The vast majority of injuries suffered by nursing home residents are the direct result of understaffing. Pressure injuries, falls, choking, dehydration, malnutrition, and unchecked infections are all caused by understaffing. Understaffing is intentional; a business model designed at the corporate level and forced on the facility. This business model is based on greed. Accepting this fact raises the value of nursing home cases. The progression is simple: the facility was understaffed, the decision to understaff was intentional, based solely on greed, and that decision killed your client.
The medicine in nursing home cases is just the mechanism to get into court; but the driving force for the case values are the “numbers.”
There are two major components to a nursing home case: 1) the abuse, neglect and injuries of your client, and 2) corporate malfeasance. This article focuses solely on the corporate malfeasance and understaffing in particular. Understaffing is perilous for defendants because the available data fully supports the proposition that the facility was understaffed, and that the understaffing was due to decisions made at the corporate level. Profits over People.
Bolstering a Nursing Home Case with Data
Two major avenues bolster a nursing home case with data. The first is an analysis of staffing information that establishes the level of staffing the facility reported to state and national agencies. You then compare this “reported staffing” to “expected staffing” (discussed below) to determine the degree of understaffing.
The other avenue is financial data for the facility. The financial data can be, and is, manipulated at the facility level. But a good evaluator can reverse the manipulation to show that the facility had plenty of money to correctly staff the facility, but they just chose not to. Discussion of the financial analysis component is outside the scope of this article, but I am happy to discuss it with anyone who wants more information on that subject.
Basics of the Staffing Analysis
The analysis is accomplished with basic math. We want to know how much staffing the facility had, how much should they have had and what the difference is. With that information, we can then determine what that difference was worth in dollars.
Reported Staffing is the amount of staffing reported by the facility.
Expected Staffing is the staffing needed to meet the acuity needs of each resident.
Minimum Staffing is the staffing needed to meet the minimum recommended staffing, generally, but may be different from the facility’s Expected Staffing.
Reported Staffing – Minimum Staffing = Over or Under staffing (generally)
Reported Staffing – Expected Staffing = Over or Under Staffing (specifically for this facility’s acuity level)
In practice, the analysis is very straightforward. To determine total reported staffing, you add the Registered Nurse (RN) time to the Licensed Practical Nurse (or “Licensed Vocational Nurse”) (LPN/LVN) time and the Certified Nurse Assistant (CNA) time. The total of the three classifications is your total direct care, in worked hours.
RN = 24 hours, LPN = 60 hours and CNA = 210 hours.
24+60+210= 294 hours of direct care.
To be relevant to a case it needs to be converted to Hours Per Patient Per Day (HPPD). To calculate this, take the total hours and divide by the census. In this example if the census was 82 residents, the math would be 294/82 = 3.58 HPPD. At this point, we know the facility was staffed at roughly 3.6 hours of direct care per patient per day. The HPPD for each nursing category can also be calculated by dividing the hours by census.
RN = 24/82 = 0.29 HPPD,
LPN = 60/82 = 0.73 HPPD
CNA = 210/82 = 2.56 HPPD.
The most recent literature on staffing indicates that the minimum for total staffing should be at least 4.1 HPPD. Academic articles by nursing care experts written on long term care staffing conclude the minimum staffing a nursing home should have for RNs is 0.75 HPPD, for LPNs 0.55 HPPD and that CNAs should be staffed at a 2.8 HPPD minimum. What we see in our example is standard “for profit” staffing; cut RN hours to almost nothing and slightly overstaff LPN hours to cover some of the RN understaffing. Since RNs are the most expensive, the facility wants to drop RN hours as low as possible to save as much as possible.
In this example, the facility was understaffing RNs by 0.46 HPPD, overstaffing LPNs by 0.18, HPPD and understaffing CNAs by 0.24 HPPD, for a total understaffing of 0.52 comparing reported staffing to minimum staffing.
The understaffing numbers appear small for a single patient, but in the aggregate across the facility they are substantial. In this example each resident is being shorted 0.46 hours of RN time per day, basically a half an hour per day. But across the entire facility that is 37.72 hours per day. How much work is not being done when you are missing almost 38 hours of labor in one day, or when you’re short 264 hours in a week? Across the year that is just under 14,000 hours. That’s seven full time RNs that this facility is shorting its patients, and at $37.71 per hour (U.S. Bureau of Labor Statistics) this facility saved $517,761 on RN staffing in one year. It gave some of that savings back with overstaffing LPNs but also saved more money by understaffing CNAs. It is common to find facilities that understaff in the $500,000-$1,000,000 range per year, occasionally more with bigger facilities.
