With the COVID pandemic, the nursing shortage has figured prominently in the news cycle. There have been many reports about the nursing shortage, severe understaffing, hospitals enacting crisis care measures, and even hospitals closing services due to nursing staff shortages. People are asking, “How did this happen?”, “How did we get here?” and “How do we fix it?”.
With my 23 years of experience in nurse staffing and scheduling, I decided to dig into researching the nursing shortage, how COVID has exacerbated understaffing, and what, if anything, can be done to help improve staffing. I’ve made some rather interesting and troubling discoveries over the past several months.
Many factors contribute to the nursing shortage, and we will cover some of these factors in future blog posts. But, today, I want to focus on a flawed budget process being used by some hospitals that increases their risk for understaffing. The two most interesting (and troubling) aspects of this issue are that this flawed budget methodology has been around for at least 30 years, and we have two high-profile professional organizations in healthcare that have been teaching this process to nurse managers for the past four years.
While the ideas I will propose on this blog to address budgeting and staffing problems will not solve the nursing shortage, they can go a long way in helping us better understand, model, and predict staff shortages. They will also provide us with data that nursing and finance leaders can use to better inform their decisions about resource allocation.
Understanding the nursing budget process and terminology
Before I can explain the budget flaw to you, I need to cover some basics of nursing budgets to make sense in the end. I’ll be keeping some of the terminology and concepts at a fairly high level for this discussion.
I want to point out that there are multiple mathematical approaches to creating nursing budgets. These different methodologies may tackle the calculations from slightly different angles but will generate the same number of employee hours needed in the end.
Nursing budgets typically start with calculating the number of patient care hours needed to deliver a specified level of care for a given number of patients. The “level of care” may be a nurse-to-patient ratio, the desired Nursing Hours Per Patient Day (NHPPD) target, or some other metric determined by nursing leadership. The “given number of patients” is often the average number of patients or average census of the unit. These patient care hours may be referred to as productive time, patient care time, or direct care time in budget-speak.
Once we’ve determined how much staff is needed for patient care, we need to hire additional positions to provide coverage or replacement to ensure we always have enough resources for patient care when someone needs time off for PTO, jury duty, maternity leave, education, etc. These non-patient care hours may be referred to as non-productive time, indirect care time, or replacement time.
For budget discussions on the blog, we will use the following definitions:
- Direct Care Time (or just Direct Time): All hours where the employee is working in a patient care capacity. Often referred to as productive time.
- Replacement Time: All hours where the employee is NOT working in patient care capacity. Often referred to as non-productive time.
I believe the terms “Direct Care Time” and “Replacement” do a better job of conveying the budgetary concepts behind them compared to “productive” and “non-productive” time.
A split of around 85% Direct Care Time (also known as productive time) and 15% Replacement Time (also known as non-productive time) is a good starting point for many budgets.
A Full-Time Equivalent or FTE is typically the primary unit of measurement in a nursing budget. An FTE refers to the number of hours worked by an employee during a pay period to be considered a full-time employee. For employees that work on a weekly pay period, five eight-hour shifts give the employee 40 hours per week which equals 1.0 FTE. Multiplying 40 hours per week times 52 weeks per year gives us 2080 hours for a 1.0 FTE position for a year. FTE is an aggregator of hours that standardizes calculations for resource needs.
In nursing, it’s common to have employees working in something other than a 1.0 FTE position. For example, an RN working three 12-hour shifts each week would be counted as a 0.9 FTE. Nurses are frequently paid on a 2-week pay period, translating into working 80-hours per 2 week period to be considered full-time. By dividing the RN’s 72 hours over those two weeks by the 80 hours per full-time equivalent, we get 0.9 FTE for that nurse’s position.Welch, T. D., & Smith, T. (2020). Understanding FTEs and nursing hours per patient day. Nurse Leader, 18(2), 157–162. https://doi.org/10.1016/j.mnl.2019.10.003
What’s the difference between scheduling and staffing?
The difference between scheduling and staffing is important for this discussion.
