Costs and consequences of using average demand to plan baseline nurse staffing levels: a computer simulation study

Area of Science:

• Healthcare Management
• Nursing Workforce Planning
• Patient Safety Research

Background:

• Nurse staffing levels are critical for patient care quality and safety.
• Low registered nurse numbers correlate with adverse patient outcomes and safety incidents.
• Current nurse staffing tools often recommend average demand, potentially leading to suboptimal levels.

Purpose of the Study:

• To simulate and compare different nurse staffing establishment strategies.
• To estimate costs and understaffing/overstaffing rates associated with various staffing approaches.

Main Methods:

• Utilized patient and roster data from 81 hospital wards across four Trusts.
• Developed a computer simulation model for nurse staffing.
• Assessed outcomes including understaffed/overstaffed patient shifts and cost per patient-day.

Main Results:

• Staffing to average demand resulted in 32% of shifts being critically understaffed.
• Increased baseline staffing reduced understaffing to 21% of shifts.
• Flexible staffing reduced over/understaffing but was risky with low baseline staffing unless temporary staff were unlimited (high cost).

Conclusions:

• Basing nurse staffing on average demand may increase understaffing compared to higher baseline levels.
• Flexible staffing is most effective with sufficient permanent staff.
• Low permanent staffing with reliance on temporary staff risks patient care quality and safety.