Do you want to beat your competitors?


Are you sick of losing deals to medical billing companies that aren’t as good as you, but either have better sales and marketing or make promises that they can’t keep?  Are you still hoping clients will unsolicited refer more clients to you?  And to win new deals do you think you can just give “better” references?


Is your long-term goal to sell your rapidly growing billing company?  If it is, you need to be growing, and certainly not losing more clients via attrition than you are gaining.  I sold my prior billing company; and I’ll tell you how to do the same.


I have an upcoming presentation at the HBMA conference in September in Las Vegas titled “Beating Competitors with Analytics”.  Following is a sneak peak at some of what we will be discussing.



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.


But what does “analytics” actually mean?  Is this just a different name for reporting?  Wasn’t it the rage for a while to call reporting “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.


Or 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, nor some pretty graphs.



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 Why’s.  Using this technique, following is the chain on Why your clients care about analytics:


  • Because you clients want to know what is going on with their business using data
  • Because they don’t want to rely 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


Why billing companies should care:

  • You should want to give customers what they want
  • Customer satisfaction improves
  • Improved customer retention
  • Improved profitability
  • Attracting new clients and growing your business



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 dive into a problem deeply by calling payers, examining EOBs, and solving a problem with a difficult payer.  However, this isn’t a data-driven approach.  And 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 see 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.



So how does one apply “analytics”?  Six Sigma set of tools and techniques for process improvement and was pioneered at Motorola in the late 80s.  It was popularized by Jack Welch at GE in the 90s while I was working at GE Medical Systems and I was trained in Six Sigma at GE, in fact.  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, Control.



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’ agree on the question, you’re certainly not going to find the solution.



What question – if you had an answer – would allow you to make a material improvement in your medical billing company?  Or a material change in the performance for your client?  Diagnosing and solving complex problems using data is analytics.  Recall earlier in this article we discussed “knowledge”.  Knowledge isn’t dead, in fact it is more important and valuable then ever.  Let’s say we wanted to test the “knowledge” of one billing company compared to another, i.e. to quantify it.  Taking a simpler version of this, what about just within YOUR billing company.  Why would you do this?  Maybe you want your company as a whole to get more “knowledgeable” and so you needed a baseline to track against improvement over time.  We could devise a written test with questions and score how employees performed.  But “knowledge” is a feature, not a benefit.  The benefit of knowledge – presumably is that it allows increased collections performance for our clients.  Maybe we don’t care about knowledge specifically, we would define the problem as how do we measure the performance of a biller or collector, compare their performance over time, and compare them to other billers.


If you’ve done this (or tried), then you know how challenging it is to get it right.  Maybe you calculated the number of demographics entered or outstanding claims worked per month.  These are productivity metrics, not necessarily performance, since we don’t know if they directly translate into increased collections.   About a decade ago we were quantifying productivity of our collectors and initially used claims per hour and day worked.  We even created financial incentives for increased productivity.  Then we figured out some people were gaming the system, in other words, they worked the easy claims.  Another way people gamed the system was that some did massive amounts of writeoffs, since these were also fast and easy and boosted their “productivity”.  We then weighted working AR more heavily in the calculation for bonuses compared to writeoffs.  Someone then figured out that if they worked a payer and found a root problem like a credentialing issue they could log 1000 claims as having been “worked” when they made one phone call to diagnose a payer-level problem.  That didn’t seem right either.


But what about the person who works less claims but is more effective?  One person works 5 claims and 4 get resolved while another works 10 claims and only resolves 3.  One person works 10 office claims and brings in $1,000 while another works 3 surgery claims and brings in $4,000.  Should the metric be dollars collected rather than claims worked?  If the incentives are created to favor something, another will get neglected.  Maybe if you weight performance calculation on dollars collected no one works the E&Ms because they are low dollar value.  Some people when they work claims fix them the first time, while others have to work a claim 2, 3 or 4 times before it gets resolved.  How would you even track all of this?  Does your system log touches on a claim in a way that you can output a report and analyze all of this data?  Very few systems have that kind of capability if any.


Goal of this article isn’t to help you develop an incentive program for compensating collectors in your billing company, but to give you an example of how analytics can impact on your business and how complex it can be.



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 does sipping Mai Tai’s on the beach sound?


But 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, % of claims 60+ and 120+, or some other variation.  In my presentation – “Beating Competitors w/ Analytics” – 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 a 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 Go, 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 actually 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.


  • Measure and benchmark your performance… so you can get better
  • Measure and benchmark your performance… so you can beat your competitors
  • Measure and benchmark your performance… so you can sell your billing company


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.  Come see our presentation at HBMA in September in order to get really specific on metrics, KPIs, and analytics to beat your competitors.



About Apache Health

Apache Health is a revenue cycle management (RCM) analytics, benchmarking, and auditing company.  The founders of Apache formerly ran a large RCM company that was acquired by a private equity group in a rollup.  Apache’s predictive analytics will benchmark billing performance and project exactly how much more revenue you should earn from your existing volume of patients. Using many factors and a blend of artificial intelligence and specialty specific benchmarks, the model projects whether changing the billing process would improve collections for your particular mix of procedures and payers.  Apache Health can help you evaluate whether to outsource the billing, determine which billing company to select to maximize performance, or track in-house billing performance improvement over time. For more information contact:


Sean McSweeney


Apache Health


For more information from Please subscribe to our blog. Enter the details below and click on "Subscribe" button