Scheduling is what nurse managers do when they create a future schedule. The nurse manager defines the employees to be paid each day on a schedule. It’s not just “worked time” that a manager has to schedule. An employee may be scheduled for a patient care shift or a non-patient care shift such as PTO, leave, education time, etc.
Staffing is the fine-tuning of the scheduled resources for the day to match the resource needs. This may involve floating staff to other units that are short-staffed, placing an employee on-call if additional admissions are expected later, or even canceling an employee’s shift if the census has dropped significantly and too much staff is scheduled. Staffing is typically done on the “day of,” but units may need to make staffing adjustments over a multi-day period such as an upcoming weekend or holiday if operational data strongly suggests adjustments will be needed.
Tying it all together, the budget determines your baseline schedule, and your schedule becomes the foundation of your daily staffing. Nurse managers must understand how their budget variances impact their ability to create safe and effective schedules. If a nurse manager is posting a future schedule alongside an overtime signup sheet, there’s a high likelihood that they will have some staffing challenges ahead of them. If multiple nurse managers in a facility are posting their schedules along with overtime signup sheets, that’s a big red flag! This may indicate that the nurse managers don’t have the right tools to accurately determine the amount of non-patient care time they can schedule while preserving the resources needed for patient care. It also may indicate that their facility is using the flawed budget process that we’ll be discussing in this post.
Building a nursing budget
Grab your calculator, and let’s step through creating a budget for a nursing unit.
Our mock unit will have an average census of 24 patients, and we want to budget for a 1:4 nurse-to-patient ratio. All of the nurses are working 12-hour shifts.
With an average census of 24 patients each day, we need six nurses on the day shift and six nurses on the night shift for all days of the week for a 1:4 nurse-to-patient ratio. All nurses are working 12-hour shifts. Arranging all of this information in a spreadsheet makes it easy to calculate that we need a total of 1008 nursing hours to provide the desired level of care (a 1:4 nurse-to-patient ratio) to our given volume of 24 patients each day. Dividing 1008 hours by 40 hours per FTE tells us we will need 25.2 FTEs just for patient care. These are our Direct Care or Productive FTEs. All of these FTEs are needed for patient care. If one nurse on the schedule above takes a PTO day, we will be short-staffed for that day.
We now need to hire additional FTEs so that we have enough nurses available to schedule to maintain the 1:4 ratio when someone is scheduled for a non-patient care shift.
According to William J Ward, Jr., professor of Health Policy and Management at Johns Hopkins and author of Healthcare Budgeting and Financial Management, 2nd edition, budgeting approximately 85% of your total hours for patient care is a good starting point for many units. Ward, W. J., Jr. (2015). Health care budgeting and financial management, 2nd edition (2nd ed.). Praeger. Since we’ve calculated the patient care hours (Direct Care Time) that should comprise the 85% of our total budgeted hours, we now need to calculate the remaining 15% of budgeted non-patient care hours (Replacement Time).
Professor Ward states that one proper way to calculate Replacement FTEs is to divide the Direct Care FTEs by the Direct Care (or Productive) percentage. This formula gives us Total FTEs. To determine just the Replacement FTEs, we subtract the Direct Care FTEs from the Total FTEs.
Professor Ward cautions that we should
Avoid the mistake of merely adding 15% of non-productive [replacement] time back to the [direct care FTEs]… doing so will short-change the FTE count and leave a manager short-staffed even before the fiscal year begins.
Professor ward further states:
…15% of nonproductive [or replacement] time is not 15% of [direct care FTEs], but rather 15% of [total FTEs]. [Total FTEs] is not a known value at the start of the calculations. It must be determined by division using the productivity [or Direct Care] rate. This is reminiscent of the old grade school ratio problems such as “10 is to 20 as X is to 40, solve for X.” Even those skilled in budget calculations often make the mistake of saying, “Let’s add 15% for nonproductive [replacement] time.” But this approach is clearly incorrect and will always result in a budget that lacks sufficient staff.
