How data can narrow your innovation focus

Attempting to transform your health care system can feel a lot like playing a game of Whac-a-Mole. You fix a small process at one facility. You overhaul a large department in another. But there are many other issues waiting and ready to surface.

Ultimately, we, as health care organizations, have to narrow the types of problems we want to solve. For OSF HealthCare, that means prioritizing efforts that align with our Mission and strategic goals. One of those goals is to address disparities in health outcomes and factors that impact peoples’ well-being.

To concentrate our efforts even further, OSF Innovation is working with Bradley University to collect and analyze internal and external data that speak to the populations we serve. The goal is to define groups that need help the most. Our work has led to the publication of three papers in academic journals.

Taking a look at the numbers

Every three years, OSF HealthCare and many other health care systems are required to do a Community Health Needs Assessment as part of the Affordable Care Act of 2010. This assessment identifies key health needs among the populations the Ministry serves. We are using this information to validate assumptions we have about a particular population or show us that we need to focus elsewhere.

Medicaid Expansion and Accessibility to Healthcare: The Illinois Experience

There is a belief bias among lawmakers and leaders in health care that expanding Medicaid to more people will increase access to medical and dental care, pharmaceuticals and mental health counseling. However, that is only partially true. In our paper, the research shows that an Illinois Medicaid expansion in 2014 flattened the gap between access to care for rural and urban populations. However, poor individuals, racial/ethnic groups and younger people still faced significant barriers to health care. As a health care system, this gives us a better idea of where we should focus outreach efforts for Medicaid education.

The Relationship between Access to Mental Health Counseling and Interest in Rural Telehealth

COVID-19 resulted in a major increase in telehealth options, so people could be safely treated at home. It has also been touted as a way to bring more specialty care to rural areas. In this report, we sought to compare interest in using digital options for mental health counseling among rural and urban groups. Our findings show that rural communities that do not have access to mental health resources are more interested in telehealth than their urban counterparts. Young adults had the most interest in using the technology. This data shows us the need to develop best practices for bringing telehealth to rural communities.

In addition to the Community Health Needs Assessment, we also used de-identified data from our Enterprise Data Warehouse (EDW) to pull information for further research. Our EDW is a centralized system where data from numerous sources are standardized and normalized to help derive insights.

Auto-assignment of providers in Medicaid Managed Care and Factors Influencing Seasonal Flu Vaccine Uptake: A Retrospective Analysis

An individual with Medicaid is expected to choose a primary care provider. But if they don’t, they are assigned one. We took a look at how this might impact a person’s decision to get the flu vaccine. Our study found that individuals who did not choose their primary care provider were less likely to get their flu shots than those who chose their clinicians. We believe this information can be useful as we work to get more people vaccinated against COVID-19.

Building paths forward

The information we’ve gathered from our Community Health Needs Assessment, patient records and claims data is just a small part of the work we are doing with data. In partnership with Bradley University and others, our goal is to create an environment where different types of data drive all of our innovative efforts.

If you’d like to learn more about how we are using data to transform health, take a look at our work on the Data Science and Advanced Informatics Lab page.

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