Skilled nursing facility 'haves' and 'have nots' — a financial journey
As a result of changing referral patterns, increasing regulations and myriad of other factors, the current financial environment poses a great threat to some skilled nursing facilities while creating opportunities for others.
A recent article published by McKnight's explored exactly this topic in reviewing the 32nd edition of the CLA Skilled Nursing Facility Cost Comparison Report. The report brings together close to a billion data points from 2016 financial and operational metrics to help long-term care operators understand how they stack up.
If we step back and take an even broader view, we find that, as time goes on, the data suggests that the separation of the high-performing and low-performing skilled nursing facilities is becoming larger. Exploring trends in occupancy rates, facility size and payer mix enables us to determine if there are any correlating factors that impact financial performance.
For the purposes of this analysis:
• High performers are defined as those facilities with an earnings before interest, depreciation, and amortization (EBIDA) and days cash on hand in the top 25th percentile for their most recently filed cost report (as of December 31, 2016).
• Low performers are those facilities with an EBIDA and days cash on hand in the bottom 25th percentile for their most recently field cost report (as of December 31, 2016).
EBIDA and Days Cash on Hand
The chart below illustrates the financial journey of high and low performers from the tail end of the great recession through 2016, as told through our previously mentioned indicators, EBIDA and days cash on hand. The left vertical axis tracks Days Cash on Hand as plotted by bar graphs and the right vertical axis tracks EBIDA as plotted by horizontal lines.
It's pretty clear the high performers were able to weather the storm and continue to enhance their profitability and cash position, whereas the low performers have seen erosion of profits and cash.
Occupancy and Total Beds
In investigating the possible drivers of performance, we started by exploring occupancy and facility size. Logic tells us that occupancy drives profitability, but we were curious to understand how facility size correlated with financial performance (chart below).
The left vertical axis tracks median occupancy as plotted by bar graphs and the right vertical axis tracks median total number of beds as plotted by horizontal lines. We were not surprised to see that high performers have higher occupancy. In our view, customers and referral sources are becoming more astute and they are choosing higher performing skilled nursing facilities as a result. In turn, the increased occupancy drives future financial results.
The data also suggests that high performing skilled nursing facilities tend to be larger than their low performing counterparts by 30% to 40%. When plotting the data, a triangle emerges from North Dakota to Texas to Ohio.
Low performers are indicated in blue and the high performers are indicated in green circles which increase in size depending on their relative count. This triangle contains approximately 60% of the low performers, but only 32% of the U.S. population, which may suggest that there are many smaller markets with lower populations that are struggling.
By taking the analysis one layer deeper, the payer mix differences between the high and low performers suggests that referral sources are crucial.
The low performers rely on the government for reimbursement 75% of the time, whereas the high performers rely on governmental reimbursement approximately 60% of the time. This is not to say that a high mix of governmental reimbursement is inherently bad, but could suggest that, as the industry evolves, two distinct skilled nursing models may emerge — one that is receiving more profitable referrals and is financially stable, and another that lacks those referrals, and will therefore require a much lower cost structure to survive.
While these national trends are interesting, understanding the trends in your local market is critical to drive meaningful business decisions.
Many providers either lack the data needed to make informed decisions, or they do not have the resources to analyze their data in a way that allows them to fully recognize what the data tells them. To enable them to understand their performance in comparison to their peers, CLA organized nearly 1 billion financial and quality measures from every skilled nursing facility in the country into a resource called CLA Clarity.
Organizing the vast data set allows providers to explore how their facility compares to specific peers in its local market. This data, when paired with the knowledge of how to analyze this data for organizations throughout the country, creates the ability to transform data into meaningful insight that influences financial performance.
Whether you're trying to understand your own cost structure relative to similarly situated organizations, identify potential affiliation or acquisition targets, or even figure out what questions to ask, access and understanding of this vital data within CLA Clarity can help.
The information contained herein is general in nature and is not intended, and should not be construed, as legal, accounting, investment, or tax advice or opinion provided by CliftonLarsonAllen LLP to the reader. For more information, visit CLAconnect.com.
Jake Slavik is a senior associate within the senior living practice at CLA, a national professional services firm.