My research suggests that many hospitals are likely using the wrong formula for calculating their Replacement Time. This flawed formula results in a 2% to 4% shortfall in expected FTE hours and increases the facility’s risk of understaffing.
Grab your calculator and check my math as we step through these examples.
Let’s first look at the incorrect way of calculating replacement time.
If we take the 25.20 Direct Care FTEs from the mock unit above and “add 15% for nonproductive [replacement] time” by multiplying the Direct Care FTEs by the Replacement percentage, we get 3.78 replacement FTEs.
Direct Care FTEs x Replacement % = Replacement FTEs
25.20 x 0.15 = 3.78 Replacement FTEs
Direct Care FTEs + Replacement FTEs = Total FTEs
25.20 + 3.78 = 28.98 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 13.04%.
Replacement FTEs / Total FTEs = Replacement FTE Percentage
3.78 / 28.98 = 13.04%
According to Professor Ward, we should instead be dividing the 25.20 Direct Care FTEs by the Direct Care percentage of 85% to determine Total FTEs. Subtracting the 25.20 Direct Care FTEs from the 29.65 Total FTEs gives us 4.45 Replacement FTEs.
Direct Care FTEs / Direct Care % = Total FTEs
25.20 / .85 = 29.65 Total FTEs
Total FTEs – Direct Care FTEs = Replacement FTEs
29.65 – 25.20 = 4.45 Replacement FTEs
When we divide the 4.45 Replacement FTEs by 29.65 Total FTEs, we get the desired 15% Replacement FTEs.
Replacement FTEs / Total FTEs = Replacement FTE Percentage
4.45 / 29.65 = 15.00%
How This Budget Flaw Contributes to Understaffing of Nursing Resources
Let’s compare the results of the calculations above.
Using the incorrect Replacement FTE calculation formula results in only 13.04% Replacement FTEs instead of the expected 15.00%. The difference between the correct and incorrect calculations results in a -2.25% or -0.67 FTE shortfall when using the flawed formula. What this means mathematically, is that if you schedule 15% of your available FTE hours for non-patient care shifts when you only have 13.04% replacement available, you would come up short on the hours needed for patient care.
If we take the 1159.20 Total Hours from the Incorrect Formula budget and erroneously schedule 15% of those hours in non-patient care shifts, that will leave us 22.68 hours short of the 1008.00 hours that we need for patient care.
Total Hours x 15% = Replacement (Non-Patient Care) Hours scheduled
1159.2 x 0.15 = 173.88 Replacement Hours scheduled
Total Hours – Replacement Hours scheduled = Available Direct Care Hours
1159.2 – 173.88 = 985.32 Available Direct Care Hours
Available Direct Care Hours – Budgeted Direct Care Hours = Direct Care Hours Variance
985.32 – 1008 = -22.68 Direct Care Hours Variance or -1.89 12-hour shifts per week
What often happens when nurse managers make schedules is that they will approve time-off requests before the patient care shifts are scheduled by the manager or via employee self-scheduling. These approvals are often done without an assessment of how much non-patient care time can be scheduled without impacting the resources needed for patient care. Overscheduling non-patient care shifts above what is mathematically available is how schedules get posted alongside an overtime sign-up sheet.
If we ran a mock productivity report for 4 weeks’ worth of the above scenario, the nurse manager would be hitting their target of 15% of their hours allocated for non-patient care shifts. However, they would be just over 90 hours or 7.6 12-hour shifts short of what is needed for the patient care shifts. These missing shifts would go unfilled or need to be backfilled by per-diem staff, float pool staff, floats from other units, overtime, or travel RNs.
In the example from our mock unit above, I’ve mathematically demonstrated that scheduling 15% of our resources for non-patient care shifts when we only have 13.04% resources available will result in a shortfall of 22.68 hours each and every week for our patient care shifts. I’ve also provided mathematical proof of Professor Ward’s explanation of the flawed budget formula.
