The Biggest Data Silo That No One is Talking About - The Opilio Story

It was a cold day in December 2013 shortly after Thanksgiving. I was sitting in my condo in North Dallas in the dark. I had just recently recovered from a severe concussion that went undiagnosed for two weeks until I had a vertigo attack at work because I had denied medical care after my car accident to make it to my best friend’s wedding and I didn’t tell anyone about hitting my head as flipped over the retaining wall and rolled down a grassy knoll on the side of the freeway.

I had woken up early in a cold sweat from a night terror about the accident and couldn’t go back to sleep. I sat in the dark, cold and depressed. A couple of months had passed and I was still jobless. In a few short months I went from my dream job in investment banking on pace to make six figures at 22 years old to a traumatized, broken, unemployed regular person.

When I should have just been thankful I was still alive with no long-term brain injury I was wallowing in self-pity. I had applied to every finance, accounting, and consulting related entry level position in the entire Dallas Fort-Worth area and had gotten only a handful of phone interviews that all ended there. I know what you’re thinking – “there is no way you applied to every single job.” My parents said the same thing at Thanksgiving dinner so I pulled them to their computer and opened my e-mail to show them the hundreds of “Thank you for applying! It was a difficult decision but at this time we have decided to move forward with other more qualified candidates” with a handful of the other “Thank you for your interest but we believe you are over-qualified for this position” e-mails.

God was looking out for me because I had just read the book How to Win Friends and Influence People a classic by Dale Carnegie, and He sparked an idea in my mind. I might have applied to every possible open job I could find, but I had friends. Friends I was embarrassed to reach out to, but, nonetheless, I had friends. I texted my fraternity brother and former roommate. I don’t remember exactly what it said but I do know it was raw, vulnerable…desperate even. I let him know the predicament I found myself in and all I needed was a shot. Just a chance. Just an interview.

He let me know he had recently started a new job in management consulting with a firm that was growing and looking to hire more people. Management consulting was one of the few industries that piqued my curiosity as much, if not more, than investment banking because it was the operational functions of business that were most interesting to me outside of finance. It came with a caveat, though, the company he said was solely focused in the healthcare industry. I knew nothing about healthcare, and I had always wanted to be in technology, so my first gut instinct was this wasn’t for me, however, what position was I in to say “no” to any opportunity. I jumped on the chance to get an in-person interview. I always did better in-person and did not have to worry about the awkwardness of phone interviews where you can’t read non-verbal cues and facial expressions.

I remember reading as much as I could get my eyeballs on from Google and talking to my friend about the nuances of the healthcare industry. I wasn’t sold on the industry just then but I got the job and went all in. It took about a year before it all began to click, but I do remember the project when it did all come together for me – the day I fell in love with the healthcare industry.

Michael Malloy was and to this day still is the highest IQ person I have ever had the privilege to work under. He built an entire practice around an innovation that my understanding he came up with in his early twenties when he worked for a BIG4 accounting firm that is still used by many firms in present day called the “black-box analysis” – named after the black box used in aircrafts. Essentially, before the de-regulation of the 2016 Price Transparency legislation when one healthcare organization was in the process of acquiring another healthcare organization the fee schedules which govern the reimbursement rates for each of the organizations could not be disclosed until after the consummation of the transaction. It was, and even now still is one of the key nuances and inefficiencies in healthcare – how can a potential buyer perform adequate due diligence without understanding the fundamentals of revenue?

The ”black-box analysis” introduced an objective third-party intermediary that would take the insurance contracts of both parties and model the fee schedules on the buyer’s most annual volume and payer mix giving them insight to which contracts were most accretive to revenue. If you are well versed in healthcare data you will understand that despite its simplicity the deliverable is not easy – especially given the magnitude of the data (certain analyses with billions of rows of invoice level detail) and the limitations of technology at that time. One of my favorite quotes that I still use from Mr. Malloy, is “there is a gap between simple and easy.”

Yet, I became infatuated with the process. It was like a big puzzle to me, and I loved solving puzzles. Under Michael’s leadership we were also challenged to rise up to high standards – we did not round numbers, no, we modeled revenue to the penny. I learned how to write SQL code in Microsoft Access and would start a query at 7pm and go to bed later that night making sure to remember to ask God that my query did not time out and fail to finish when I woke up the next morning.

I am not sure if it was by Michael’s calculated strategy, luck, or divine intervention but I got staffed on the “black-box” engagement for the Baylor, Scott and White merger in late 2014/early 2015. It was a grueling experience with many late nights and our revenue analysis was a pivotal piece in either making or breaking the transaction because it had implications of over $1 billion dollars in revenue to the potentially combined entities. I remember when I turned in my work and a couple of days passed and Michael called me into his office unexpectedly. He asked me to shut the door.

