Nursing Budget Flaw Impact on Understaffing at the Hospital and Regional Levels

by | Jan 18, 2022 | Demystifying Understaffing, Nurse Staffing and Scheduling, Nursing FTE Budgets, Nursing Informatics, Nursing Innovation, Nursing Shortage, Understaffing | 0 comments

In my blog post, Flawed Nursing Budget Process Increases Understaffing Risk, I spelled out the details behind an incorrect formula in a nursing budget process used by some hospitals. This post will expand on how this small error can translate into significant resource shortfalls when applied across a facility or even multiple hospitals in a city or region. These shortfalls increase a facility’s risk of understaffing and burnout. We’ll also show how this error can also impact citywide and regional markets and why it’s crucial to understand how widespread use of this flawed budget calculation is.

TNIB Medical Center – Mock Stepdown Unit

For this example, we’re going to use a slightly larger unit.

TNIB - Mock Stepdown Unit
TNIB – Mock Stepdown Unit

This unit has an average census of 30 patients. It is budgeted for a 1:3 nurse-to-patient ratio except for Tuesday and Wednesday when there is a resource nurse for 10 hours to assist with admissions, discharges, and transfers. To deliver the desired level of care, we need to schedule ten nurses to work 12-hour shifts for the day and the night shifts.

Here we can see that we’ll need 1700 RN hours per week to provide the desired level of care for the average daily census of 30 patients. Dividing 1700 hours by 40 hours/FTE gives us 42.5 FTEs needed just for patient care.

For this unit’s budget, we’re also going to plan for 85% of our FTE hours for Direct Care (or productive) time, and the remaining 15% of our FTE hours should be for Replacement (or non-productive) time. We’ll start with using the correct formula for calculating Replacement FTEs.

According to Professor Ward, we should divide the 42.50 Direct Care FTEs by the Direct Care percentage of 85% to determine Total FTEs. When we subtract the 42.50 Direct Care FTEs from the 50 Total FTEs, it gives us 7.5 Replacement FTEs.

Direct Care FTEs / Direct Care % = Total FTEs

42.50 / .85 = 50.00 Total FTEs

Total FTEs – Direct Care FTEs = Replacement FTEs

50.00 – 42.50 = 7.50 Replacement FTEs

When we divide the 7.50 Replacement FTEs by 50.00 Total FTEs, we get the desired 15% Replacement FTEs.

Replacement FTEs / Total FTEs = Replacement FTE Percentage

7.50 / 50.00 = 15.00%

Impact of an Incorrect Nursing Budget Formula on Staffing Capacity

Now, let’s examine the impact of the nursing budget flaw on our larger step-down unit.

If we take the 42.50 Direct Care FTEs from the mock stepdown unit above and incorrectly “add 15% for non-productive [replacement] time” by multiplying the Direct Care FTEs by the Replacement percentage of 15.00%, we get 6.38 replacement FTEs and 48.88 Total FTEs

Direct Care FTEs x Replacement % = Replacement FTEs

42.50 x 0.15 = 6.38 Replacement FTEs

Direct Care FTEs + Replacement FTEs = Total FTEs

42.50 + 6.38 = 48.88 Total FTEs

When we check our math on the Replacement FTEs, we find that instead of having 15% of our Total FTEs as Replacement FTEs, we only have 13.05%.

Replacement FTEs / Total FTEs = Replacement FTE Percentage

6.38 / 48.88 = 13.05%

TNIB - Mock Stepdown Unit - Budget Flaw Impact on Understaffing
Comparison of correct and incorrect Replacement FTE calculations

Using the incorrect Replacement FTE calculation formula results in only 13.05% Replacement FTEs instead of the expected 15.00%. The difference between the correct and inaccurate calculations results in a -2.24% or -1.12 FTE shortfall when using the flawed formula. If you schedule 15% of your available FTE hours for non-patient care shifts when you only have 13.05% replacement available, you will not have enough hours needed for patient care.

