Using Data to Reduce Stigma and Discrimination Around Mental Illness

 

Connecting state and local government leaders

“There’s a way to start quantifying things we wouldn’t normally capture,” according to San Bernardino County’s chief of behavioral health informatics.

OXON HILL, Md. — San Bernardino County uses data to identify needs within its public behavioral system and reduce hospital visits, inpatient days and recidivism.

A mix of rural and urban areas, the large, diverse Southern California county has residents who live as many as 80 miles away from the nearest hospital, and a quarter of its population of 2 million residents has Medi-Cal—the state’s Medicaid system.

About one-in-five people experience mental illness a year in the U.S., and one-in-five people with mental health disorders visit a hospital annually, according to data from the National Alliance for Mental Illness. But there’s more to these figures than meets the eye.

“Talking about how ‘they’re filling up our hospitals’ is not an accurate portrayal of who these people are,” said Josh Morgan, the county’s chief of behavioral health informatics and a psychologist, during a Tuesday morning session at SASAnalytics Experience 2017 in the Gaylord National Resort and Convention Center near the nation’s capital.

Taking a hard look at the data reduces the stigma and discrimination around mental illness, Morgan said, because while impoverished people with serious, chronic mental illness stay in the system for 20 to 30 years, only 4 to 5 percent of them visit a hospital in any given year.

Data can also help combat NIMBYism—or “not-in-my-backyard” sentiment—that sees officials or community members resist development of recovery centers or deny there’s a problem at all.

Mental illness is the leading cause of disability and suicide, which impose high costs on states, and California has attempted to address the situation with its Mental Health Services and Mental Health Wellness acts. Such policies are full of themes of recovery and resilience, but those goals aren’t necessarily tied to specific measurements or requirements, Morgan said.

When San Bernardino County needed to decide whether to continue a funding stream for its Serving Transitional Age Youth program, a short-term crisis residential facility for clients ages 18 to 26, it helped traditional data showed 73 percent exhibited improvement in being considered a suicide risk.

More useful? Nontraditional data showed 58 percent of clients experienced an uptick in optimism—feelings of hopelessness being the No. 1 factor in suicides, Morgan said.

One in four primary-care patients have depression, according to data from the Substance Abuse and Mental Health Services Administration, but their physicians only identify a third of those cases precisely because measures like optimism are hard to capture. That doesn’t mean health care organizations can’t or shouldn’t, especially when it impacts their reimbursement two to three years later.

A holistic picture of outcomes might mean scoring hopefulness on a scale of one to 10, recognizing that won’t capture the essence of “hope” but that it captures something, Morgan said.

“There’s a way to start quantifying things we wouldn’t normally capture,” he said.

Another benefit of San Bernardino County’s use of data is that it’s helped bring stakeholders and the public health system together using Sheriff’s Department arrest, Arrowhead Regional Medical Center hospitalization, Department of Behavioral Health, Department of Public Health, and Homeless Management Information System datasets. Data visualizations have been incorporated into stakeholder meeting handouts to foster a “culture of analytics” among the public, which has become more engaged.

The Sheriff’s Department brass has stopped viewing people with mental illnesses as a time suck and burden on jails—a classic warning sign a public behavioral system isn’t using data effectively.

“How often does law enforcement rave about behavioral health people being embedded with them?” Morgan said.

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