I grew up in shame-based household. I had been cussed out many times at the investment bank. I remember a sense of dread and panic began to sweep over me. My mind started racing and thoughts of “I must have messed up,” and “I hope I didn’t completely blow it” filled my head. A moment that felt like a day passed and Michael smiled, asked me to sit, and told me what a great job I did. He reviewed the models and he invited me to come and sit in with him on the presentation of our findings with the entire executive team of Baylor Healthcare later that week. As I left his office I’ll never forget his parting words, “you earned it.” They stick with me to this very day as a reminder that even though you may not always get the recognition you think you deserve that great work does not go unseen forever.

That was the day I fell in love with the healthcare industry. I did not choose it; it chose me.

Fast forward ten years later and our healthcare system is in major crisis. It breaks my heart to see the lost value driven by inefficiencies that despite the technological innovations, some of the brightest minds in the world, price transparency deregulation, and $17.6 trillion dollars spent in 2022 alone that many of the same problems from ten years ago still exist now. It breaks my heart because the true cost of a failing healthcare system isn’t merely dollars – it is human life.

Ransomware attacks that increase mortality rates between 20% and 35%  become so rampant they rarely make national headlines anymore. Year over year declines in reimbursement rates have caused major healthcare systems into bankruptcy threatening access to core basic health services in our major cities. Approximately, 55% of rural hospitals are at risk for bankruptcy. The consequences of COVID-19 have increased burn out and now a shortage of nurses and mid-level providers has grown from an important issue into a major crisis just to name a few of the very real problems we face. I say we because no matter what you do or who you are if you live in the United States the healthcare industry and its current crises do affect you whether you know it or not. I have my own saying “it used to be said all roads lead to Rome, but in the United States all roads lead to healthcare.” As a practical example, do you remember the 2008 bailout of the major U.S. car manufacturers like General Motors and Ford? Did you know that one of the key reasons U.S. manufacturers could not compete with foreign imports was because of healthcare costs for their retired employees – in 2003, healthcare for retired workers cost GM $1,300 per each vehicle sold.

I don’t claim to have all of the answers, but there is a recurring trend I have seen over and over and over again that I will not say is easy but so simple to fix in healthcare. Integration of the EMR system to the accounting system, and/or ERP system. The technology to do this not only exists – but it is now readily available and more affordable than ever before. I obtained the technology from a leading public company called Domo with no money down before I even secured an investor group to start Opilio based on selling nothing more than my vision. The EMR system can be integrated with the accounting system remotely in one to two business days through what’s called an API which is just a fairly simple coding exercise I taught myself on YouTube how to do in a couple of hours that acts as intermediary for two different software programs to “communicate” with each other. If you have linked your bank account with Venmo, Cash App, Plaid, or the hundreds of other similar applications on the market you have used an API potentially without even knowing it. I am happy to answer the technical questions to explain more about “how,” but the “why” is what is most important.

I became one of the youngest directors at Grant Thornton for a lot of reasons, but there was the one primary reason – I was the best at what I did, which was using historical data to predict future cash collections. Before I re-joined the practice at Grant Thornton they, like most other practices, were using the cash collection water or what others know as the cash triangle to estimate future cash collections. To put it simply, the analysis takes a look-back period, typically three years of historical data, and waterfalls month-over-month cash collections in the month in which they were received (payment date) back to the month in which the service was provided (date of service) using simple division of cash collections divided by gross charges to get an average cash collection percentage. One reason for the complexity of healthcare is the revenue cycle. In other industries you typically provide a service/sell a product and you the merchant gets paid at the time the transaction occurs (or in the case of credit card sales in one to two business days) or there are stated AR terms and the merchant can plan accordingly for their cash flows. In healthcare a physician provides a service and it can take months, even over a year to get paid for that service, add to this multiple contracts that all pay different rates for the same service, bundled payments, co-pays, alternative payment methods, denials, coding errors, etc., and understanding healthcare revenue and predicting revenue is very nuanced, complex, and painstaking process. The cash waterfall is not a bad methodology, it is extremely helpful to understand the “tail” or days sale outstanding, i.e., how long it takes on average to get paid, but it does come with its flaws and limitations.

One such limitation is that if you do analysis on all of the data your output will be skewed because in healthcare there are multiple payers and each payer pays a different rate for the same service which is represented by a CPT code. If Blue Cross Blue Shield pays $150 for a 30 minute office visit and Medicare pays $100 or the same 30 minute office visit and BCBS makes up 60% of your payer mix and Medicare comprises 40% your analysis will be skewed toward BCBS’s high reimbursement – but what happens if you forecast and budget to that statistic and your payer mix changes? You will have a shortfall of your projected cash. This is only a very simple example of payer mix changes, but most providers also offer a number of different services using various CPT codes which also get paid at different rates. Small changes in payer and service mix have large dollar amount ramifications. If the analysis is off by 1% on a $100M revenue organization that represents a $1 million dollar variance of budget to actual.

