I received a letter from the University of Chicago Medical Center explaining that effective Jan 2016; they will no longer accept BCBS.
The announcement took me by surprise. Not because the hospital was dropping an insurance plan- but because they were dropping a major plan, BCBS.
BCBS has a significant market share in Chicago; which translates to a lot of patients having BCBS as their insurance carrier.
I can only imagine why the hospital decided to drop BCBS, but I think I can say with a fair amount of certainty that the decision must have been difficult for stakeholders of the hospital. Undoubtedly dropping such a large plan would affect a lot of patients, but also, shake up the hospital’s income.
CAN A PRACTICE AFFORD TO DROP A PLAN?
I worked with a practice that was in a similar situation. The partners wanted to drop an insurance plan, but they had questions they wanted to answer before pulling the trigger, so to speak.
For example, one of the questions was how many patients would they potentially lose and how significant would be the financial impact if they dropped the insurance plan?
To help them answer their questions, I worked with the practice manager to create a simple spreadsheet that I call an insurance distribution sheet. Below is a version of the spreadsheet already completed.
To build the spreadsheet, we needed 3-data sets from the practice’s practice management system. Those three data sets were:
- Number of Patient Seen by Insurance Plan
- Gross Charges by Insurance Plan
- Net Receivables by Insurance Plan
The practice management system we were working with did not provide these data sets in one clean report. We had to run individual reports and enter the values into the spreadsheet.
Once the data was aggregated, we added a simple formula to translate the results into percentages. And the results is what the example above shows.
For those that are unfamiliar with Excel, click HERE to see a brief overview of how to calculate the percent of the total.
WHAT DO THE COLUMNS MEAN?
The first column is the insurance company patients had at the time of service. Percent of patients represents the ratio between all the patients seen, versus the patients seen with the corresponding insurance company. For example, let’s say the practice saw 1000 patients and of those, 300 had BCBS.
300 / 1000 = .3*
(*) BCBS represented 30% of the patients seen
Like percent of patients, percent of charges is the ratio of the practices gross charges divided by the gross charges corresponding to each insurance company. Example. Let’s say the practice billed $1,000,000. Of that million, BCBS represented $250,000.
250,000 / 1,000,000 = .25*
(*) Percent of charges for BCBS is 25%
The percent of receivables column follows the same math as percent of patient as well as percent of charges. And the cents/$ column calculates how many cents on the dollar the practice is collecting from the payor.
INTERPRETING THE GRAPH
Let’s look at BCBS and read across from left to right.
We see BCBS has 40% in the percent of patient column. Meaning, of all the patients seen, 40% had BCBS as their primary insurance. The next column is percent of charges. We see the BCBS represented 45%. This indicates that 45% of gross charges for the practice was billed to BCBS.
Percent of receivables is the next column over. It indicates that the revenue from BCBS accounted for 50% of the practice’s total income. And the revenue averaged 73 cents on the dollar. Another way to read it is, for every $1 billed to BCBS, the practice received 73 cents.
In contrast, let’s look at UHC. Only 8% of all the patients the practice saw for the period were UHC patients. UHC represented 9% of the practice’s revenue, and they averaged 60 cents on the dollar.
WHAT CAN WE GLEAN?
With an analysis like this, the practice can begin to find concrete answers to their pressing questions. For example, if UHC was the plan they were planning to drop, the sheet is able to show them what the impact would be from both a patient standpoint and financial standpoint.
UHC represents 10% of their patient panel. Which would have to leave the practice if they drop the plan, taking with them 9% of the practice’s revenue.
If the plan in question is BCBS, the numbers tell a different story. Fifty percent of the practice’s revenue would walk away with 40% of their patient panel.
Another observation is that Medicaid accounted for 37% of patients seen; but the State’s insurance plan accounted for 24% of the practice’s revenue. Something worth pondering.
HOW MUCH IS THE SHORTFALL?
For the sake of argument, let’s say UHC is the plan the practice was considering dropping. Doing so they would lose 9% of their revenue. This is not insignificant. If practice revenue is 1-million dollars, 9% represents $90,000. If practice revenue is 5-million, 9% is near $500,000. It’s less money no matter how you look at it.
PREPARING FOR THE SHORTFALL
When the doctors I was working with realized how much they’d lose, they got cold feet.
Here is what I explained to them…. the practice doesn’t have to see the same amount of patients to recuperate the 9% revenue shortfall. In fact, the practice can see fewer patients and still make up the revenue shortfall. How so?
Because of the cents on the dollar.
BCBS pays .73cents for every dollar billed. That’s 13cents more than UHC. By filling the schedule with better paying plans, like BCBS, Aetna or HFN, the practice will recuperate the 9% revenue loss faster because they are making more per patient than they would treating a UHC customer.
NOT ALWAYS SO CLEAR
Admittedly this graph does not give you a comprehensive picture. There are potentially other variables that a practice may consider. However, in the case of the practice that I worked with, this analysis was all they needed to answer their questions and move forward.
One last thing before you move one… don’t focus on the numbers you see on the graph and use them to compare with your practice numbers. Focus instead on the method, the process and the math with your numbers. Deal?
The practice reached out to the payer to negotiate better rates. Armed with the data, they felt empowered (not at the mercy of the payor) and firmly request payment increases. The payer agreed. And they signed a contract that was competitive.