Sociotechnical probabilistic risk modeling to predict injurious falls in community living centers.

Abstract

The goal of this study was to apply sociotechnical probabilistic risk assessment to prioritize risks and prevention strategies for serious injurious falls of residents in nursing homes. Risk modeling teams consisted of 26 clinical and nonclinical staff from three Department of Veterans Affairs community living centers and one state Veteran's nursing home. Participants met in groups several times to identify and assign probabilities to provider and resident at-risk behaviors and equipment failures. They identified prevention strategies for the failures that accounted for the highest levels of risk. Six scenarios were modeled: (1) transferring from bed to wheelchair, (2) propelling from bedside to bathroom, (3) transferring from wheelchair to toilet, (4) transferring from toilet to wheelchair, (5) propelling from bathroom to bedside, and (6) transferring from wheelchair to bed. The greatest paths of risk were for residents with impaired mobility and high fragility. A 26% reduction in injurious falls could be achieved by (1) reducing the number of unassisted transfers through a modest improvement in response time to alarms, (2) installing automatic brake locks on 90% of wheelchairs, (3) making the wheelchair maintenance process highly reliable, and (4) decreasing improper transfer techniques by 10%.