To control for this we would run waterfall analyses by payer and by service, which for most clients was accurate and satisfactory. However, for each new “cut” of revenue, meaning each incremental payer or service the analyses become exponential. For example, in a simple setting with only the five major payers (BCBS, United, Aetna, Cigna, and Humana) and Medicare that only uses 3 CPT codes (99213, 99214, and 99215) you would run 18 cash waterfalls and add them all up together to estimate your total revenue. You would run three cash waterfalls for each payer (BCBS – 99213, BCBS – 99214, BCBS 99215, United – 99213, United – 99214, United 99215, and so on down the list of payers).

If you are in healthcare you know that is a simplistic. What happens when your organization is larger with over 300 locations, 80 CPT codes, and 12 major payers, and you are in discussions for a large investment from a sophisticated private equity firm that wants to understand revenue by location, by each of the 80 CPT codes, and each of the 12 major payers? If you do the math does your organization, or any organization for that matter, have the ability to run 288,000 individual cash waterfalls, add them all together, and get to an accurate answer without technological limitation or chance of human error?

I was tasked to do just that. When we communicated to the client it wasn’t feasible they pointed to the executed engagement letter, and told us to “figure it out.” I figured it out using an alternative approach called the zero-balance account (“ZBA”) analysis which is essentially very similar to the cash waterfall approach, but can be done in a databasing tool like Microsoft Access, Alteryx, Tablaeau, Domo, and I am sure others. One of the biggest limitations was the volume of data to be analyzed was too large for Microsoft Excel. I directed the work cross functionally with our data analytics team and automated the process – we turned the analysis back to them in three business days.

That’s when I realized my highly complex job could be automated. It was not a proud moment, but a scary one. This occurred in October 2022, one month before ChatGPT released publicly and the AI explosion began. I had up to this point been unconcerned about AI technology, but now I knew it threatened even my job. I was working 14 to 16 hour days, and at least three days a week I would sign off between 9pm and 10pm from work and stay up self-teaching myself AI, machine learning, python, and learning new platforms like Bubble, Xano, and Domo until 3am and sometimes 4am in the morning. I was determined not to be fearful but to embrace my skillset and learn a new one.

I don’t believe in coincidences, and I had just graduated from the Flow Research Community’s Peak Performance training as a Certified High Performance Coach. I tapped into the flow state consciousness and in about six months felt comfortable enough with the technology to use it and ultimately start Opilio because what used to take professional service firms like Grant Thornton weeks or months to complete and charge six figures for can now be installed in a couple of days, tested and perfected over a couple of weeks to maybe a couple of months for large-scale projects and that same analysis can be automated with the most important metrics visualized to executives and decision-makers in real-time and be made affordable for even the smallest of practices.

The reason this analysis is so valuable and the reason those services even exist at large firms like a Grant Thornton is because the majority of healthcare organizations operate on a cash-basis. The problem is it takes months to collect the cash, so the cash received today is based on a service that was provided months ago with little to no transparency about what the current operations of the business. To simplify it, many physicians, many organizations are planning their business based on outdated information. Countless times, we encountered sophisticated private equity operators and single physician practices with the same issue, they planned based on cash coming in the door and did not know that there was a change in payer mix or a change in service mix that led to poor decisions that many times at such severe consequences it put their entire business at risk. More than once I have encountered healthcare organizations where a payer stopped adjudicating and paying claims and it went undetected for multiple months.

This is also the severe limitation of revenue cycle management vendors. Their reports are amazing, but the majority of the time they are based on a cash basis, and I applaud the RCM companies trying to do more to provide transparency into accrual-based revenue, or predicting your future cash flows, but there is no substitute for a firm like Opilio with our depth of experience, CPA designation, and technology platform.

I have made a small name for myself helping my clients increase their reimbursement through payer negotiations – and I love and will continue this work. Unfortunately, this negotiating rate increases is a band-aid. CMS has proven year over year they will continue decreasing reimbursement in their effort to curb the rising cost of healthcare and commercial payers will continue to consolidate and follow suit. Opilio’s true value is optimizing your revenue by allowing you to manage your business based on the most recent data and giving you visibility into the future, integrating your systems with your EMR which is the biggest data silo so you can streamline your operations and increase your profitability through reducing inefficiencies and making better decisions with better data in real-time and allowing you to reinvest those dollars where it matters most – enhancing the patient experience which will allow you grow and thrive in the communities in which you serve.

I won’t say it will be easy, but it can be simple. This isn’t a sales pitch, today is December 20, 2023, and just like that text I sent to Brandon ten years ago this is a raw, real, vulnerable…desperate cry to the providers, healthcare executives, private equity groups, commercial insurers, regulators, and everyone touched by the healthcare industry to stop pointing the finger at each other for our broken system and first take a look in the mirror and hold ourselves accountable to the changes we can make and then come together to find objective, fair, and equitable solutions to the same problems that plagued us when I started my career because there are no more excuses. We have the brightest minds, we have the market transparency, and now we have the technology. Opilio can help address many of the issues, but it will take concerted effort from the industry leaders as a whole. I hope we can partner together to build a healthier future for all.