If we use the 1955 Total Hours from the Incorrect Formula budget and erroneously schedule 15% of those hours in non-patient care shifts, we will be understaffed by 38.25 hours.

Total Hours x 15% = Replacement (Non-Patient Care) Hours scheduled

1955 x 0.15 = 293.25 Replacement Hours scheduled

Total Hours – Replacement Hours scheduled = Available Direct Care Hours

1955 – 293.25 = 1661.75 Available Direct Care Hours

Available Direct Care Hours – Budgeted Direct Care Hours = Direct Care Hours Variance

1671.75 – 1700 = -38.25 Direct Care Hours Variance or -3.19 12-hour shifts per week

Expanding these numbers to cover a 4-week scheduling period, our mock stepdown unit nurse manager would be looking at a deficit of 153 hours needed for patient care. That deficit translates into understaffing of 13 unfilled 12-hour shifts on the schedule. These shifts will likely be unfilled or be worked by unbudgeted resources such as floats, overtime, or even travel RNs. This scenario is how schedules are often posted alongside an overtime sign-up sheet.

The Snowball Effect of an Incorrect Nursing Budget Formula on Understaffing

So far, we’ve been focusing on the impact of this incorrect nursing budget formula on understaffing for individual units. All nursing units in the hospital likely use the same flawed formula as part of the budget process for the nursing division.

For a unit that needs 50 total RN FTEs, we calculated that the incorrect budget formula would result in a loss of 38.25 direct care hours. The hours deficit will grow linearly as you add FTEs so long as the direct care and replacement percentages remain the same. Let’s calculate the variance per 100 RN FTEs to see if we get a 76.50 direct care hours shortfall. We will use the same parameters of 85% of total hours for patient care time (Direct Care Time) and 15% of total hours for non-patient care time (Replacement Time).

Here, we’ve calculated the correct and incorrect FTEs, hours, and percent distribution of hours.

Correct FTE Calculations

Direct Care FTE / 0.85 = 100 Total FTEs
85 / 0.85 = 100
Total FTEs – Direct Care FTEs = Replacement FTEs
100 – 85 = 15
Replacement FTEs / Total FTEs = Replacement %
15 / 100 = 15.00%

Incorrect FTE Calculations

Incorrect FTE Calculation
Direct Care FTE * 0.15 = Replacement FTEs
85 / 0.15 = 12.75
Direct Care FTEs + Replacement FTEs = Total FTEs
85 + 12.75 = 97.75
Replacement FTEs / Total FTEs = Replacement %
12.75 / 100 = 13.04%

Let’s see what happens when our nurse manager schedules 15.00% of their available employee hours as non-patient care shifts when only 13.05% replacement resources are available.

Direct Care Hours Variance

Total Incorrect Formula Hours * 0.15 = Non-Patient Care Hours Scheduled

3190 * 0.15 = 586.50

Total incorrect Formula Hours – Non-Patient Care Hours Scheduled = Available Direct Care Hours

3190 – 586.5 = 3323.50

Available Direct Care Hours – Budgeted Direct Care Hours = Direct Care Hours Variance

3323.5 – 3400 = -76.50

As predicted, we end up with a 76.50 hour weekly shortfall of patient care hours per 100 RN FTEs required due to the flawed replacement formula.

In the table above, the overall shortfall is 2.25 FTEs representing 90 hours. All FTEs are subject to the 85%/15% split, and 85% of 90 hours is 76.5 hours. The remaining hours lost result in the loss of 13.50 hours of non-patient care time. In addition to contributing to understaffing, the budget error also reduces the hours available to provide time off for staff.

The Scaling Impact of an Incorrect Nursing Budget Formula Variance on Understaffing

Using the incorrect nursing budget formula variance per 100 RN FTEs, we can estimate the impact of the error on understaffing across a facility or multiple facilities in a geographic region that are using the flawed budget methodology.

