The last time we talked about nurse staffing, we discussed that not all patients are created equally, and the needs of one patient will fluctuate over the course of an inpatient stay.

Using electronic health records we can harvest patient data to adjust for an individual patient’s acuity at various points in time to understand nurse staffing requirements. In part 2 of our nurse staffing series, we look at how to further refine staffing calculations by accounting for the differences in nursing experience levels. 

A Deeper Dive into Staffing Calculations 

It is fairly intuitive that a unit full of high acuity patients would need more nurses than unit of low acuity patients. Now, say in our hypothetical hospital there are two units with similar numbers of patients with similar acuities. One of the units is comprised of mostly 1st and 2nd year nurses, the other unit is staffed by nurses who mostly have more than 10 years of experience. Even by holding the patients and census constant we wouldn’t expect the same optimal nurse to patient ratios to apply to each unit in that the more experienced nurses should be able to handle a higher patient workload. So how do we account for this? 

Similarly to calculating a patient’s acuity score, it is also possible to assign a proxy for nursing ability. One of the more common scales is Benner’s Stages of Clinical Competence. It is more subjective than simply looking at years of experience as we did in the fictional hospital above.

Benner’s Stages

In short the stages of competency recognize that more experienced nurses will gain efficiencies in their decision making by being able to look at the whole situation and synthesize the most important elements. They can also draw on past experiences to intuitively expect certain events and be prepared how to handle them.  

There is subjectivity in assigning nurses to a category. The resulting categorization may not always be perfect. Despite this potential imperfection, it is better than having the same expectation from every nurse in regards to ability. This assessment is typically done by a supervisor or manager.  

Scaling Based on Competency 

The next step is to determine how to scale nursing capacity based on competency. Returning to our hypothetical hospital, let’s assume a typical (meaning average acuity patient and a nurse rated as competent) overall nurse to patient ratio of 1:4. A table like the one below should be constructed with the input of nursing management with an understanding of the patient mix on their unit, but this is one example: 


In practice, it is less likely that the actual number of patients deviates significantly from 4 in the example above. This is most likely accounted for in terms of individual nursing assignments with more experienced nurses taking a higher percentage of the complicated patients and the more novice nurses taking a higher percentage of the less acute patients.  

The Daily Balance 

Nurse managers and charge nurses are already taking these factors into account when doing assignments and looking at opportunities to pull nurses to cover short staffed units.  However, most of them are doing this in their heads.  The best practice is to have tools that automatically calculate patient acuity and interface with nurse schedules and rosters to understand if a unit is over or understaffed at a given point in time.  This way, you are empowering your nurse managers with the information needed to make the best staffing decisions for your patients. 

About the Author

Bill Ferris has been at IPS since 2010, and has been working in healthcare focusing on analytics, modeling, and performance improvement for over 20 years. His past experience includes projects focused on obstetrics, emergency departments, perioperative services, outpatient clinics, ancillary services, and inpatient units in both the private sector and military medicine. He holds degrees in Industrial Engineering and Information Technology Management. Currently he is the Director of Professional Services at IPS. He also really likes to fish before heading to the office.

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