Nurses' Experience Implementing an Automated Video Monitoring System to Decrease the Risk of Patient Falls during a Global Pandemic.

Healthcare is a complex sociotechnical system where information systems (IS) and information technology (IT) intersect to solve problems experienced by patients and providers alike. One example of IS/IT in hospitals is the Ocuvera automated video monitoring system (AVMS), which has been implemented in more than 30 hospitals. The purpose of this study was to evaluate nurses' attitudes toward AVMS implementation over time as they received the training program developed for this intervention. Consistent with the job demands-resources (JDR) model, we found that perceptions of AVMS usefulness increased over time and were positively associated with perceptions of social influence and behavioral control. These results were consistent with our finding that there was a significant decrease in the risk of unassisted falls from the bed from baseline to intervention. Leaders in hospital systems and healthcare organizations may want to consider implementing an AVMS as researchers continue to test, verify, and demonstrate the effectiveness of these interventions for improving patient well-being.

Evaluation of Automated Video Monitoring to Decrease the Risk of Unattended Bed Exits in Small Rural Hospitals.

OBJECTIVES: This study aimed to evaluate the effectiveness of using 1 to 4 mobile or fixed automated video monitoring systems (AVMSs) to decrease the risk of unattended bed exits (UBEs) as antecedents to unassisted falls among patients at high risk for falls and fall-related injuries in 15 small rural hospitals. METHODS: We compared UBE rates and fall rates during baseline (5 months in which patient movement was recorded but nurses did not receive alerts) and intervention phases (2 months in which nurses received alerts). We determined lead time (seconds elapsed from the first alert because of patient movement until 3 seconds after an UBE) during baseline and positive predictive value and sensitivity during intervention. RESULTS: Age and fall risk were negatively associated with the baseline patient rate of UBEs/day. From baseline to intervention: in 9 hospitals primarily using mobile systems, UBEs/day decreased from 0.84 to 0.09 (89%); in 5 hospitals primarily using fixed systems, UBEs/day increased from 0.43 to 3.18 (649%) as patients at low risk for falls were observed safely exiting the bed; and among 13 hospitals with complete data, total falls/1000 admissions decreased from 8.83 to 5.53 (37%), and injurious falls/1000 admissions decreased from 2.52 to 0.55 (78%). The median lead time of the AVMS was 28.5 seconds, positive predictive value was nearly 60%, and sensitivity was 97.4%. CONCLUSIONS: Use of relatively few AVMSs may allow nurses to adaptively manage UBEs as antecedents to unassisted falls and fall-related injuries in small rural hospitals. Additional research is needed in larger hospitals to better understand the effectiveness of AVMSs.