Scaling of Incorrect Nursing Budget Formula Variance
Scaling of Incorrect Nursing Budget Formula Variance

A loss of 76.50 direct care hours per week per 100 RN FTEs due to the flawed budget formula becomes an annual shortfall of nearly 4,000 hours or over 330 12-hour shifts.

For a mid-sized medical center that requires 500 RN FTEs, the numbers are more dramatic:

  • A shortfall of 9.56 RN FTEs
  • A loss of 382.50 patient care hours, nearly 32 12-hour shifts worth of patient care time, per week
  • Which results in a 1,530 hour deficit of scheduled patient care hours representing a loss of over 127 12-hour shifts across a 4-week scheduling period
  • If we annualize these numbers, this mid-sized medical center would realize a loss of nearly 20,000 patient care hours that were intended to be budgeted for but were not available to be scheduled.
  • This medical center would also be looking at to backfill 1657 12-hour shifts that should have been populated by unit-based resources had they used the proper budget calculation.
  • Resources such as float pool, unit-to-unit floats, overtime, per-diem agency staff, and travel RNs are expended in order to backfill the schedule to bring it up to the desired baseline budgeted level of care and staffing.
  • Filling these scheduling deficits with unbudgeted resources can have a significant negative effect on the finances of the hospital.
  • These resources then become unavailable to deploy in response to increases in patient volume and unplanned decreases in available staff such as a significant number of employees needing to quarantine for several days.
  • And, finally, if this facility doesn’t have the resources to backfill the holes in the schedule, the shifts will go unfilled, increasing the liklihood of an understaffing situation.

Regional Market Implications

As I mentioned in the evidence for the prevalence section of my Flawed Nursing Budget Process Increases Understaffing Risk post, the information I’ve collected indicates that this flawed budget process is not uncommon. If that is the case, we must consider the potential impact on nursing job markets in regions where multiple hospitals use the flawed formula. Many hospitals find it difficult to hire all the nurses needed and may not realize that they need dozens more positions than they originally planned.

For a city or region that required a total of 2,500 RN FTEs:

  • 47.8 RN FTEs would be lost to this error.
  • There would be a weekly deficit of 1,912 hours representing 159 12-hour shifts that needed to be filled.
  • Expanding the numbers to a 4-week scheduling period yields a shortfall of 7,650 patient care hours or 637 12-hour patient care shifts.
  • Annualized, this error would result in a loss of nearly 100,000 patient care hours that should have been availble to be scheduled.
  • There would also be over 8,200 12-hour patient care shifts that would need to be filled by unbudgeted resources.

That is a lot of potential missed patient care time.

While the original 2-4% shortfall sounds small, I believe I have demonstrated how the scaling of this error can become a significant operational concern for hospitals and regional healthcare networks. We must raise awareness of this flawed budget process to determine how widespread it is. It is also essential that we provide information and education to nursing and finance leaders on correctly calculating the desired number of replacement resources.

How Nursing Informatics Can Help Combat Understaffing and the Nursing Shortage

As I have mentioned previously, many articles in the nursing literature speak to creating a nursing budget. However, little in the literature discusses operationalizing a budget to develop safe and effective schedules.

Budgeting, staffing, and scheduling are all collections of related mathematical formulas. Some interesting insights become available once you understand the formulas and how they are linked across the concepts. Explaining the budget error has shown that we can reasonably model and calculate staffing capacity and the impact of budget variances on staffing capacity.

Correcting the flawed budget formula opens the door to creating new tools and educational material that can help to empower nurse managers to make data-driven decisions about their resource allocation. Nurse managers armed with the correct data, tools, and reports can take a more care-centric approach to scheduling their nursing staff by prioritizing the preservation of resources needed for scheduling patient care shifts. The data can provide transparency to unit staff regarding the amount of time off that can be reasonably granted each month without impacting the resources needed for patient care. The data can even help predict the amount of understaffing should managers decide to schedule more time off than the budget would allow.

