Ana Lòpez-DeFede, PhD, is Director of the Division of Medicaid Policy Research at the University of South Carolina Institute for Families in Society. Dr. Lopez-DeFede, at a recent Medicaid 2.0 work group, explained how her state uses Medicaid data to improve health quality.

Your organization is contracted by South Carolina’s Medicaid program to produce a website and usable information on cost and utilization data. What makes your state unique in how you share Medicaid data? 

We’ve been working with Medicaid since 1997 and have their data and an extensive history of working with it. For South Carolina, transparency is important and so is the ability of the average person to access the data. We really wanted a platform that would be accessible and easy-to-use for an individual conducting research, local planners or, say, a state legislator who wanted to understand the Medicaid population in his or her district. People can get data even over a period of multiple years at our website.

What kind of data do you share and how is the information being used?

 We present the data in different categories, such as Medicaid enrollment, and benefits and services. You can examine these categories by geography, age, or whether someone is in a Medicaid managed care plan or not. You could determine how Medicaid impacts one specific area of the state. You could find the number of in-patient hospital visits by age group. You could compare Medicaid managed care versus fee-for-service as it relates to ER visits or hospitalizations. We also provide information on quality improvement initiatives, health care reform and health disparities.  A good example is birth outcomes where an infographic shows the gains made as a result of the state’s Birth Outcomes Initiative. Users can see the patterns around low birth weight and read a very quick summary to understand the gains made and where there is a need for further improvement. The data is easily interpreted.

How could Medicaid data be valuable to a state such as New Jersey?

For New Jersey, one of the important things would be to make the data easy to use.  You can look at categories such as how many Medicaid recipients are blind or disabled. People who might want this information may not know the Medicaid codes and categories so you need to make the data easy to interpret. An agency or organization could see where the needs are and then see where there are gaps in services. The data make it easier to understand what the issues are across the state — and how to translate that knowledge into action.

Who is using the data?

 On a monthly basis, we have several thousand people accessing our data. … Let’s say I am a state legislator. I could look at my district and understand the percentage of people who are on Medicaid and how that breaks down in terms of race, ethnicity —and how that compares to another geographic area. If I am a juvenile judge, and I am interested in behavioral health services for juveniles, I might want to look at Medicaid providers offering behavioral health services in my area. We try to provide an understanding of the uninsured population in the state. We are a non-expansion state. We can provide information about who would be eligible under expansion and who would not. A United Way or free clinic could hone in on where the services are needed. Our goal is to be transparent and provide user-friendly data and maps.

What do you see as the biggest success and lessons learned in South Carolina?

The biggest overall recognition the state has received is on the platform and the usability of the data. Our feedback from users is that they are pleased by what they can do. If anything, they want more information and more updates. We’ve learned to be flexible and to continually update things and provide story maps and info graphics. We’ve discovered that our data is not only valuable for people in South Carolina but we have folks from all over the country looking at this data. You can use our data without any special software.

As I mentioned, we’ve used the data to examine infant mortality and low birth weight babies. You can add a graphic layer showing where the ob-gyn providers are and you can look at age groups and whether the mothers with low birth weight babies had access to prenatal care. You can find the “hot spots,” these areas with high numbers of low birth weight babies and low numbers of ob-gyns. Suddenly you have a picture. You can provide better care in these geographic areas and positively impact the circumstances associated with poor outcomes.