Measurement Concerns

The number of measurement tools available per body part creates difficulty in comparing results.

By Alfonso L. Amato, PT, MBA

The introduction of Functional Limitation Reporting (FLR) by the Centers for Medicare and Medicaid Services (CMS) requires the use of a functional measurement tool. However, CMS has no recommendation or endorsement of what functional measurement tool to use in the outpatient rehabilitation setting.

Rehabilitation has led the way in health care by developing the science of measuring and reporting outcomes. A multitude of functional outcomes measures are available through commercial and open-access sources for nearly every type of patient health condition seen in rehabilitation. Although variety is typically considered positive, for rehabilitation professionals, this variety leads to a problem. The number of measurement tools available per body part can create difficulty in comparing results between patients, or between practices.

A simple head-to-head comparison of functional change between measurement tools is impossible. Let us analyze a common scenario. Two therapists are treating patients who have knee pain. Each therapist chooses a different functional measurement tool to measure function. Therapist A uses the Lysholm Knee Rating Scale and Therapist B uses the Lower Extremity Functional Scale (LEFS). Both tools are valid and reliable functional measurement instruments; both use a higher score to report better function. The LEFS top score is 80 points; the Lysholm top score is 100. Each therapist will report the resulting functional score from each instrument.

The challenge arises when you want to compare the outcomes between these two patients. A score of 40 on the LEFS is not the same as a score of 40 on the Lysholm. You cannot compare a patient’s outcome measured by the Lysholm with a patient outcome measured by the LEFS. Even with two measures with the same scaling of 0-100, a score of, say, 47 does not mean the same thing as a score of 47 on the other measure. Even if the necessary sophisticated statistical analyses were performed to “link” or “crosswalk” the scores of one measure to another, any change in scores would not be comparable. That is, clinical and statistical interpretations of change— the minimum clinically important difference (MCID) and Minimum clinical difference (MCD)—would remain unique to each measure.

When reporting change in function between patients, measurement properties of the tool are just one aspect in the comparison equation. Patient characteristics must also be taken into consideration. Certain patient factors affect functional outcomes and need to be considered when making a direct comparison. The science of outcomes has evolved to equalize patients via risk adjustment. The main factors considered via risk adjustment often include gender, age, and acuity of the condition. To accurately compare effectiveness and efficiency of care, risk adjustment is required. When comparing functional change of “knee patients,” even with the same functional measurement tool, you cannot compare functional change of each patient because you do not know what other confounding variables have influenced the patient’s potential for change. Risk adjustment accounts for the variables that influence the patient’s ability to respond to treatment and allows for one patient to be compared with another accurately. Using more risk adjustment variables allows you to better account for as many patient differences as possible.

No one wants to be punished for caring for the patients who are sicker, more severe, more complex, more difficult to get better, but that can happen if reimbursement is using a system that does not take risk adjustment into account.

Functional limitation reporting utilizes a G code modifier, which does not specify the specific measurement tools used. Use of different measurement tools can confound the understanding of the functional improvement as a result of care. The G code functional limitation levels are broken down into 20-point increments of change on a 0-100 scale. The following example can show how the reporting of change in a G code level may not provide an accurate picture of true functional change:

Patient A’s functional score at admission places the patient at the bottom of a G code scale; Patient B’s functional score at admission is placed at the top of a G code scale. Both patients had 19 points of change, but one is reported to be in a higher G code and the other patient remains in the same G code. This issue may lead to a missed opportunity to fully understand the change in function the G code reporting process was designed to capture. G code reporting, or a system like it, will possibly be the basis for future reimbursement policies. There is the real possibility that the rehab provider may be paid differently based on the G code level change, rather than on the patient’s actual functional change.

In summary, functional outcome reporting is here to stay. It will become the common language for reporting efficiency and effectiveness in outpatient rehab. It will increasingly be the basis for reimbursement. How do we ensure that reporting functional change will accurately reflect the benefit the patient received from the rehab provider, and that the rehab provider is paid fairly and credited for their contribution to the patient’s welfare?

A functional reporting system that has the following attributes will be the best opportunity to accurately measure and report functional outcomes, and become a basis for future reimbursement policy:

• The industry settles on a functional outcome measurement system used by all providers.
• The measurement system provides for the most accurate risk adjustment available for valid comparison of providers and treatments.
• The measurement system has psychometric properties that ensure high responsiveness, validity, reliability, and precision of measurement.
• The required G code method of reporting functional limitation allows for accurate reporting of change that captures true patient improvement.
• The measurement system has risk-adjusted predictive analytics that most accurately predict discharge functional level.

These five attributes of a functional outcomes reporting system will provide the basis for a fair and accurate process to fully understand patient change, better inform policy initiatives, and guide evidence-based practice. 

Alfonso L. Amato, PT, MBA, is the president of FOTO, a private outcomes management and reporting company. He can be reached at alamato@fotoinc.com.