Automated Fall Detection With Quality Improvement, Article Critique Example

Automated fall detection with Quality Improvement “Rewind” to Reduce Falls in Hospital Rooms

Falls in the hospital by older adults is an increasing problem, with the advances in technology there has been a focus in developing ways to detect and prevent these from occurring. Authors Rantz, Banerjee, Cattoor, Scott, Skubic, and Popescu wrote, “Automated Fall Detection With Quality Improvement “Rewind” to Reduce Falls in Hospital Rooms”, in which provides a study in order to test Microsoft Kinect in order to test if falls are able to be not only detected but also prevented. More importantly the study was based on the implementation of the rewind privacy-protecting technique and the implementation of fall detection in six hospitals. The purpose of their study was on the basis that the increase in patients falling in the hospitals has contributed to the increase in healthcare costs for both the hospitals and the patients, but also an increase in hospital stay, resources, and injuries to the patient. The problem has become such an issues that CMS implemented reimbursement policies and regulations which limit hospital compensation for fall-related injury care. (Rantz, Banerjee, Cattoor, Skubic, Popescu, 2014)

Using Microsoft Kinect motion sensors in hospital rooms, it provided an unobtrusive, cost-efficient, and viable solution to detect and prevent falls. The technology helps in underlying what causes patients to fall, and what can be done to prevent these occurrences. The technology used was able to provide hospital step with the rewind option of seeing the events that occurred before and during the patients’ fall. This has provided staff which much needed look that hasn’t been available in the past, which contributes to the process of analyzing quality improvement. The key points that the article addresses is the use of technology in detecting if the patient potentially hit equipment or the floor, which could save on unnecessary procedures, and ruling out harm. The technology provides an unobtrusive and cost-efficient solution to hospitals.

The authors in which are qualified in the fields of nursing, education, electrical and computer engineering, and health management are qualified to conduct the study. Their research has centered on a pressing issue in the rise of health costs, extended patient stays, and an increase in hospital resources dedicated to treating patients that fall during hospitalization. The incorporation of the unobtrusive and cost-efficient method in detecting and preventing falls can contribute to the reduction in overall healthcare costs throughout the healthcare sector. Their methodology in conducting their study consisted of a descriptive pilot study over a duration of eight months in a 20-bed unit located within the MU Health Center. The Progressive Care Unit was used based on their high number of patient falls and risks for falls. Installed in six rooms, the Kinect sensors logged data continuously throughout the day. Based on their approach it provided a more valid study on the use of technology in capturing the moments before and during the events that patients fell. Unfortunately, the one-time a fall was reported it was not recorded by the technology due a power outage. While this could be seen as a disappointment, with the use of 50 stunts falls, they were able to test the feasibility of using the technology.

This study is very important because they were able to find a cost-effective solution to helping healthcare facilities save on unneeded procedures. Assessing if harm was caused to patients in the event of a fall, and overall healthcare costs. The authors provided a well-researched study that was less on medical jargon, and clearly stated that audiences from any background can comprehend. The authors have not only contributed to the healthcare sector, but also patient safety. As the information collected can be used in determining what procedures or improvements need to be made in decreasing the risks for falls in hospital rooms. Their contribution to the study of gerontology is valued, as the rising issue of patient falls, is reported mostly in older adults. Creating ways to prevent this is valuable to the field.

References

Rantz, Marily, Banerjee, Tanvi, Cattoor, Erin, Scott, Susan D., Skubic, Majorie, Popescu, Mihail. (2014). Automated fall detection with Quality Improvement “Rewind” to Reduce Falls in Hospital Rooms. Journal of Gerontological Nursing. Vol. 40, No. 1. Pg. 13-18.