Given that dementia represents the major cause of loss of autonomy in older adults, a diagnosis of Alzheimer's disease and its related dementias (ADRD) could represent a critical moment that increases the risk of suicidal ideation (SI) and attempt (SA). However, despite significant research progress in the past decade, it remains unclear if there are ?clusters? of patients with ADRD who are at an increased risk for suicide, and how utilization of healthcare services, or the lack thereof, might be associated with SI/SA rates. This supplement will use large-scale commercial health insurance claims data and advanced machine learning algorithms to study these questions.
As of 2015, annual age-adjusted suicide rate in the U.S. is 13.26 per 100,000 individuals, and on average, there are 121 suicides per day. Successful identification of patients who are at the risk of self-harm, suicide attempt, and suicide can lead potential clinical interventions for improving patient outcomes. This proposal will apply ?big data? techniques to identify patients at risk of suicidal behavior using large-scale integrated clinical data.
