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How data analysis helps a California county identify barriers to behavioral health care

We often hear that people who suffer behavioral or mental health disorders may be too stigmatized to seek the help they need. Public health officials in San Bernardino County, California thought that too – until data analysis dispelled some of their misconceptions. The SAS case study below is an interesting look at how technology helps surface new insights that lead to better outcomes for vulnerable populations.
-- Philip Bane


People will talk about their battles with cancer, diabetes or a difficult pregnancy. But how often do you hear someone discuss their severe depression or substance abuse around the office water cooler?

Most would agree there's a stigma associated with behavioral or mental health disorders. Because of that, people are often uncomfortable or intimidated about seeking the help they need. San Bernardino County Department of Behavioral Health (DBH) officials wanted to change that.

They enlisted the help of Council Lead Partner SAS and its data management and advanced analytics solutions to address the stigmatization challenge and to help guide their service and community outreach strategies. They also wanted to see what data could tell them about reducing hospital readmissions and improving the quality of care they provide county residents.

"We need to make good decisions about the community we're serving, and the best way to do that is to collect, manage and analyze data," said Sarah Eberhardt-Rios, Deputy Director for Program Support Services at DBH. "One of the benefits of our SAS data warehouse is the ability to bring a lot of disparate data sources together, as this helps tell a person’s story and shapes how we can assist."

What DBH learned
Here are a few examples of what the agency learned via deep dives into that data.

  • Stigmatization:The data actually revealed a different, less stigmatizing picture than many people in the field have thought. "In the past, we’ve developed systems and business processes under the assumption that people frequently avoid care. But analytics tells us that they’re often eager to access services," said Dr. Joshua Morgan, Chief of Behavioral Health Informatics for DBH. "We found that they’ve been knocking on our doors, but sometimes the most appropriate intervention services have been difficult to access, mostly because the array and types of services we offer aren’t widely known. If their inability to access services is due to a barrier that we have unintentionally contributed to, we work diligently to change that."
  • Improving access:DBH maps data about its consumer population and uses the maps to determine the best locations for different behavioral health services that will best meet the location needs of those they serve. Analysts can see which areas need improved access, find places they thought were underserved that actually weren’t, and see how this affects their network of providers.
  • Hospital readmissions:The data also reveals patterns of re-hospitalization. The department reviewed how long people had been in care, what systems they came from, what services were used and what services could potentially keep them out of the hospital. DBH discovered that it had preconceived notions about hospitalizations and how to connect patients to outpatient services. This insight was used to change how the department provided outreach for outpatient services, to both consumers and hospital staff.

A faster, nimbler DBH
SAS analysis has helped DBH identify patterns that it would not be able to otherwise detect.

"We start with a question or hypothesis and mine our data warehouse for answers," Eberhardt-Rios explains. "If we find that our hypothesis was wrong, we ask additional questions. This approach saves us months or years of manual or other types of analysis. Ultimately, we become much faster and nimbler, which means our community members are getting the health services they need quicker."

Related articles…
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IBM Video: Solving social service challenges with analytics
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