Most physical therapy and occupational therapy practices treat a revenue problem as a billing problem. It isn't a billing problem; it's a revenue cycle complexity problem. After eight years of measuring millions of claims, we know that 71% of the complexity putting your revenue at risk is created inside your practice but external to billing, long before a claim ever reaches a biller. The single most valuable thing you can do is make that complexity visible, because you can't reduce what you haven't measured.
I shared this in a recent webinar I was invited to join as a guest with Stride. Here are the core ideas, in one place.
What business are you actually in?
If your providers treat patients and you depend on third-party reimbursement, here is the first thing I want you to sit with: you are not a physical therapy practice that happens to have billing. You are a revenue cycle management business that performs physical therapy services in exchange for revenue.
That is not wordplay. It changes how your business needs to be structured. Your roles, your functions, the data you create, and the KPIs you watch all need to be aligned around revenue cycle objectives. Revenue cycle is the economic engine of the practice. You can be the best clinician in the world and still build a business with very little value if you never get paid, quickly and completely, for your time.
The three objectives every revenue cycle shares
Every revenue cycle business has the same three objectives when it comes to converting provider time into cash:
- Collect it all. Convert 100% of provider time into cash. Collect everything that is on the table for you to collect.
- Collect it fast. In as few calendar days as possible. Call it days in AR, DSO, or whatever you like; it is how long, on average, it takes you to get paid.
- Collect it efficiently. As cost-effectively as possible, which really means as efficiently as possible.
Here is the part I most want you to take away: objectives one and two depend on objective three. What we have proven with eight years of data is that it is the efficiency of the revenue cycle, primarily the billing process, that ultimately determines whether you collect it all and collect it fast. Efficiency is not the nice-to-have at the end of the list. It is the thing the first two objectives rest on.
Why I call it a black hole
I use the black hole analogy because black holes are mysterious. You can't see one directly. You can only measure it by its effect on the things around it, and that takes data and math to explain what you observe.
Revenue Cycle Complexity is the same. The complexities themselves are difficult to quantify directly, but we can understand them clearly by measuring their impact on the work your practice does every day. That is exactly what we do. We have been measuring the Revenue Cycle Complexity black hole in practices for eight years, and we make it visible by measuring its pull on the everyday workflows of a revenue cycle business.
The reason billing is where the black hole shows up most is simple. Billing is the only function that is directly affected by every other function. Patient registration, verification of benefits, pre-authorization, documentation, and everything else flows into it. That relationship is also the opportunity. If billing is affected by everything, then billing is the place to understand everything.
Where revenue cycle complexity actually starts
We call our data platform the Observatory. It lets us convert the billing process into origin data, so we can get to root cause. Millions of claims and millions of documented complexity incidents later, here is what our current national roll-up says about where complexity comes from:
- 71% is generated internal to the practice but external to billing. Patient registration, verification of benefits, authorization management, clinical documentation, credentialing, and the like.
- 10% comes from payers.
- 13% comes from systems: the EMR, practice management software, and clearinghouse, most of it from improper setup.
- 6% is generated inside the billing process itself.
That means 94% of all revenue cycle complexity is external to billing. When that distribution first rolled up years ago, it sat at 78/14/4/4. The systems share has climbed as more platforms enter the market with setup and onboarding problems, which tells you this is living data, not a static talking point.
Break open the 71% that starts inside the practice and the order matters. Patient registration is the largest single source at 31%. Provider documentation and policy or process each account for 17%. System setup is 12%. Authorization management is 8%, verification of benefits is 6%, cross-functional communication and patient-driven issues are 4% each, and credentialing is 1%.
Policy is worth an example, because it is easy to miss. Say you have a policy that you will not collect any money from a patient until after you receive the ERA or EOB from the insurance company. That is a bad policy, and it will cost you. It delays money, inflates AR, and stretches the time to collect from patients, because all of it now happens after discharge. One policy, written with good intentions, quietly working against all three of your objectives.
It's about time: the gap between time demand and time supply
Once you can measure complexity, the question becomes what it costs you. In our model, the answer is measured in time.
Billing Time Demand is always variable. There is no exception to that. It is driven far more by the complexity inside your claims volume than by the volume itself. Billing Time Supply, on the other hand, is almost always fixed. You have so many FTEs, staffed a certain way, paying for a set amount of time. That is the structural problem across the whole industry: demand on time is a variable, but supply is close to a constant. A fixed supply only works when complexity is so low that supply happens to line up with demand.
When demand exceeds supply, outcomes suffer, and the diagnostic chain is predictable. RCC is high, Billing Time Demand is high, Billing Time Supply is too low, AR grows, revenue shrinks, and administrative cost climbs.
