According to the U.S. Centers for Disease Control & Prevention (CDC) health equity is achieved when every person has the opportunity to “attain his or her full health potential” and no one is “disadvantaged from achieving this potential because of social position or other socially determined circumstances.” Having a complete view of an individual’s clinical data is vital to achieving this.
During CommonWell TV 2022, we asked our members to reflect on this very important topic by asking this question:
Why is data quality critical, not just to improve data exchange, but to improve equity in health care?
Read below for their responses and watch this year’s CommonWell TV videos here.
Data quality underpins everything we all want to accomplish. If data is missing from a message, coded in a non-standard way, or is inaccurate, it can have significant consequences from creating lack of insight or an ability to serve a clinical need, creating a patient safety risk. Putting that in the context of health equity, data quality shortcomings prevent insight into very basic, but important things about individuals and the care they receive. For example, if we can’t accurately code race, ethnicity or address information, shared at the de-identified level, then you can’t effectively evaluate health disparities or inequities using those clinical data sets.
The more complete picture that a provider has of a patient’s clinical, social, environmental, and socioeconomic status, the easier it is to create a plan of care that addresses all of the gaps. Physicians should be able to seamlessly order Meals on Wheels services or medical transportation—just like they would order oxygen or an infusion pump—we want those pieces of information to also be available. This is the data that helps promote equity and helps us understand the needs of a patient beyond their clinical care. Having the CommonWell network to share that information with makes sure that things are more equitable and more holistic for the caregiving individual.
As we look at end users, providers nurses, doctors—they are relying more and more on outside information to support workflows. They are noticing there is incomplete information. We need an industry wide focus on data quality at the source. The better information we have from all sources leads to equitable treatment. That is what is necessary to ensure that interoperability is fulfilling its highest calling and keeping the patient at the center of care.
High quality data capture is critical to improving health care in general. It helps us engage the community in an active role in their health care—and that improves outcomes. It’s not just improving the data we have, but proactively looking for the absence of information that can improve health equity for often underrepresented and underserved populations.
It’s one thing to be able to create connection points for the national exchange of data, but if the data is incomplete, inaccurate, or not trustworthy, we’re going to fall short. Ensuring we have that right balance of quality versus quantity and the proper checks and balances is essential. That allows us to confidently say that the data can become actionable and meaningful.