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How data-informed policy can empower behavioral health recovery and stigma reduction

How we measure behavioral health success can actually increase stigma and discrimination. Data and analytics can shift the focus to positive outcomes.

Before diving into this article, take a moment to stop and look around you. 

Whether you’re in the office, at a café, coffee shop, or about to sit down with family or friends, notice the number of people around you or think about those close by.  

Now, take that sample you’ve created and split it in half.  

That mental divide you just made represents the fifty percent of people that will meet criteria for a mental illness diagnosis at some point in their lives. 

In the state of California, mental health disorders are among the most common health conditions faced by the state’s residents. A report supported by the California Health Care Foundation even stated that 1 in 24 Californians have a mental illness so serious that it impedes their ability to function and participate in normal activities of daily life. With such a staggering number of behavioral health diagnoses in our country, how has the stigma and discrimination surrounding them been affected? 

Sure, we see several contributing factors to this statistic on a day to day basis… and if we really wanted to get into the nitty gritty of it we could pick up a textbook or read more online… but when’s the last time we reflected and looked at ourselves to understand how we might be unintentionally playing a part in this stigma?  

It’s ironic that our healthcare system is increasingly focused on strengths-based and person-centered principles, yet the measurements of success, results, and language around mental illness in our system do not carry the same uplifting verbiage and/or standards for its patrons. In fact, I would argue that our language around mental illness further perpetuates this stigma and discrimination.  

Language in general is one of the major influences on stigma, discrimination, and even access to healthcare. Put simply, it matters, and we need to be more mindful of how we are discussing mental illness moving forward – not only from an individual perspective but at the policy level and how we are using it within our legislation as well. 

As mentioned earlier, policies in our healthcare system have been written in a dialect with success in mind. If this is so, then why is there such a disconnect between the actual outcomes?  

One key factor is because the results and outcomes being measured are based upon the principle of decreasing negative components associated with mental health conditions, instead of looking for an increase or change among positive ones.   

The negative side effects of well-intentioned policy 

Consider California Senate Bill 82, the positively framed Mental Wellness Act of 2013. Since people with mental health conditions impact multiple systems such as hospitals and the criminal justice system, SB82 was put in place to help address those significant public costs. A goal of SB82, which is still in effect and funded, is to “reduce unnecessary hospitalizations and inpatient days by appropriately utilizing community-based services and improving access to timely assistance.”  

Similarly, the California Mental Health Services Administration states that Prevention and Early Intervention programs “shall emphasize strategies to reduce the following negative outcomes that may result from untreated mental illness.” Those outcomes include suicides, incarcerations, school failure or dropout, unemployment, prolonged suffering, homelessness and removal of children from homes.  

This shows how we associate, talk about, and measure only the “bad stuff” when referring to people with behavioral health conditions. I won’t deny these outcomes are important and yes, it may be easier to collect that data than data related to recovery and resilience – but we need to consider if our measured outcomes reinforce stigma unnecessarily. 

As a society we cannot be complacent with statistics that aren’t telling the whole story or telling a skewed one. 

When I was the Chief of Behavioral Health Informatics in San Bernardino County, we used data to challenge our basic assumptions. We explored how RBEST, or Recovery Based Engagement Support Teams, impacted the consumers’ treatment path.  

RBEST is an innovative approach to fostering and developing trust with individuals who have been inappropriately served, underserved or unserved and who suffer from untreated, severe chronic and persistent mental illness.  

As a short-team learning project, the two primary learning goals of the RBEST project were to 1) increase the quality of services, including better outcomes, and 2) reduce the frequency of mental health related emergency room visits and unnecessary psychiatric hospitalizations. The RBEST project strived to service clients in the least intrusive, restrictive, and disruptive way in order to promote consumer resiliency and recovery, as well as to preserve and maintain the individual’s dignity and self-worth, while linking them to appropriate behavioral health services. 

In order to de-stigmatize the focus on mental wellness and help us get closer to achieving health equity, we must advocate for and support more whole person approaches to data, analytics, and evaluation. Instead of reporting on just symptoms and pathology, we need to try focusing on contextual factors, like family support and reshaping our services to better engage with families and loved ones. With RBEST, we found the importance of not only focusing on the health of the patient, but also engaging family members and loved ones as allies in supporting  the highest quality of care.  

During an initial evaluation of the RBEST project, negative outcomes decreased: Review of hospital admissions prior to engagement in comparison to post engagement indicated a 43% reduction in hospital admissions and a 37% reduction in total hospital days. And positive outcomes also increased: Upon ending RBEST engagement, results also showed a significant improvement in family satisfaction in addition to a 49% reduction in crisis services. 

When the power of data and analytics come into play, there’s nothing stopping us from building a system that is truly person-centric and strengths-based to the core. If we can continue to provide evidence and data that backs it up, we are one step closer to achieving health equity in America, influencing public policy, funding, culture, and more. 

Discover how analytics to support whole person care can improve the health care system by viewing this free on-demand webinar.


As SAS’ National Director of Behavioral Health and Whole Person Care, Dr. Josh Morgan helps public health agencies use data and analytics to support a person-centered approach to improving health outcomes. A licensed psychologist, Morgan was previously the San Bernardino County Department of Behavioral Health’s Chief of Behavioral Health Informatics. His clinical work includes adolescent self-injury, partial hospitalization, intensive outpatient programs, psychiatric inpatient units and university counseling centers. Morgan earned his Bachelor of Arts in religious studies from the University of California, Berkeley, and a PsyD (Doctor of Psychology) in clinical psychology with an emphasis in family psychology from Azusa Pacific University.

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