NUR 4280 Module 4 Staffing and Budget Analysis Example

Paying Overtime for a Predictable Peak: A Staffing and Budget Variance Analysis for an Observation Unit

Student Name

Bachelor of Science in Nursing, Thomas Edison State University

NUR-4280: Leadership and Management In Nursing

Mentor Name

Month Day, Year

Paying Overtime for a Predictable Peak: A Staffing and Budget Variance Analysis for an Observation Unit

Our observation unit finished the last quarter with an overtime bill far above budget, and the nurse manager asked the charge nurses to help explain why. The explanation turned out to be simple: our staffing pattern assumes a steady census, but our census rises sharply every afternoon and evening, and we cover the rise by holding nurses over or calling them in at overtime rates. This paper describes the unit's staffing plan, analyzes the overtime variance, links staffing to patient safety evidence, and proposes a cost-neutral change to shift times. The figures are rounded from a composite unit and are used to show the method.

The Staffing Plan and the Census Curve

The unit has 22 beds and is staffed for a target ratio of one registered nurse to four patients, with a charge nurse who carries no assignment. Each 12-hour shift, day and night, is budgeted for five staff nurses, a charge nurse and two patient care technicians. That plan works when the census is near 20. The problem is the shape of the day. Most discharges happen between 0800 and 1100, after morning test results return, and most admissions arrive from the emergency department between 1400 and 0100. On a typical weekday the census falls to about 12 by late morning and rises to 21 or 22 by early evening.

At a census of 12 at 1000, five staff nurses carry fewer than three patients each. At a census of 22 at 2000, five nurses would carry more than four each, so the charge nurse asks a day nurse to stay or calls in an extra nurse for the evening hours. The staffing grid treats the shift as one block, while the work arrives in a curve. National staffing principles treat staffing as a decision that follows the number of patients and what they need hour by hour (American Nurses Association, 2020), not set once per shift, and our unit's pattern shows why that principle matters.

The Overtime Variance

The quarterly budget allowed 200 hours of registered nurse overtime, at an average overtime rate of $72 per hour, for a budgeted overtime cost of $14,400. Actual overtime was 640 hours, or $46,080, producing an unfavorable variance of $31,680. Penner (2017) recommends separating a personnel variance into its causes before acting on it, typically volume, the number of patients served; rate, the price paid per hour; and efficiency or use, the number of hours used per unit of work. Our patient volume for the quarter was within 3 percent of budget, so volume does not explain the variance. The base hourly rate did not change. Nearly all of the variance is a use variance in the form of premium-rate hours: we bought the right number of hours at the wrong time and paid time-and-a-half for the difference.

Reviewing the timecards confirmed the pattern. Of the 640 overtime hours, about 520 fell between 1900 and 2300, either as day nurses held over or as night nurses called in early. The remaining hours were spread across sick calls and one week with an unusually high census. The overtime is not random. It is the price of a predictable four-hour peak.

Why Staffing at the Peak Matters for Safety

The cost is not the only reason to staff the evening peak properly. Needleman et al. (2011) followed nearly two hundred thousand admissions at one academic center and linked every exposure to a badly understaffed shift, any shift running a full eight or more RN hours below plan, with a slightly higher hazard of death; exposure to a shift with unusually heavy admissions and discharges raised the hazard about twice as much. The study was observational and set in a large academic medical center, so it cannot be applied number for number to an observation unit. Its relevance lies in the second finding: our evening hours are exactly the high-turnover period it describes, with admissions arriving faster than discharges leave. Covering those hours with exhausted nurses on the last hours of a held-over shift is not a safe way to meet the peak.

A Cost-Neutral Proposal

I propose converting one of the five day-shift 12-hour positions into a mid-shift from 1100 to 2300. The change adds no hours; it moves twelve hours of an existing position four hours later. From 0700 to 1100, four day nurses would cover a census that is usually 12 to 16, within the target ratio. From 1100 to 1900, five nurses would be on as before. From 1900 to 2300, the mid-shift nurse would join the five night nurses, giving six nurses for a census of 20 to 22. The peak would be covered at straight time by a nurse at the start of a shift rather than at overtime by a nurse at the end of one.

If the mid-shift removed even three quarters of the evening overtime, about 390 hours a quarter, the saving would be roughly $28,080 a quarter at the overtime rate, with the base hours unchanged. The plan carries risks. A day with an unusually heavy morning would be short a nurse until 1100, so the charge nurse would need authority to start the mid-shift early. The position may be hard to fill, since some nurses dislike late finishes, so I suggest offering it first to volunteers and rotating it otherwise. Success would be measured by overtime hours between 1900 and 2300, the number of shifts below target staffing, and the share of shifts in which a nurse was held over.

Conclusion

The unit's overtime variance came from a staffing pattern that ignores the shape of the census. Breaking the variance into volume, rate and use showed that the unit was buying the right number of hours at the wrong time. A mid-shift moves existing hours to the period of highest need, should reduce overtime substantially, and matches staffing to the high-turnover hours that the safety evidence identifies as most risky. A budget variance, read carefully, is often a description of how work actually arrives on a unit.

References

American Nurses Association. (2020). ANA's principles for nurse staffing (3rd ed.). American Nurses Association.

Needleman, J., Buerhaus, P., Pankratz, V. S., Leibson, C. L., Stevens, S. R., & Harris, M. (2011). Nurse staffing and inpatient hospital mortality. New England Journal of Medicine, 364(11), 1037-1045. https://doi.org/10.1056/NEJMsa1001025

Penner, S. J. (2017). Economics and financial management for nurses and nurse leaders (3rd ed.). Springer Publishing.