Beating Competitors With Analytics
If you can demonstrate better performance quantitatively, you can beat your competitors, get more revenue, increase profits, and maybe even sell your company and retire.
What Is “Analytics”?
Analytics is a hot area, and it seems like every conference has presentations on analytics and data, but how many are actually useful? We are focusing on a very practical application of analytics in RCM, which is how it can help you win deals and grow your business.
What does analytics actually mean? Is this just a different name for reporting? Don’t people also call it “business intelligence,” or BI? People seem to use many of these terms interchangeably, and it seems fashionable currently to call reporting “analytics,” as if you can charge more money for this.
Is this just a competitive issue—my competitor claims to have analytics, so I should, too?
And, hey, the client won’t know the difference if we call reporting “analytics.” For a definition of analysis, Merriam-Webster offers this: “a detailed examination of anything complex in order to understand its nature or to determine its essential features: a thorough study.” Therefore, reporting is definitely not analysis, nor analytics, nor is analytics data, data warehousing, interfaces, spreadsheets, or some pretty graphs.
Why Analytics Matters
If analytics is the process of solving a complex problem using data, which is the definition we will use, then your clients absolutely care about analytics. One of the tools often used in Six Sigma is the 5 Whys. Using this technique, what follows is the chain on why your clients care about analytics:
- Because your clients want to know what is going on with their business using data
- Because they don’t want to rely solely on their gut
- Because they want a detailed understanding of complex problems in their business and want to identify opportunities
- Because they want to fix the problems and seize the opportunities
- Because they want to be successful, win more deals, cut costs, get promoted, etc.
- Because they want to make more money
Not Your Strong Suit?
You’re not alone. Our industry has historically stressed “knowledge” coming from experience. I believe this may derive from a time when it was easier to possess a large preponderance of knowledge about billing simply from doing it (i.e., on-the-job-training).
Most medical billing services (and medical billers) have succeeded by being able to deeply dive into a problem by calling payers, examining EOBs, and solving a problem with a difficult payer. However, this isn’t a data-driven approach. Historically, you didn’t need a data-driven, analytical approach to solve problems. However, there is only so much someone can solve swimming in a sea of data. If one of your billers encountered a dozen denials of a certain type amid 300 over the course of several weeks, would they be able to identify the pattern? We now need analytics in order to perform revenue cycle management successfully.
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How does one apply analytics? Six Sigma tools and techniques for process improvement were pioneered at Motorola in the late 1980s. It was popularized by Jack Welch at GE in the 1990s while I was working at GE Medical Systems. One of the central tenets is what is known as DMAIC, which is the data-driven improvement cycle that is so beneficial for service operations and so rarely employed in our industry. It is an acronym that stands for Define, Measure, Analyze, Improve, and Control.
Start from the Problem Statement
We don’t have time for a complete deep dive to learn Six Sigma, but focusing on defining the problem well is often the key to success, which is the first part of DMAIC. What are you trying to solve? I can’t tell you how many times I have talked to a billing company or a billing manager when trying to analyze something and I get presented with a report. When I ask what question this report is supposed to answer, I get something completely different than what we’re trying to solve. If you don’t agree on the question, you’re certainly not going to find the solution.
Beating the Competition
You believe you’re better than the competition? By nature of you being a part of HBMA (a selection bias), that is likely true. But how do you prove it? The answer is with analytics. If you can demonstrate better performance quantitatively, you can beat your competitors, get more revenue, increase profits, and maybe sell your company and retire.
How do you measure it? If you are like 99% of the billing companies, consultants, and billing managers we have encountered over the years, at the top of the list will be some measure of accounts receivable. It might be AR days, AR DSO, percent of claims 60+ and 120+, or some other variation. In my presentation at HBMA 2019, I’ll give you the answer, and I think you will be surprised.
One question we frequently get (and even some skepticism) is whether you really quantify RCM performance. I can’t tell you how many times I have heard someone in a billing company tell us you cannot; it’s far too complex. For millennia people thought a machine would never be able beat a human at chess. Alan Turing first posited that a computer would one day beat humans back around 1950, and he was met with a lot of skepticism (and even some ridicule) by chess masters. But, in 1997, Deep Blue beat the reigning world champion Gary Kasparov. And there are now legions of examples of things that people thought could not be done with technology that now are taken for granted. Another example that might be even more relevant (i.e., quantifying performance and predicting results) comes from baseball. Ever heard of “MoneyBall”? No one thought you could predict which players would perform better using data, and yet this has now become legend and even a movie.
Our industry has been saying that we can’t even measure our own performance. Does that sound acceptable? If a computer program (designed by humans) can beat grand masters at chess or even predict which baseball player will hit more runs, then we are kidding ourselves if we believe we cannot calculate which medical billing company performs better.
We have entered a new era in revenue cycle management where referrals are no longer going to be enough to win new clients and retain existing clients. Analytics is the key to beating your competition. The future will belong to medical billing companies that know how to harness analytics to perform well and demonstrate it so that they win business and retain clients.
Sean McSweeney is a serial entrepreneur and currently founder and CEO of Apache Health, a healthcare RCM predictive analytics company. Prior to Apache Health, McSweeney co-founded and was the president of Cobalt Health, a leading national laboratory revenue cycle management (RCM) company with over 125 employees. Cobalt Health was acquired in 2015 by a private equity group doing a rollup. He is an avid believer in lean startup methodologies, rapid prototyping, and testing to validate market hypotheses. He can be reached at email@example.com