How much does complexity move time? Comparing our highest-complexity practices to our lowest, using client data from 2022 through 2025:
- 665% more total billing time per visit.
- 1,997% more total AR management time per visit.
- 4,060% more denial management time per visit.
I have clients doing 500 visits a month whose billing takes more of our time than clients doing 5,000 visits a month. That sounds impossible until you understand that complexity, not volume, is the real driver of time demand. When the work of one biller balloons into the work of many, no staffing plan built on a fixed number of people can hold the line.
Why hiring more people has never scaled
There are two sides to this problem, and you have to attack both.
On the practice side, we have to reduce the creation of complexity at its origin. Today the standard approach is to hope you hire good people, give them KPIs, try to align everyone, and trust that they don't make mistakes. When it works, it is amazing. It just doesn't work most of the time, because the complexity is being created upstream, in functions external to billing.
On the billing side, you cannot staff and scale a four-thousand-percent swing in denial management time with human capacity alone. This is where technology, automation, and AI agents come in: not to replace the people, but to remove the ceiling on time supply so it can flex to meet demand at any level. Fixed time supply modeling will always fail, and your outcomes will fail with it, when complexity is high.
So we work it from both ends. Reduce the complexity being created at the front office, and remove the structural limits that keep billing time supply from expanding. That requires a variable time supply model, matched to measured demand.
The AI wave is a strategy question, not a technology question
There is an AI wave already on the horizon, and you can ride it to tremendous value or get rolled by it. I believe that within the next 12 to 18 months, every administrative function in a healthcare business will either be replaced by automation and AI, or be redesigned as an integration of technology and humans.
I am not interested in bypassing the human. The concept that matters is human in the loop. Automation is a bot; it follows a linear path and stops the moment something unexpected happens. AI is a thinking thing you train to understand what people do, and then it can process at speeds people can't match. The right answer is not AI everywhere. It is the right solution, on the right workflow, at the right time, with the brain of the biller and the brain of the therapist still making the calls that matter.
The strategic move underneath all of it is ownership. Own your data. Own the knowledge loops that come from it. Build intellectual property for your own business. The winners of this next era will be the practices that turn what they already do every day into their own data and intelligence. The losers will be the ones who let a vendor wall them off from it.
Where to start
When people ask me the single most important thing they can do to reduce revenue cycle complexity, my answer is short: define it, capture it, quantify it. Know exactly what it is. In about 30 days, a practice can capture the full picture of the complexity it generates simply by converting human experience into data.
Then comes the harder part, which is doing something with it. Our data also shows that roughly half of the practices that have the data and know what best practice looks like still don't execute on it. Measurement makes the problem visible. Execution is what changes the outcome. Thinking up new things is creativity; doing new things is innovation.
None of this has to feel heavy. It is exactly what companies like ours think about all day so you don't have to. The path forward starts with awareness, and awareness starts with measurement. Better Data leads to Better Process, which leads to Better Outcome, which leads to a Better Business. Every link is necessary, and no link can be skipped.
See the size of your own black hole
You can't reduce what you haven't measured. Every RCS relationship begins with a revenue cycle assessment that quantifies the complexity inside your practice and the opportunity to improve your revenue cycle outcomes. We share the findings with you at no cost and no risk, so you can decide your next move from data instead of a guess.
Request Your Free Revenue Cycle Assessment
Frequently asked questions
Is my revenue problem a billing problem?
Usually not. In our data, 94% of revenue cycle complexity is created external to billing, with 71% originating inside the practice in functions like patient registration, verification of benefits, authorization management, and documentation. Billing absorbs the effects of that complexity, but it rarely creates it.
What is Revenue Cycle Complexity (RCC)?
RCC is the operational, structural, payer-originated, and systems-driven errors and omissions that increase the time required to bill and collect, and that put your revenue cycle objectives at risk. We call it a black hole because it consumes time and revenue invisibly until it is measured.
Why does complexity matter more than claim volume?
Because complexity, not volume, drives Billing Time Demand. Comparing our highest-complexity to our lowest-complexity practices, total billing time per visit rises 665%, AR management time rises 1,997%, and denial management time rises 4,060%. We have 500-visit-per-month practices whose billing takes more time than 5,000-visit-per-month practices.
Will AI replace billers in physical therapy practices?
Within the next 12 to 18 months, most administrative functions will either be automated or redesigned as an integration of technology and people. The model I advocate keeps humans in the loop and uses automation and AI to remove the ceiling on capacity, not to remove the judgment of the biller and the therapist.
What's the first step to reducing revenue cycle complexity?
Define it, capture it, and quantify it. You cannot reduce what you haven't measured. A practice can capture a full picture of its complexity in about 30 days by converting everyday billing experience into data.