This example is for only one unit. All of the other units in our mock facility very likely used the same incorrect formula. When we do the analysis across all units, the shortfall in patient care resources can be substantial. If you have 10 of our mock units in a facility using the same flawed budget process will generate a weekly shortfall of 226.8 hours or nearly 19 12-hour shifts. Expanding these facility numbers to cover a 4-week period yields a 907.2 hour or 75.6 12-hour shift shortfall. Again, these missing shifts would go unfilled or need to be backfilled by per-diem staff, float pool staff, floats from other units, overtime, or travel RNs.
Keep in mind that I’m only focusing on the RNs in these scenarios. It is l likely that the incorrect budget formula has also been applied to nursing assistants and any other support staff included in the budget calculations.
I’ll discuss the impact of this error across facilities in more detail in an upcoming blog post.
You may have noticed a small discrepancy between the hours variance values in the tables versus the calculations. The hours variance in the table is demonstrating the overall shortfall between the two budget methodologies. In the calculations, I’m demonstrating the shortfall that will be experienced if the nurse manager mistakenly believes that they have 15.00% replacement resources available instead of their actual 13.04%
I’ll also cover some of the finer details of the overall shortfall in a future blog post.
The Evidence for the Prevalence
As I was reviewing the literature on nursing budgets and healthcare finance, I ran across some examples of the flawed formula that had been published. I spoke with Professor Ward to discuss my findings. He recommended reaching out to someone in nursing or healthcare leadership that could help to get the word out about the error and how to correct it.
As I’ve continued my research, I’ve found the incorrect formula in journal articles, conference presentations, textbooks, consultant materials, and, most recently, verified that the incorrect formula is being taught in a workshop for nurse managers by two high-profile professional organizations. While it’s hard to say how widespread the flawed budget methodology is, the evidence suggests that it is not uncommon.
Over the past several months, I’ve spoken to a number of healthcare finance professionals, CNOs, DNPs, PhDs, C-suite healthcare executives, healthcare innovators, and healthcare influencers. The majority of the responses have largely fallen into 3 categories:
1: We’ve always done it this way!
Two CNOs that I approached regarding the error dismissed my findings by saying “We’ve always done it this way!”
I also found an example of the flawed formula in a recent journal article by someone considered to be an expert on nursing budgets and productivity. When I wrote to the author, who was also a former CNO, I explained my understanding of the error, provided them with the information from Professor Ward’s book, and included mathematical proof demonstrating the error. The author’s response was not only “I’ve always done it this way!”, but that they had also worked with 3 large healthcare consulting firms and they did it that way, too!
In the late 1990s and early 2000s, I had an opportunity to work with a budget and productivity consultant at two different hospitals. This small consulting group was formed in 1991 and they were well known for helping hospitals develop their budgeting and scheduling processes. I still have the workbooks from this consulting group’s workshops. Upon reviewing their recommended approach to budgeting, I discovered that they had been using the incorrect formula as well. Since these consultants had to have learned about budgeting from someone else, it’s safe to say that this error has been around for at least 30 years.
2: Fixing this will cost too much money!
There were several people I talked to that said “Robert, you’re going to have a hard time getting people to listen to you because fixing this is going to cost money.” They were right.
Going through the process of fixing this budget error means that many facilities will discover that they have fewer resources available than needed to meet the intended budget targets. In cases where hospitals seek to hire nurses to fix their understaffing problem, they may find they have to potentially hire dozens more than they had originally planned.
Fixing this will end up costing money. Nurses are the bedrock of our healthcare system. In a recent study, 40% of nurses indicated they were considering leaving healthcare due to burnout, increased workload, and COVID-19 associated stresses.Sinsky, C. A., Brown, R. L., Stillman, M. J., & Linzer, M. (2021). COVID-related stress and work intentions in a sample of US health care workers. Mayo Clinic Proceedings. Innovations, … Continue reading. The study also estimated that it would cost 1.2 to 1.3 times the nurse’s salary to replace them.
3: That’s interesting…
Many responses could be categorized as a “Well, that’s interesting…” and not much else. And some that responded in this way also suggested that fixing this will cost too much money.