If you want to zero in on the exact staffing needs at one specific facility over a specific time, the gold standard is to compare reported staffing to Expected Staffing. Expected staffing is determined using time studies conducted by CMS. The basic premise is that the facility is assessing each person using an evaluation tool called the Minimum Data Set (MDS), a 40+ page assessment document that lays out how much assistance the individual needs with eating, dressing, toileting, their medical diagnosis, and rehabilitation needs, etc. In Section Z, there is an acuity score for that individual. Prior to October 1, 2019, this was called a “RUG score”, it is now called a “Nursing Services Score”. The MDS is submitted to CMS and the acuity score sets the daily reimbursement for this resident.
Taking a step back, what we have here is the federal government asking the facility “how much care does this person need?” and the facility responding, “this resident needs X amount of care per day” to which the federal and state governments respond with a daily reimbursement to the facility. The rates are based on the understanding that the facility is going to meet the individual needs of each resident; therefore, each reimbursement is directly tied to the amount of time that is expected to care for an individual with that acuity. To staff significantly below expected staffing is fraud.
Expected staffing can be calculated if one has Section Z from every MDS done at the facility, starting six months before your client entered the facility, through the day of their discharge. This data shows when each resident entered and discharged from the facility, and what their acuity level was each day. That acuity level can be looked up in a table to determine how much RN, LPN and CNA nursing time that person needs per day. Then you add all the nursing time associated with each resident, each day, divide by the number of residents in the building that day (census) and you will have the EXACT expected staffing for that facility that day.
This calculation will reveal the exact expected amount of RN, LPN and CNA time for each day, which can be compared against the facility’s reported staffing, to see exactly why your client fell on that Saturday or why your client developed that stage IV pressure wound in three weeks. If you use the hourly average cost of labor from the annual cost reports you will be able to explain to your mediator or jury EXACTLY how much money this facility pocketed in staff savings and how that directly, negatively, impacted your client.
Sources of Staffing Data
Payroll Based Journal
Arguably the best staffing data is held by CMS (The Centers for Medicare and Medicaid Services) through their Payroll Based Journal (PBJ) system. CMS started collecting PBJ data in January 2017 and it is usually available online 90 days after each quarter ends.
PBJ data includes daily census and daily staffing, broken down by RN, LPN, and CNAs. With this information one can determine the exact reported staffing for any day or length of time.
CMS Annual Cost Report
CMS requires each nursing home to file an annual cost report technically known as CMS Form 2540-10. CMS annual cost reports are subject to a FOIA request to CMS. It is a spreadsheet with sixty-six tabs, and while most of these tabs have no relevance to our cases, worksheet S-3-V contains staffing data. The data is aggregated for a year, so you will not be able to determine what the staffing was on a certain day, but you can see what the staffing was for the year. One caveat is that the data reported is Paid Hours, not Worked Hours. “Paid Hours” include vacation, sick leave and therefore will be an inflated number when you are analyzing for direct care hours as compared to PBJ data, which is worked hours. The annual cost report contains the facility census on Worksheet S-3 at row 1, column 7. Nursing administration hours are available on worksheet S-3, Part II, line 7.
To estimate Worked Hours from Paid Hours, deduct 8% from Paid Hours. The formula for that is Paid Hours * 0.92 = Worked Hours.
As mentioned above, the annual cost report includes average hourly wages paid to each classification of employee. This can be used to calculate the savings due to understaffing based on the actual pay scale used by the facility instead of using the national labor statistics. The hourly wages are located on the same lines as the hours paid information on Worksheets S-3-V and S-3, Part II.
Medicaid Cost Reports
Medicaid Cost reports are required by all states, each state uses a different form and collects different information. Most states do not collect staffing data. Notable exceptions are Arizona, California, Illinois, Oklahoma, and Pennsylvania who all collect good staffing data. Of these states all of them have cost reports online, except Oklahoma, which must be obtained by contacting the state and filing a request. You should check with your state Medicaid agency to see if your state collects staffing data, this is not an exhaustive list, and the reporting requirements change from time to time so there might be available data in your state.
Like the CMS cost report the staffing data contained within the Medicaid cost reports is annualized data, not daily staffing data. You also need to determine if it is Paid Hours or Worked Hours, some states conveniently collect both types of data.
Staffing in Discovery
Additional staffing data can be obtained in discovery. Use Requests for Production (RFP) to get the facility’s “punch detail”. This is the industry term for “timecards”. This will include the exact times each employee clocked in and out of the facility for their individual shifts and is normally be provided in a .pdf format. The data must be usable and needs to be in a spreadsheet. Instead of hand converting the .pdfs, request, and insist, that the production be in “native format” which will be .csv (standard spreadsheet) or .xlsx (Excel). Native format will allow for fast and efficient staffing analysis calculations.
Staffing schedules are useful to get 30,000-foot view of the staffing as it applies to different floors or units within the facility. Because the schedules are aspirational, they are not to be used for an exact staffing analysis. The fact that someone was scheduled does not mean they showed up for their shift, showed up on time or stayed the entire shift.
