At a glance
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Predictive Analytics Combined With Computer Visualization Enhances Patient Safety and Eases Nurse Burden for Preventing Falls
In Brief
A clinical study evaluating Fall prevention algorithm and Inspiren camera visualization for Fall Patients and Fall Injury. Completed, enrolled 5,350 participants across 1 site.
Detailed Summary
Annually, in the United States there are 700,000 - 1,000,000 inpatient falls reported, and one-third of patients sustain an injury. The average estimated cost per fall is $6,694, resulting in over $1.4 -1.9 billion dollars in losses each year (AHRQ, 2017). This study aims to compare the impact of different fall prevention strategies on the rate of occurrence of falls and falls with injury in an academic medical center on three adult medical units. While maintaining the usual standard of care for fall prevention, each unit will add one of the following: (1) use of a fall risk alert to nurses using an algorithm based on electronic health record data or (2) computerized camera visualization or (3) a combination of both.
Study Details
Timeline
Interventions
Algorithm generates fall prevention alerts to nurses in real time, using evidenced based electronic health record information regarding changes in care that may suggest the need for additional fall prevention strategies
The Inspiren computer camera visualization is an additional strategy for nurses to employ when there is a change in a patient's fall risk.