All Things Data


Anatomy of a Measure: Age Ranges

One of the most basic components of most clinical quality measures (CQM’s) is a check of the patient’s age. For an indicator like the Breast Cancer Screening measure, of course, we only want to include women within a clinically relevant age range. But, like a lot of things related to CQM logic, things can get complicated quickly.

Let’s start by making a distinction between clinical intent and measure specification. The clinical intent is how the measure should work; how a health care provider would explain the measure to you. They’d say something like “women over 50 need to have a mammogram every 2 years” – simple.  However, measure specification is how the measure is technically defined, which needs to be very clear and concise because it’s being interpreted by programmers and computers. So a measure specification needs to say something like “the denominator includes all women whose age was greater than or equal to 52 on the last day of the measurement period”.

Now you may think you just spotted a typo in this post – in the clinical intent example I said 50 and in the measure specification the example I said 52. How does that make sense?

Let’s look at the NQF 2372 eCQM spec. The description section says “Percentage of women 50-74 years of age who had a mammogram to screen for breast cancer”, and the population criteria section says “Age>= 51 year(s) at: ‘Measurement Period'”. But what does “Age>= 51 year(s) at: ‘Measurement Period'” actually mean? This way of expressing measure logic is called the Quality Data Model (QDM) and guidance on interpreting QDM can be found here –https://ecqi.healthit.gov/system/files/qdm_4_3_508_compliant.pdf. Specifically refer to section 3.2.7 for “Age At”, where you can see that the intent is to check the patient’s age “at the start of the measurement period”.

In DRVS we calculate most of our measure logic using the end of the measurement period as that is the primary reference date (the reason for this could be a subject for another blog post). Because the eCQM specifications assume a year-long measurement period we simply add 1 year to the specified measure logic so that we can check the patient’s age at the end of the measurement period. Now there is some complexity regarding the edge case of patients whose birthday is on the first day of the measurement period, but a deeper dive into that edge case is beyond the scope for this post.

Now let’s take a step back and consider whether or not our measure logic actually aligns with the clinical intent of the measure. The current clinical guidance from the USPSTF recommends biennial screening mammography for women aged 50 to 74 (ie. screening every 2 years). When we calculate a CQM we are essentially checking every patient’s compliance with these guidelines. In this case a patient cannot be deemed non-compliant until they are 52 years old. It doesn’t make sense to include someone who turned 50 on the last day of the measurement period because they still have 2 years to get a mammogram before they are considered non-compliant. This explains why the clinical intent may express the age criteria with one number (50), while the measure specification uses a different number (52).

Hopefully, this example helps to dispel some of the confusion around measure age logic and demonstrates how we at Azara think about measure development. We’re constantly trying to develop measures that comply with industry standard specifications while trying not to get too lost in the weeds of QDM syntax, code system mappings, and other “nitty gritty” details. At the end of the day our goal is to deliver measures that provide clinically accurate results and reflect reality, so when it seems to make no sense, it always helps to go back to those two concepts – “what do the measure specifications say and what is the clinical intent?”

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