The denominator statement describes the population evaluated by the individual measure. The population defined by the denominator can be the same as the target/initial population, or it can be a subset of the target/initial population to further constrain the population for the measure. The measure developer must describe the denominator statement sufficiently so the reader understands the eligible population or composition of the denominator, and should not use codes in lieu of words to express concepts in written descriptions. The measure developer should define the denominator precisely and include parameters such as
- Age ranges
- Time interval
- Other qualifying events, e.g., look-back period
Format: Patients, age [age or age range], with [condition] in [setting] during [time frame]
- All patients aged 18 and older with a diagnosis of major depressive disorder (MDD) (CMIT Member ID 30) (CMS CBE #0104e)
- All patients at least 18 years old as of the first day of the reporting month who are determined to be maintenance hemodialysis (HD) patients (in-center and home HD) for the complete reporting month at the same facility (CMIT Member ID 313) (CMS CBE #2978)
Denominator exclusions refer to criteria that result in removal of patients or cases from the denominator before calculating the numerator. A denominator exclusion means the numerator event is not applicable to those covered by the denominator exclusion; an example of a denominator exclusion is to “exclude women who have had bilateral mastectomy from the denominator for a measure of screening mammography.”
The goal of denominator exclusion criteria is to have a population or sample, all of whom share a similar profile in terms of their likelihood of meeting the numerator criteria.
Format: denominator-eligible patients who [have some additional characteristic, condition, procedure]
The measure developer must not specify systematically missing data as a denominator exclusion. The CMS consensus-based entity (CBE) Consensus Standards Approval Committee Guidance on Quality Performance Measure Construction notes systematic missing data (e.g., when poor performance is selectively not reported) reduce validity of conclusions that can be made about quality.
To avoid complexity, the measure developer should limit denominator exclusions to just those that are absolutely necessary. Ensure the measure logic expressions (e.g., Clinical Quality Language) clearly identify denominator exclusions. The measure developer should support an allowable denominator exclusion with
- Evidence the denominator exclusion condition occurs with such frequency that it will distort the measure results without the denominator exclusion, and
- Evidence the denominator exclusion significantly improves measure validity, and/or
- Evidence of both empiric and face validity.
- Conditions present on admission should not count as an outcome of interest.
- An outcome of interest can be very difficult to prevent in a population of interest, and therefore not an indication of substandard care.
- Some inclusion criteria identify populations who are at very low risk for the outcome of interest, but then the measure developer incorrectly made a denominator exclusion to prevent dilution of the quality improvement denominator.
- Some inclusion criteria are for the purpose of enhancing face validity with clinicians.
- Some inclusion criteria are an inherent part of the quality improvement definition.
- The inclusion criteria may conflict with the patient’s goals of care (e.g., advanced illness, terminally ill).
Determine Need for Denominator Exception
A denominator exception allows the measured entity to get credit when the measured entity performs the quality action, but not penalized if not done for an appropriate reason. The exception allows the exercise of clinical judgment and implies the measured entity considered or offered treatment to each potentially eligible patient in the denominator. Denominator exceptions are most appropriate when measures of contraindications to drugs or procedures are relative (Spertus et al., 2010). A measure developer should specifically define a denominator exception when capturing the information in a structured manner fitting the clinical workflow. The measure developer should only use a denominator exception in proportion measures. It is not appropriate for ratio or continuous variable measures.
Although no single agreed-upon approach to denominator exceptions exists, there seems to be consensus that denominator exceptions provide valuable information for clinical decision-making. Measure developers who build denominator exceptions into measure logic should be aware that—once implemented— denominator exception rates may be subject to reporting, auditing, endorsement/maintenance review, and validation of appropriateness. The measure developer should account for these factors in measure design and development.
The measure developer must capture the denominator exception with explicitly defined data elements that allow analysis of the denominator exception across measured entities to identify patterns of inappropriate denominator exception and gaming and to detect potential health care disparity issues. Analysis of rates without attention to denominator exception information has the potential to mask disparities in health care and differences in measured entity performance.
- Inappropriate denominator exception: a notation in the patient’s medical record indicates a reason for not performing the specified care, and scientific evidence does not support the reason.
- Gaming: patient refusal may be a denominator exception; however, it has the potential for overuse. For example, a measured entity does not actively encourage the service, explain its advantages, or attempt to persuade the patient, and then uses patient refusal as the reason for nonperformance.
- Disparity issues: the use of a patient reason for denominator exception for mammograms is found to be high for a minority population, which may indicate a need for more targeted, culturally appropriate patient education or closer examination of patient access issues such as lack of transportation or lack of childcare.
Transparency and Evidence
To ensure transparency, the measure developer should capture an allowable denominator exception in a way the measured entity can report it separately, in addition to the overall measure rate. The measure developer should support an allowable denominator exception with evidence
- Of sufficient frequency of occurrence such that distortion of the measure results occurs without the denominator exception
- The denominator exception is clinically appropriate to the eligible population for the measure
Although no single agreed-upon approach to denominator exceptions exists, there seems to be consensus that denominator exceptions provide valuable information for clinical decision-making. Measure developers who build denominator exceptions into measure logic should take caution that, once implemented, denominator exception rates may be subject to reporting, auditing, endorsement/maintenance review, and validation of appropriateness. The measure developer should account for these factors in measure design and development.