Apples Ain’t Oranges: The Case for Risk-Adjusted OMTs

Chuck Klosterman, author of Sex, Drugs, and Cocoa Puffs, will tell you that you absolutely can compare apples to oranges. However, he’s never worked in health care. Sure, both apples and oranges are fruits—just like all patients are people. But picture this: two PT clinics—both alike in dignity, in the fair USA, where we lay our scene. One clinic averages 10 visits per case; the other, 20. If that’s all you have to go by, then you probably assume the first clinic is much more efficient—and effective—at patient care.

Not so fast. After all, case and patient mix are critical factors. Perhaps the second clinic treats patients with more severe injuries or complicated pre-existing conditions. Thus, comparing clinics based solely on case-load efficacy is unfair. To truly measure the quality of care provided, one must examine the patient outcomes achieved—and more importantly, use risk-adjusted OMTs.

The Case for Outcome Measurement Tools

Although we find ourselves in 2024, believe it or not, there are still rehab therapists who need a reason to use outcome measurement tools. But in the face of yearly rate cuts from federal payers, commercial insurances following suit, and the ever-worsening administrative burden placed on clinics by said insurances, collecting outcomes is no longer an idea, it’s a lifeline for rehab therapy. In case you need convincing, just check out WebPT Co-founder and Chief Clinical Officer Heidi Jannenga’s recent founder letter on why data makes the case for rehab therapy.

The Case for Risk-Adjusted OMTs

But again, we run into an apples-to-oranges problem. Considering scores of regularly completed outcome measurement tools (OMTs) alone, one clinic may demonstrate faster functional improvement compared to other clinics. However, certain patients heal better than others. Let’s use two ACL reconstruction rehab patients as an example: one takes 10 visits longer to achieve the same level of function as the other. But that's not necessarily a reflection of the quality of each patient's care, because one patient is 30 years older than the other and suffers from knee osteoarthritis. Both patients receive excellent care, and both patients get better. But without taking into account these critical patient case details, all you have on paper is a visit count—and that’s not the sole way practitioners want to be judged.

Thus, if clinicians don’t take complicating factors into account, then the quality of their data, the justification of their care, and ultimately, the legitimacy of PT in general are all invalid. And that hurts bottom lines, as  the Journal of the American Physical Therapy Association explains: “Assessments of provider performance that are tied to public reporting or financial incentives that are based on unadjusted outcomes may penalize providers treating the sickest patients who fail to show enough improvement or require more visits in a treatment episode.”

Risk-adjusted OMTs make regulators jump for joy.

So, how do practitioners account for complicating factors consistently and at scale? Enter risk adjustment. According to an overview published on CMS’s website, “The purpose of risk adjustment when comparing outcome rates (e.g., hospitalization rates) for two different patient samples is to statistically compensate (or adjust) for risk factor differences in the two samples so that the outcome rates can be compared legitimately despite the differences in risk factors.”

Risk-adjusted OMTs create clarity in a not-so-clear healthcare market. 

Unadjusted outcomes can lead to poor payment or penalties, but risk-adjusted outcomes —and the valid data they provide —help level the data playing field. Risk-adjusted OMTs allow healthcare practitioners and payers to establish baselines for tracking quality and efficacy over time, both internally and across facilities, regions, and the country. Similarly, such measures allow practitioners to prove the effectiveness of specific treatments or interventions. 

To circle back to our two ACL patients, let’s assume the therapists regularly use the lower extremity functional scale (LEFS) to assess improvement throughout both episodes of care. LEFS accounts for age and other complicating factors. Thus, the therapists can better—and more fairly—assess and prove the efficacy of their care.

For all of the above reasons, OMTs must be risk-adjusted, which means test results take into account differing levels of patient complexity, such as age, weight, litigation, diabetes, cancer, and heart disease. (Luckily we have more information at the ready on all things outcome measures.) Patient complexity doesn’t end with the aforementioned comorbidities, though. 

As the previously cited CMS overview states, “In general, risk factors for an outcome are chosen first by conceptually and clinically specifying the potential risk factors, and then assessing which ones are empirically related to the outcome.” 

Risk-adjusted OMTs are the bedrock for value-based care.

Payment reform is happening, and the key to ensuring not only proper payment but also physical therapy’s rightful place in the care continuum is outcomes data. But it has to be the right outcomes data. Risk adjustment ensures the comparability of data, which moves PTs one step closer to proving their worth and effecting change with payers. 

All of this is to say that the right Practice Experience Management platform will help you apply the right OMT with proper risk adjustment built-in to the software. That way, the next you need to negotiate an insurance contract—or deal with one of the many regulatory burdens we have today—you can channel your inner Matt Damon and ask, “How you like dem apples?”