These tools would also provide valuable data that could help to facilitate discussions between the nurse manager, their nursing leadership, and finance regarding resource needs and allocation. Even if a facility has a nurse staffing and scheduling system, there’s a good chance it doesn’t have all of the data, information, and reports needed to make fully informed decisions about staffing and scheduling. Nursing leaders can move from a reactive to a proactive position when dealing with nurse staffing and scheduling issues with the correct information.

Nursing informatics professionals with a solid understanding of budget, finance, and nurse staffing and scheduling concepts, as well as the math involved, could be formidable agents in a data-driven, evidence-based, care-centric approach to staffing and scheduling. Given the many quality, safety, and financial metrics negatively affected by understaffing[1]Shin, S., Park, J.-H., & Bae, S.-H. (2018). Nurse staffing and nurse outcomes: A systematic review and meta-analysis. Nursing Outlook, 66(3), 273–282. … Continue reading, even minor improvements in staffing could reap significant rewards for patients, patient care staff, and facilities.

Help Wanted: Healthcare Leaders Open to Innovative Approaches to Addressing Understaffing

There’s only so much that informatics nurses can do on their own. We need innovative and creative nursing and finance leaders willing to sit down and discuss new budgeting, staffing, and scheduling tools and strategies. In 2020, AONL, ANA, and HFMA put out a joint report titled The Business of Caring: Promoting Optimal Allocation of Nursing Resources. In this report, they identified five action steps to improve the allocation of nursing resources[2]Begley, R., Cipriano, P. F., & Nelson, T. (2020). Common ground: AONL, ANA, and HFMA Outcomes-Based Staffing Report Provides Guidance, Insights. Nurse Leader, 18(3), 216–219. … Continue reading:

  • Pioneer creative nurse staffing approaches. Optimize staffing using evidence-based approaches to help organizations make informed decisions, enhance workforce utilization, and improve outcomes.
  • Assess the impacts of new technology on all phases of care before, during, and after implementation. In some cases, improvements in certain outcomes may come at the expense of other elements of the care episode.
  • Work toward joint accountability. Addressing long-term challenges requires fierce collaboration, starting in the C-suite and diffusing throughout the organization.
  • Agree on shared principles. Workplace stresses on nurses and finance professionals have ripple effects ont he entire healthcare organization. These systemic stresses translate to principles for allocating appropriate nursing resources for patient care.
  • Promote interprofessional collaboration. The key to delivering high-value health care is collaboration among clinicians, health care administrators, and finance leaders. Interprofessional collaboration is predicated on relationship building. When finance and nursing professionals achieve a shared understanding of value and build solid working relationships that reflect insight into their respective workplace stresses, all health care team members, the organization – and most importantly, patients – will reap the benefits.

I’ve identified a significant factor in understaffing for some, possibly many, hospitals. I also have some innovative ideas on “pioneer[ing] creative nurse staffing approaches” through data and education. Correcting the 30-year-old budget formula error should be a top priority. Providing practical tools and education to nursing and finance leaders would help to “promote interprofessional collaboration” at all hospitals, not just the ones using the flawed budget process.

I am seeking bold and innovative nursing and finance leaders that are open to exploring new ideas and approaches to nursing workforce management. If you’re a nurse manager or a member of a scheduling committee for your unit and are struggling with understaffing, I’d love to talk to you, too.

References

References
1 Shin, S., Park, J.-H., & Bae, S.-H. (2018). Nurse staffing and nurse outcomes: A systematic review and meta-analysis. Nursing Outlook, 66(3), 273–282. https://doi.org/10.1016/j.outlook.2017.12.002
2 Begley, R., Cipriano, P. F., & Nelson, T. (2020). Common ground: AONL, ANA, and HFMA Outcomes-Based Staffing Report Provides Guidance, Insights. Nurse Leader18(3), 216–219. https://doi.org/10.1016/j.mnl.2020.04.007

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