10 admissions a day and each patient stays 4 days on average. By Little's law, the average number of occupied beds is 10 x 4 = 40, so occupancy is 40 / 50 = 80%. If length of stay rises to 4.8 days, occupied beds become 48 and occupancy is 96%, leaving only 2 free beds for random surges. A change of 0.8 days in the stay has taken the ward from comfortable to strained. These numbers are an illustration.

How to model it in Machinations

Use a Source for admissions, a Pool for occupied beds with a capacity, and a Delay or Drain for discharge after the length of stay. A Register divides occupied by total beds. Add a Queue for patients waiting when the Pool is full. Make admissions and stay length Levers, then Play many times and chart occupancy and waiting.