Annotated Bibliography on Technology in Nursing

Technology in healthcare has led to many advancements that improve patient care. As an assistant director of nursing for long term care, I often look for ways to improve patient care. Falls and pressure ulcers are the areas I focus on the most as they are unfortunate the most prevalent patient quality of life issues I encounter. I utilized the Capella library in order to access databases such as PUB med and OVID to select peer-reviewed scholarly articles which are within the last five years. I used terms such as “patient sensor falls prevention technology” and “technology to reduce pressure ulcers” during my research. I then selected the research that focused most on patient monitoring technology that can be used to reduce falls and pressure ulcers in long term care. Ali, H. B., & Li, H. (2015). Developing a fall-prevention system for nursing homes. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 59(1), 601-605. doi:10.1177/1541931215591132. In this article the authors review current fall prevention systems implemented in nursing homes, challenges involved with these current systems and how technology can be used to mitigate these challenges. The article discusses the advantages and challenges of currently used systems such as chair/bed sensors, clip alarms and call light systems. A literature review was conducted and showed that these systems may not be effective in preventing falls. A systematic study was conducted involving interviewing nursing and administrative staff, field observations and work analysis. Staff were interviewed regarding daily routines, how they respond to call systems and falls. Observations included 120 hours among different shifts in four long term care nursing homes in upstate

ANNOTATED BIBLIOGRAPHY ON TECHNOLOGY IN NURSING 3 New York. The challenges identified with use of these systems included difficulty identifying the source of an alarm due to lack of visual cue, inability to display more than one alarm at a time and false alarms. Using the information gathered, the authors proposed a fall prevention system that uses technology to predict falls and notify staff. Electromyography data is used to predict a patient risk for fall and then communicates findings to smart watches worn by staff. The smart watch offers a visual cue for staff, a code to indicate what kind of alarm it is and the time the alarm has been ringing. Having an auditory system accompanied by a visual notification system that is easily accessible by staff will increase response times