Decision Support Systems and Behavioral Informatics to Advance Safe, Independent Living in the Home and Community
CHAIR
PRESENTERS
DESCRIPTION
People who sustain moderate to severe traumatic brain injury (TBI) often have cognitive, physical and behavioral impairments that limit their ability to safely and independently carry out activities. The combination of disability and multiple chronic conditions substantially increases their risk of unsafe events in the home and community, and rehospitalizations. Home and community-based service providers often have limited training and experience in meeting the broad needs of persons with chronic TBI-related impairments. Population-based, capitation healthcare payment models provide potential opportunities for preventive and wellness services. The development of automated decision support systems using medical record data, observations, and behavioral informatics has the potential to optimize diagnostics and tailor personalized intervention programs through monitoring; data translation; severity-based, just-in-time, treatment recommendations; and regular, actionable feedback. We will present our most recent findings on innovative, scalable, and portable behavioral informatics approaches to delivering safety, health and activity-related diagnostics and intervention programs for people with TBI-related disabilities.
LEARNING OBJECTIVES
- Describe the decision-making hierarchy and rationale used to develop a decision support system.
- Identify the components of unobtrusive data collection and monitoring required to generate behavioral informatics upon which inferences can be made.
- Characterize the data required to develop inferential algorithms for health behavior monitoring.
