Evolution of an Early Illness Warning System to Monitor Frail Elders in Independent Living

Gregory Alexander, Marilyn Rantz, Marjorie Skubic, Richelle Koopman, Lorraine Phillips, Rainer Guevara, Steven Miller
2011 Journal of Healthcare Engineering  
This paper describes the evolution of an early illness warning system used by an interdisciplinary team composed of clinicians and engineers in an independent living facility. The early illness warning system consists of algorithms which analyze resident activity patterns obtained from sensors embedded in residents' apartments. The engineers designed an automated reasoning system to generate clinically relevant alerts which are sent to clinicians when significant changes occur in the sensor
more » ... , for example declining activity levels. During January 2010 through July 2010, clinicians and engineers conducted weekly iterative review cycles of the early illness warning system to discuss concerns about the functionality of the warning system, to recommend solutions for the concerns, and to evaluate the implementation of the solutions. A total of 45 concerns were reviewed during this period. Iterative reviews resulted in greater efficiencies and satisfaction for clinician users who were monitoring elder activity patterns. abilities as users interact with the clinical technology to make clinical decisions or to document care provided. Positive outcomes from this process include fewer errors involving patients, healthcare personnel, and other users; decreased training costs; a better fit with the way clinicians work and think; reduced time spent redesigning systems; and greater user satisfaction. This paper describes the evolution of an early illness warning system being designed by members of the Center for Eldercare and Rehabilitation Technology (also called the Eldertech team) at the University of Missouri in the Midwestern US. The early illness warning system is being developed and used in an independent living facility, TigerPlace. The early illness warning system incorporates algorithms that issue automated alerts to clinicians, warning them of potential declines in activity levels and acute health events experienced by residents living in TigerPlace.
doi:10.1260/2040-2295.2.3.337 pmid:22211161 pmcid:PMC3248794 fatcat:356chms2arco5p4lja5lfv5mwi