Temporal Variations in Bed Occupancy Rates and Estimated Nurse Staffing Requirements in Intensive Care Units: A Cross‐Sectional Study

ABSTRACT Background Temporal variations in bed occupancy rates are an important determinant of nursing workload in intensive care units (ICUs). However, few studies have characterised these patterns or incorporated them into estimates of nurse staffing requirements. Aims This study aimed to describe weekly variations in ICU occupancy rates and illustrate nurse staffing requirements under scenarios based on occupancy rates. Study Design A cross‐sectional study analysed data from patients admitted to ICUs at a tertiary hospital in Seoul, South Korea, between 2022 and 2023. Generalised additive mixed models (GAMMs) characterised nonlinear occupancy patterns. Nurse staffing requirements were estimated at 1‐min intervals under two staffing scenarios: nurse‐to‐patient ratios of 1:1 (Scenario 1) and 1:2 (Scenario 2) in a 20‐bed unit. Results In total, 25 872 hourly observations from 6147 ICU patients were analysed. The mean occupancy rate was 83.2% in medical ICUs and 60.5% in surgical ICUs. The GAMMs showed nonlinear hour‐of‐week patterns ( p < 0.001), with estimated occupancy rates varying by 6.66 percentage points in medical ICUs (79.91%–86.57%) and 23.57 percentage points in surgical ICUs (48.83%–72.41%). Under Scenario 1, the mean number of nurses required was 16.6 in medical ICUs and 12.1 in surgical ICUs. Staffing requirements remained within ±15% of the mean in medical ICUs but exceeded the upper limit for 13.08 h in surgical ICUs (Wednesday 10:53 PM–Thursday 11:57 am) and fell below the lower limit for 25.80 h (Saturday 4:27–9:19 PM and Sunday 12:50 PM–Monday 9:44 am). The difference between the highest and lowest staffing requirements per shift was 1.2 nurses in medical ICUs and 4.3 nurses in surgical ICUs under Scenario 1, compared with 0.6 and 2.2 nurses, respectively, under Scenario 2. Conclusions Monitoring ICU occupancy at hourly levels may inform nurse staffing planning. Relevance to Clinical Practice Hospital administrators may consider these temporal patterns when allocating nursing resources.