Nursing budgets, and staffing and scheduling operations are very specialized areas of expertise. It’s difficult to easily explain some of the concepts to people that have never been exposed to the process. To thoroughly understand some of the concepts and problems also requires stepping through tedious mathematical formulas.
It looks like this budget problem could be an issue for some hospitals. The evidence continues to suggest that the flawed budget process is not uncommon.
I believe the driving force behind many of the “That’s interesting…” responses is that they weren’t sure what we should or could do about it. It’s a complex problem with far-reaching implications.
Finance and Business Skills for Nurse Managers
In the nursing literature, there are many articles that talk about how to create a nursing budget. However, there is little in the literature that discusses how to operationalize a budget and create safe and effective schedules.
I was initially excited to discover that the Association of Nurse Leaders (AONL) and the Healthcare Financial Management Association (HFMA) had teamed up to teach a Finance and Business Skills for Nurse Managers class.
The class was taught by a VP of Nursing, representing AONL, from a hospital in the eastern United States, and a Director/Finance Executive from HFMA. The VP of Nursing stated that the two of them had been teaching the class together twice a year for the past four years.
Unfortunately, when it came time to cover the budget calculations, they were using the incorrect formula in the class. Here is the excerpt from the FTE calculation slide. I added the highlighting for the incorrect formulas, the red boxes around the percentages, and blue text replacement calculations.
After the class, I reached out to the instructor from HFMA to discuss my concerns and findings regarding the flawed formula. They were initially open to discussing the problem, but once I explained the details of the error, they stopped responding to my emails.
The VP of Nursing was much more receptive to hearing my explanation of the error. They promised to review my findings.
With the increased sense of urgency around understaffing and burnout in healthcare today, the response to this information from nursing and healthcare leadership has been disappointing. Especially when presented with an objective mathematical proof of the error and suggestions on how the budget process and staffing could be improved.
If you can’t measure it, you can’t improve it.
So, now, I’m bringing this information to the healthcare community to raise awareness and, hopefully, spark a discussion. Nurses are exceptionally resourceful and creative and we have a deep understanding of many of the challenges we have in healthcare. Upcoming blog posts will provide greater detail and understanding of these budget calculations and concepts as well as additional background on other key factors in the nursing shortage.
It is my hope that everyone from bedside RNs to nurse managers to C-suite executives will gain a deeper understanding of how budget variances impact staffing capacity. Once we reach a collective understanding of these concepts, we can begin brainstorming on how to begin solving some of these problems.
If we can’t measure it, we can’t improve it. Correcting this flawed formula opens the door to create some simple tools that would create transparency about staffing capacity for nursing staff and empower nurse managers to make data-driven decisions when creating their schedules. There is a significant opportunity for nursing informatics professionals in the budgeting, staffing, and scheduling space in nursing. Given the right data, Informatics nurses well versed in staffing and scheduling operations and finance can proactively identify units at risk for staffing problems and provide guidance to nursing and finance leadership on the root causes of the identified issues. Given the many quality, safety, and financial metrics negatively affected by understaffingShin, 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.
If you’re a nursing informatics professional that is involved with nursing budgets or staffing and scheduling operations, let’s connect and chat! If you’re someone interested in brainstorming solutions for addressing the nursing shortage, understaffing, and burnout, I’d love to hear from you, too.
Let’s get the conversation started!
|↑1||Welch, T. D., & Smith, T. (2020). Understanding FTEs and nursing hours per patient day. Nurse Leader, 18(2), 157–162. https://doi.org/10.1016/j.mnl.2019.10.003|
|↑2||Ward, W. J., Jr. (2015). Health care budgeting and financial management, 2nd edition (2nd ed.). Praeger.|
|↑3||Sinsky, C. A., Brown, R. L., Stillman, M. J., & Linzer, M. (2021). COVID-related stress and work intentions in a sample of US health care workers. Mayo Clinic Proceedings. Innovations, Quality & Outcomes, 5(6), 1165–1173. https://doi.org/10.1016/j.mayocpiqo.2021.08.007|
|↑4||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|