Implementation of major organizational change initiatives presents a challenge for long-term care leadership. Implementation of the INTERACT® (Interventions to Reduce Acute Care Transfers) quality improvement program, designed to improve the management of acute changes in condition and reduce unnecessary emergency department visits and hospitalizations of nursing home residents, serves as an example to illustrate the facilitators and barriers to major change in long-term care. As part of a larger study of the impact of INTERACT® on rates of emergency department visits and hospitalizations, staff of 71 nursing homes were called monthly to follow-up on their progress and discuss successful facilitating strategies and any challenges and barriers they encountered during the yearlong implementation period. Themes related to barriers and facilitators were identified. Six major barriers to implementation were identified: the magnitude and complexity of the change (35%), instability of facility leadership (27%), competing demands (40%), stakeholder resistance (49%), scarce resources (86%), and technical problems (31%). Six facilitating strategies were also reported: organization-wide involvement (68%), leadership support (41%), use of administrative authority (14%), adequate training (66%), persistence and oversight on the part of the champion (73%), and unfolding positive results (14%). Successful introduction of a complex change such as the INTERACT® quality improvement program in a long-term care facility requires attention to the facilitators and barriers identified in this report from those at the frontline.

Background: Driving is a complex behavior that may be affected by early changes in the cognition of older individuals. Early changes in driving behavior may include driving more slowly, making fewer and shorter trips, and errors related to inadequate anticipation of situations. Sensor systems installed in older drivers’ vehicles may detect these changes and may generate early warnings of possible changes in cognition. Method: A naturalistic longitudinal design is employed to obtain continuous information on driving behavior that will be compared with the results of extensive cognitive testing conducted every 3 months for 3 years. A driver facing camera, forward facing camera, and telematics unit are installed in the vehicle and data downloaded every 3 months when the cognitive tests are administered. Results: Data processing and analysis will proceed through a series of steps including data normalization, adding information on external factors (weather, traffic conditions), and identifying critical features (variables). Traditional prediction modeling results will be compared with Recurring Neural Network (RNN) approach to produce Driver Behavior Indices (DBIs), and algorithms to classify drivers within age, gender, ethnic group membership, and other potential group characteristics. Conclusion: It is well established that individuals with progressive dementias are eventually unable to drive safely, yet many remain unaware of their cognitive decrements. Current screening and evaluation services can test only a small number of individuals with cognitive concerns, missing many who need to know if they require treatment. Given the increasing number of sensors being installed in passenger vehicles and pick-up trucks and their increasing acceptability, reconfigured in-vehicle sensing systems could provide widespread, low-cost early warnings of cognitive decline to the large number of older drivers on the road in the U.S. The proposed testing and evaluation of a readily and rapidly available, unobtrusive in-vehicle sensing system could provide the first step toward future widespread, low-cost early warnings of cognitive change for this large number of older drivers in the U.S. and elsewhere.