The 30,000 Foot View: Using Big Data to Address Complex Clinical Questions in the Most Vulnerable Older Adults

Older people of color, those who are socially isolated, veterans, and incarcerated older adults experience disparities in mental healthcare and high levels of psychiatric and physical comorbidity, including increased risk of suicide. The identification of risk factors and understanding the culture and context that impact risk are major public health challenges. Effective approaches to address these challenges are likely to involve using national databases and applying advanced methodologies to address complex clinical questions in older adults. By leveraging extensive epidemiological datasets, we can effectively pinpoint risk factors and consequences associated with mental health disorders in later stages of life. Moreover, these datasets allow us to disaggregate heterogeneous groups which are often treated as homogeneous (e.g. people of color, veterans, etc.). This disaggregation may reveal significant within group differences and provide important contextual information regarding these groups which can be used to deliver precision mental healthcare in an efficient manner and reduce the burden of mental illness in late life. In this session, we will explore innovative methodologies of utilizing national datasets to discern the cultural and contextual elements that impact the mental health and well-being of four high-risk, older adult populations. Emphasis will be placed on identifying patterns in mental healthcare disparities and comprehending how factors such as race, ethnicity, sex, gender, and incarceration contribute to feelings of loneliness, suicide rates, and dementia. Furthermore, we will also discuss the potential application of this data in developing precise risk assessment tools and targeted prevention and treatment strategies. interventions for late-life mental health issues.