Mental health equity achieved through innovative artificial intelligence and technology based solutions

Like food deserts, where communities are deprived of adequate food resources, “mental health care deserts” also exist, where communities do not have access to quality affordable mental health care and face barriers to receiving treatment. These deserts contribute to “mental health equality gaps”, the gap between the need for mental health treatment and services available.

Over 43 million people in the U.S. experience mental illness yearly. However, 56 percent of adults with a mental illness in the US do not receive treatment. Although race, ethnicity, income, or place of residence should not determine who receives treatment, the reality is that some populations face distinct challenges to receiving the effective mental health care.

Reducing mental health disparities and expanding health equity should be of the highest priority for the medical establishment. It was with this mindset that the University of Illinois Department of Psychiatry established its new digital mental health center, the Enhancing Quality and Access Leveraging Digital Mental Health (EQUAL-DMH) Center. Charged with closing the mental health gap through the use of new technologies, as well as addressing the current mental health care crisis, the EQUAL-DMH Center is a first-of-its-kind center in Illinois that combines pioneering research and custom treatment to realize tomorrow’s medicine today.

The EQUAL-DMH Center is represented by a collaborative, transdisciplinary group of clinicians, researchers, educators, and stakeholders working to improve equitable access to mental health treatment with innovative smart, connected technology.  The EQUAL-DMH Center supports cutting-edge research to develop evidence-based digital tools, apps, inventions, and other technology based mental health treatment.

Closing the mental health gap through technology

The mental health equality gap disproportionally affects communities of color and marginalized identities, with only 23% of Asian Americans, 33% of Black Americans and 34% of Hispanic/Latinx Americans with mental illness receiving treatment in the last year. The prevalence of depression in the U.S. has increased, as it has globally, catapulting depression to the number one cause of disability worldwide. This crisis has come at a staggering cost; estimates place the economic cost of mental illness in the U.S. to be more than 193 billion dollars a year in lost earnings.  Lack of access to treatment, coupled with inefficient models of care, lie at the heart of this crisis; these factors have only worsened over the past two years due to the impact of the COVID-19 pandemic and racial unrest. Those seeking proper diagnosis and management for their mental health conditions can be faced with barriers such as medically underserved communities, socio-economic factors, a shortage of psychiatrists and other mental health specialists, as well as cultural and societal stigmas.

The EQUAL-DMH Center, with strengths in psychiatric research, machine learning, intervention development and health equity, is uniquely positioned to address these challenges. The center has developed a wide range of innovative, technology-enabled solutions to address the lack of access to mental health treatment, as well as provider shortages.

The center leverages these existing strengths to address these challenges through three interacting themes:

  • Digital phenotyping/Fundamental processes
  • Digital mental health interventions
  • Enterprise-level innovation


Digital Phenotyping/Fundamental Processes

This theme encapsulates those efforts using fundamental data science techniques (machine learning, multimodal data fusion) in support of digital phenotyping, the ability to characterize behavioral phenotypes through our interactions with smart, connected devices and wearable technologies. The work has the potential to address health disparities in mental health treatment by developing more bias-free, objective methods of assessment. UIC has several strengths in this area as evidenced by the projects including BiAffect, a smartphone app that seeks to identify digital “biomarkers” that will predict and monitor manic and depressive episodes in people with mood disorder by unobtrusively monitoring keyboard dynamics metadata.


Digital Mental Health Interventions

This theme covers the development of the digital health interventions for mental health conditions, an area where UIC has had considerable success in recent years. UIC researchers have created numerous tools that have been particularly effective in marginalized communities.

DiaBetty - DiaBetty utilizes Amazon’s Alexa platform as a diabetes coach and educator that is sensitive and responsive to the patient’s mood. The artificial intelligence-based technology is designed to assist patients newly diagnosed with type 2 diabetes. Given the issues of diabetes-related stress and the negative impact of depressive symptoms on type 2 diabetes, patients need solutions to help manage diabetes in the context of their mood and lifestyle.

Sunnyside for Moms - Sunnyside for Moms is a web-based cognitive behavioral therapy intervention targeting postpartum depression. Sunnyside for Moms combines cutting-edge technology, enhanced mental health outreach efforts, and new opportunities to identify blood biomarkers for depression to help moms from low-income communities identify, manage, and treat perinatal depression. The program’s mental health screening has demonstrated success in reducing depressive symptoms during pregnancy and preventing the development of postpartum depressive episodes.


Enterprise-Level Innovation

This theme encapsulates projects that utilize health informatics and machine learning techniques to innovate at the level of the healthcare enterprise. Under the theme of enterprise-level innovation, the center is developing a model to optimize scheduling of new patients based on resource requirements and provider capacity.  

The center will also support groundbreaking work in the use computation and systems-based approaches to substance misuse, using natural language processing based digital classifiers to screening inpatients for substance use disorders.

“It is the duty of the EQUAL-DMH Center to use its research and clinical experience to develop models of care that can efficiently and effectively treat mental illness, with a continued mission of implementing evidence-based scalable mental health solutions that expand mental health accessibility,” says Dr. Olusola Ajilore, director of the EQUAL-DMH Center.

For more information on the EQUAL-DMH Center, click here.


EQUAL-DMH Center Leadership:

Olusola Ajilore, MD, PhD, Director

Niranjan Karnik, MD, PhD

Alex Leow, MD, PhD

Jenna Duffecy, PhD

John Zulueta, MD