Dementia risk analysis using temporal event modeling on a large real-world dataset

The objective of the study is to identify healthcare events leading to a diagnosis of dementia from a large real-world dataset. This study uses a data-driven approach to identify temporally ordered pairs and trajectories of healthcare codes in the electronic health record (EHR). This allows for discovery of novel temporal risk factors leading to an outcome of interest that may otherwise be unobvious. We identified several known (Down syndrome RR = 116.1, thiamine deficiency RR = 76.1, and Parkinson's disease RR = 41.1) and unknown (Brief psychotic disorder RR = 68.6, Toxic effect of metals RR = 40.4, and Schizoaffective disorders RR = 40.0) factors for a specific dementia diagnosis. The associations with the greatest risk for any dementia diagnosis were found to be primarily related to mental health (Brief psychotic disorder RR = 266.5, Dissociative and conversion disorders RR = 169.8), or neurologic conditions or procedures (Dystonia RR = 121.9, Lumbar Puncture RR = 119.0). Trajectory and clustering analysis identified factors related to cerebrovascular disorders, as well as diagnoses which increase the risk of toxic imbalances. The results of this study have the ability to provide valuable insights into potential patient progression towards dementia and improve recognition of patients at risk for developing dementia.

Tracking the Rise of Geriatric Emergency Departments in the United States

The traditional model of emergency care no longer fits the growing needs of the over 20 million older adults annually seeking emergency department care. In 2007 a tailored "geriatric emergency department" model was introduced and rapidly replicated among hospitals, rising steeply over the past 5 years. This survey examined all U.S. emergency departments self-identifying themselves as Geriatric Emergency Departments (GEDs) and providing enhanced geriatric emergency care services. It was guided by the recently adopted Geriatric Emergency Department Guidelines and examined domains including, GED identity, staffing, and administration; education, equipment, and supplies; policies, procedures, and protocols; follow-up and transitions of care; and quality improvement. Results reveal a heterogeneous mix of GED staffing, procedures, physical environments and that GEDs' familiarity with the GED Guidelines is low. Findings will inform emergency departments and gerontologists nationwide about key GED model elements and will help hospitals to improve ED services for their older adult patients.