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Contributing Writer · May 3, 2011

Meaningful Use criteria: Record demographics drill down

For clinicians to become eligible for EHR Incentive Program(“Meaningful Use”) payments, a number of criteria must be achieved. There are 15 core measures, and 10 “menu” items from which a clinician must choose 5. Some measures have exclusions, as they may not pertain to a given scope of practice.

One of the core measures is to record Patient Demographic information into each patient chart. There are no exclusions to this measure. Specifically, for all patients seen during the Measurement Period (which, on the first year, is 90 consecutive days), at least 50% of those unique patients must have all the demographic information recorded – or a specific exclusion if the patient declined to provide one or more elements, or if recording an element is contrary to state law. The items must be recorded as structured data.

The elements that must all be included in this measure are (1) gender, (2) date of birth, (3) patient’s preferred language, (4) race, (5) ethnicity.

Preferred language, race and ethnicity follow the same standards as used by the Census Bureau, which is where the pick-lists are drawn.

Why is such data important?
One of the overarching goals of the whole effort to digitize medical records in this country is to be able to reduce health care disparities between different populations. Historically, health care has been shown to disadvantage certain populations based on race, ethnicity and language.

In order to carry out outcomes research and other observations of health data, being able to distinguish the experience of patients based on race, ethnicity and language is important. Building a data store that can drive public health policy, or other disease and treatment research, is a vitally important long-term vision for digitized health data. Including race, ethnicity and language in this data set is an important foundational element.

So what’s the problem?
Traditionally, race, ethnicity and language have not been captured by legacy systems. Our experience at Practice Fusion, with over 10 million patient records uploaded into our Electronic Health Record (EHR) system, is that most of the source lists (usually from legacy billing systems) contain gender and date of birth, but not race, ethnicity or language.

That means that most of the patient records in a clinician’s EHR do not have all the needed elements to meet the Meaningful Use criterion. Very few records contain all the elements, and certainly most all clinical practices currently fall below the 50% threshold.

During the Measurement Period (90 days in 2011), therefore, as patients are encountered, these elements will need to be added to the record. This is a manual process, and will generally need front-desk staff to enter the missing pieces as patients are seen (either at check-in or at the time of appointment-making or eligibility checking).

What can a clinician do now?
Even prior to the 90 day Measurement Period, it would be recommended that clinicians review the need for these (usually missing) pieces of data with their staff, and create the workflow habit of checking these items and filling them in when they are missing. That way, during the Measurement Period, something less than 100% of the encounters will need to have this step done (which is a time slow-down during a clinic session).

This element of Meaningful Use will be quite evident once we develop and release a Meaningful Use dashboard later this summer. But to avoid a last-minute scramble, it would be wise for a practice to recognize the issue and begin getting into the habit of recording race, ethnicity and preferred language routinely in order to more easily reach the 50% threshold needed for Stage 1 Meaningful Use.