G-code Severity Modifiers - Methods

Self-report measures can be mapped to G-code severity modifiers that are required by the Centers for Medicare and Medicaid (CMS).

Description of G-code Severity Modifiers

Clinicians who provide physical therapy (PT), occupational therapy (OT), or speech therapy (ST) to improve function report G-codes to the Center for Medicaid and Medicare Services (CMS), as required by CMS Functional Limitation Reporting. For example, a physical therapist may use a code to convey the patient’s current mobility (G8978), the level of mobility the therapy is aiming to achieve (G8979), or the level of mobility at the conclusion of care (G8980). These are known as G-codes for functional reporting.
A G-code severity modifier is used to indicate the level of impairment, limitation, or restriction that the patient is experiencing. This is a percentage ranging from 0% impaired to 100% impaired. G-code modifiers (e.g., CK) are associated with a specific range of impairment (e.g., at least 40% but less than 60% impaired, limited, or restricted). For example, when reporting current mobility, a patient may have 40% to 50% impairment (CK) and treatment aims to reduce that to under 20% impairment (CI).

Assigning a G-code severity modifier (level of impairment) to a patient relies on clinical judgement. A patient self-report measure of function can be used to help a clinician identify the most appropriate modifier to a given individual. As illustrated below, score ranges from select PROMIS® and Neuro-QoL™ self-report measures have been mapped to each G-code severity modifier. For example, a Neuro-QoL Mobility score between 40.6 and 45.1 is mapped to the G-code modifier CK.

 

How G-code Modifiers are Mapped to PROMIS and Neuro-QoL Scores

Distributional methods were used to map Neuro-QoL and PROMIS T-scores to G-code modifiers. Distributional methods recognize that the possible range of test scores do not reflect the scores people actually receive. They also prevent complications that occur when score ranges vary based on the version of a test that is administered (e.g., a 4-item short form vs. a computer adaptive test).

Neuro-QoL Mapping Methods

Neuro-QoL scores were mapped to G-code modifiers using percentiles based on data obtained from the adult general population. For example, on Neuro-QoL Upper Extremity Function - Fine Motor, ADL measures, 20% of people (20th percentile) in the general population received a score of 31.7. Because lower scores on this measure indicate more impairment, a score less than 31.7 is associated with modifier CM (11.5 – 31.6) or CN (11.4 or lower), indicating more than 80% impaired.

PROMIS Mapping Methods
The distributional approach used for PROMIS reviewed the range of possible T-scores on an exemplar form. For PROMIS, this was the computer adaptive test. Then, that range of possible scores was divided into groups for each G-code severity modifier based on the theoretical distribution of scores and other information known about the measure. For example, a T-score of 50 on PROMIS Physical Function means that approximately half of people in the general population do better than it, and half do worse. This does not indicate 50% impairment, but it also does not indicate 0% impairment. Using clinical judgement and knowing some information about the range of possible measure scores, a PROMIS Physical Function T-score of 50 reflects approximately 1% to 19% of impairment and should therefore be associated with a CI modifier.

Other Mapping Methods
Another method is sometimes used for self-report measures that have a score range of 0-100. The percent impairment is set to match the score. For example, the Neck Disability Index generates scores ranging from 0 to 100. A score of 50, for example, is then associated with CK (the modifier used for 40% to 59% impaired, limited, or restricted). As PROMIS and Neuro-QoL utilize T-scores, in which the mean of the referenced group (usually the general population) is set to be 50, their possible score range is not necessarily fixed to be 0 to 100. Therefore, this method is not suitable to the PROMIS and Neuro-QoL measures.

 

Additional Guidance on Assigning a G-code Severity Modifier

With all of these approaches, a clinician must use all available evidence to choose the most appropriate G-code severity modifier. Scores from multiple tests can provide evidence for one or more different modifiers. Thus, anchoring final decisions clinically using all information about a patient is the most important final step in identifying the correct G-code severity modifier.

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