This blog post is a part 3 of our inpatient nursing staffing series. See “Using EHR Data to Optimize Inpatient Staffing” and “Leveraging Nursing Experience to Optimize Staffing” for previous posts in the series.  

The decisions that a hospital makes or fails to make regarding staffing can have dramatic effects on access to care, customer service, operating costs, and staff retention. The art of balancing staffing supply and patient demand is a critical component of healthcare delivery. Many studies suggest that both patient and job satisfaction are linked with nurse staffing levels.

As quoted from  a 2009 study by Kutney-Lee and colleagues:

“Patients’ reports of satisfaction are higher in hospitals where nurses practice in better work environments or with more favorable patient-to-nurse ratios.”

Determining Full-Time Equivalents (FTEs)

In this blog post, we will explore important considerations when staffing inpatient hospital units to meet patient demand. Analyzing required staffing levels in terms of full-time equivalents (FTEs) provides a comparison point for measuring level of availability. For instance, a 40-hour work week, 1 FTE could be 1 staff member at 40 hours per week or 2 at 20 hours per week each, etc.   

Schedule Structure Considerations

The structure of a given staff schedule can significantly impact how FTE needs are met.  In some cases, the schedule and it’s shifts are set and unmovable due to personal and/or seasonal constraints and preferences. However other times there may be opportunities to optimize staff schedules based on patient demand patterns. The visual above provides a breakdown of key schedule structure considerations.

Recommendations: Balancing Under and Over Staffing

Rather than analyzing a patient census at a single point in time, it is more effective to aggregate historical data and use that to understand a full picture of intraweek variability. Patient demand can be summarized by grouping and averaging hour-of-week demand.  The balancing act of staffing is to staff high each unit enough that workload can be completed safely and meet time constraints. In addition, it is important to minimize over-staffing, which is costly in terms of labor hours.  

The “sweet spot” for staffing is often a higher percentile of demand – around the 60th to 90th percentile.  On one end of the spectrum, if staffing is set to meet average demand, understaffing may be significant and result in staff not being able to keep up with workload. On the other end, staffing to the maximum number of beds on a unit, generally results in significant over-staffing, which is costly.  When attempting to narrow down the  percentile of demand it is important to consider:

Accounting for Benefits

Staff benefits are an important consideration of any FTE calculationA staffing model should include days allocated for vacation, sick, training and any other non-patient care days. Typically, around 10-15% should be added to the staff needs to provide a buffer for benefits and finalize FTE needs. 

Putting it into Action

These FTE considerations and calculations give hospitals insight into the total number of staff needed to cover workload on a given unit.  This number provides a useful guide for the number of staff that should be hired.  Having the right level of staff will allow for appropriate staffing levels throughout the week and coverage for vacation, sick and administrative time, while maintaining an appropriate quality care for patients and employee satisfaction, while also minimizing over-staffing costs. 


About the Author

Tiffany Naughton is a Senior Healthcare Analyst at IPS with over 7 years of experience. Working to provide actionable insights to clients through data mining and analysis, modeling, and designing visualizations and reports, her experience has involved projects throughout several areas of healthcare including operating room, obstetrics, pharmacy, emergency departments, and inpatient units.  Tiffany holds degrees in Management Information Systems, Operations Management, and Quantitative Methods. 

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