Budgets are critical to link the understaffing to corporate malfeasance. The budgets set the staffing. The facility employees may say they staff to acuity but that is rarely the case. Because they are staffing to a budgetary number dictated by corporate, they staff only to census. For each individual admitted to the facility they will staff an additional number of hours, no matter what that resident actually needs. Although this is a per se violation of CMS and state staffing regulations, the facilities will deny it. The budgets also establish corporate involvement in the day-to-day operational control of the facility.
Expected staffing reveals a lot about a facility, but it can be challenging to calculate. At the facility level, you must request production of all the data in Section Z for all Minimum Data Sets (MDS) that were performed in the six months leading up to your resident’s admission and continuing through their entire stay. Section Z is where the facility reports a final “coding” for the resident that tells Medicare how sick they are, and in turn, how much the facility gets paid for that resident. In short, it shows the acuity of each resident. You need the Section Z data for all of the residents in the facility, which can be produced without identifiers to be HIPAA compliant. With those codes, the acuity level can be looked up in a table to determine how much RN, LPN and CNA time that person needs per day. Doing this for every resident in the facility for each day your client was in the facility is a sizable undertaking, but the payoff is well worth the effort, as explained earlier.
To streamline authentication and admissibility, I suggest requesting the data, annual reports, etc. used in your analysis from the Defendants. If they balk, send what you’ve used with a request for admission asking them to authenticate it.
This analysis can be tedious and time-consuming. And most attorneys did not go to law school because they loved math. But the analysis is ammunition to question the Director of Nursing, the Administrator and corporate players about why they were not staffing to acuity. Ultimately, it will open the door to either discovery or testimony that lay the responsibility for your injury at the feet of the management company, the directors of the chain or possibly the owners themselves.
The vast majority of injuries sustained in nursing home cases can be directly traced to systemic understaffing. Your analysis of the corporate components and links to the management company’s involvement will show this was not an accident, nor an isolated incident. It can be very powerful to combine this intentional business model with testimony from your victim’s family and former employees about the effect of understaffing, e.g., call lights always going off, food served cold, and residents going unchanged.
Showing that understaffing was intentional, done to increase profits, with conscious indifference to the lives of residents changes your ho-hum nursing home case into a rock-star corporate malfeasance case.
1 Centers for Medicare & Medicaid Services (CMS). Report to Congress: Appropriateness of Minimum Nurse Staffing Ratios in Nursing Homes Phase II Final Report. Baltimore, MD: CMS; 2001. (See The relationship between nurse staffing levels and the quality of nursing home care, by Kramer AM and Fish R. Chapter 2, and Minimum nurse aide staffing required to implement best practice care in nursing facilities, by Schnelle JF, Simmons SF, and Cretin S, Chapter 3.)
2 Bostick JE, Rantz MJ, Flesner MK, Riggs CJ. Systematic review of studies of staffing and quality in nursing homes. JAMDA. 2006;7:366-376.
3 Harrington C, Dellefield ME, Halifax E, Fleming ML and Bakerjian D. Appropriate Nurse Staffing Levels for U.S. Nursing Homes, Health Services Insights 2020; Volume 13:1-14 https://journals.sagepub.com/doi/full/10.1177/1178632920934785
4 Centers for Medicare & Medicaid Services (CMS). Report to Congress: Appropriateness of Minimum Nurse Staffing Ratios in Nursing Homes Phase II Final Report. Baltimore, MD: CMS; 2001. (See The relationship between nurse staffing levels and the quality of nursing home care, by Kramer AM and Fish R. Chapter 2, and Minimum nurse aide staffing required to implement best practice care in nursing facilities, by Schnelle JF, Simmons SF, and Cretin S, Chapter 3.)
5 Institute of Medicine. Keeping Patients Safe: Transforming the Work Environment of Nurses. Washington, DC: National Academy of Medicine; 2004. [Google Scholar]
6 U.S. Department of Health and Human Services, Centers for Medicare & Medicaid Services (CMS). Medicare and Medicaid programs: reform of requirements for long-term care facilities (Final Rule). Fed Regis. 2016;81:68688-68872.
7 Centers for Medicare & Medicaid Services (CMS). State operations manual appendix PP − guidance to surveyors for long term care facilities (Rev. 11-22-17). https://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/GuidanceforLawsAndRegulations/Nursing-Homes.html.
8 American Nurses’ Association. Nursing staffing requirements to meet the demands of today’s long term care consumer recommendations from the Coalition of Geriatric Nursing Organizations (CGNO). Position Statement 11/12/14. www.nursingworld.org.
9 Table 2 (STM Classification System), Harrington C, Dellefield ME, Halifax E, Fleming ML and Bakerjian D. Appropriate Nurse Staffing Levels for U.S. Nursing Homes, Health Services Insights 2020; Volume 13:1-14 https://journals.sagepub.com/doi/full/10.1177/1178632920934785