Case Study 1-10843
IET delivered a nursing staffing model designed to enhance flexibility and meet the patient demand exactly as it happens. The improved model will take the hospital from the 75th percentile to the 25th percentile in NHpPD; saving over $4.0 million dollars annually in nursing salaries.
A well respected university teaching hospital with approximately 1,900 employees.
IET worked with a team of nurses and nursing administrators to map out the current staffing model. Using historical data, IET measured performance to the defined current state model and found that demand drivers did not match the actual staffing levels. The client was consistently staffing at the upper limits of the demand drivers creating an overstaffing condition for parts of the day.
IET investigated the effects of overstaffing to see if there was any clinical enhancement by having additional resources available. IET found that the patient to nurse interaction was the same with similar outcomes whether there was an overstaffing condition or an appropriate staffing condition. This proved that it is mutually beneficial for the patient, nursing staff and the hospital’s bottom line to match the staffing level to the demand drivers appropriately at all times of the day.
IET found that patient admissions and discharges are very predictable and as such, the demand drivers could be accurately planned for. Using this information and specific clinical diagnosis needs, IET developed a staffing model maximizing flexibility through adjustable staffing levels on a 2 hour basis and planning for known periods of increased activity.
The improved staffing model expects to save $4.0 million in nursing staffing salaries annually and drive the client form the 75th percentile into the 25th percentile in terms of NHpPD.