for NURS-FPX4040 Assessment 3: Evidence-Based Proposal and Annotated Bibliography on Technology in Nursing Advances in technology and technological applications have revolutionized operations in various fields, healthcare included.

The healthcare sector, in particular, has, over the years, experienced incredible growth in the use of various technology and technological applications. Among such technologies are patient monitoring devices. Patient monitoring devices have been used in various aspects of patient care to give care to patients with various illnesses or those who are at risk of particular conditions. An example of patient monitoring devices is the fall detection systems which are used in monitoring patient groups such as elderly persons to prevent their fall (Wang et al., 2020). Therefore, the purpose of this assignment is to create an annotated bibliography regarding the use of fall detection systems as patient monitoring devices Rational For Technology Topic and Research Process Patients need to be safe in the care environment. However, events such as patient falls can lead to adverse outcomes such as bone fractures, broken body parts, and even death. In addition, patient falls also lead to increased spending and prolonged stay in hospitals which lead to hospital-acquired infections (Wang et al., 2020). Therefore, this is a topic of interest; hence, it was chosen to further explore the development in the use of monitoring devices to control the rates of patient falls. A research process was conducted to obtain relevant articles that show the use of these devices and their importance in controlling patient falls. The article databases used include Google Scholar, the Cochrane Database of Systematic Reviews, Ovid, the Cochrane Central Register of Controlled Trials, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Medline. The keywords used include patient falls, fall detection systems, sensors, and patient monitoring systems. Annotated Bibliography Hashim, H. A., Mohammed, S. L., & Gharghan, S. K. (2020). Accurate fall detection for patients with Parkinson’s disease based on a data event algorithm and wireless sensor nodes. Measurement, 156, 107573. https://doi.org/10.1016/j.measurement.2020.107573 This research was conducted to determine the accuracy of the fall detectors for patients with Parkinson’s disease using wireless sensor nodes. Therefore, the research aimed at designing and implementing a wearable fall-detection system based on the wireless sensor network (Hashim et al.,2020). The system accurately detected patient’s falls based on the data event algorithms. Analysis of the data showed that the fall detection system achieved 100% specificity, sensitivity, and accuracy in patient fall detection. This technology is relevant to nursing practice and the work of interdisciplinary teams since it improves nurse efficiency in improving patient outcomes. Interdisciplinary teams can also collaborate to analyze patient data and make efforts to stop falls. This publication was chosen because it directly addresses fall detection and high accuracy. The nurse informaticist can play a critical role in collaboration with other nurses and physicians to improve outcomes. Ajerla, D., Mahfuz, S., & Zulkernine, F. (2019). A real-time patient monitoring framework for fall detection. Wireless Communications and Mobile Computing, 2019, 1-13.https://doi.org/10.1155/2019/9507938 This article by Ajerla et al. (2019) focuses on a real monitoring framework to detect patient falls. Therefore, the purpose of this research was to formulate a fall detection system that applies computing approaches using wearable devices that send data for real analysis to detect falls. The analysis of the data showed that the patient monitoring device had a positive impact on patient outcomes as it was able to detect patient falls with 99% accuracy. Therefore, the technology used also greatly improved patient safety as fall detection leads to the prevention of patient falls. This technology is also relevant to nursing since nurses can use the described fall detection system to help reduce fall incidences among patients. The work of the interdisciplinary care team can also be positively impacted since they can collaborate to use the system to monitor patient falls and take appropriate measures to prevent such fall incidences. This article was also selected since it addresses the technology of interest, which is a fall detection system. In addition, it is also interesting since the researchers used relatively cheaper materials to make the fall detection system. Saadeh, W., Butt, S. A., & Altaf, M. A. B. (2019). A patient-specific single-sensor IoT-based wearable fall prediction and detection system. IEEE Transactions On Neural Systems and Rehabilitation Engineering, 27(5), 995-1003. https://doi.org/10.1109/TNSRE.2019.2911602 This article by Saadeh et al.(2019), mainly focused on sensor Internet of Things-based wearable fall prediction and detection systems. Therefore, the authors aimed to explore the efficacy of the system in detecting patient falls and controlling or reducing the rates of falls. The analysi