NURS-FPX4040 Assessment 3: Evidence-Based Proposal and Annotated Bibliography on Technology in Nursing
Capella University NURS-FPX4040 Assessment 3: Evidence-Based Proposal and Annotated Bibliography on Technology in Nursing-Step-By-Step Guide
This guide will demonstrate how to complete the Capella University NURS-FPX4040 Assessment 3: Evidence-Based Proposal and Annotated Bibliography on Technology in Nursing assignment based on general principles of academic writing. Here, we will show you the A, B, Cs of completing an academic paper, irrespective of the instructions. After guiding you through what to do, the guide will leave one or two sample essays at the end to highlight the various sections discussed below.
How to Research and Prepare for NURS-FPX4040 Assessment 3: Evidence-Based Proposal and Annotated Bibliography on Technology in Nursing
Whether one passes or fails an academic assignment such as the Capella University NURS-FPX4040 Assessment 3: Evidence-Based Proposal and Annotated Bibliography on Technology in Nursing depends on the preparation done beforehand. The first thing to do once you receive an assignment is to quickly skim through the requirements. Once that is done, start going through the instructions one by one to clearly understand what the instructor wants. The most important thing here is to understand the required format—whether it is APA, MLA, Chicago, etc.
After understanding the requirements of the paper, the next phase is to gather relevant materials. The first place to start the research process is the weekly resources. Go through the resources provided in the instructions to determine which ones fit the assignment. After reviewing the provided resources, use the university library to search for additional resources. After gathering sufficient and necessary resources, you are now ready to start drafting your paper.
How to Write the Introduction for NURS-FPX4040 Assessment 3: Evidence-Based Proposal and Annotated Bibliography on Technology in Nursing
The introduction for the Capella University NURS-FPX4040 Assessment 3: Evidence-Based Proposal and Annotated Bibliography on Technology in Nursing is where you tell the instructor what your paper will encompass. In three to four statements, highlight the important points that will form the basis of your paper. Here, you can include statistics to show the importance of the topic you will be discussing. At the end of the introduction, write a clear purpose statement outlining what exactly will be contained in the paper. This statement will start with “The purpose of this paper…” and then proceed to outline the various sections of the instructions.
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How to Write the Body for NURS-FPX4040 Assessment 3: Evidence-Based Proposal and Annotated Bibliography on Technology in Nursing
After the introduction, move into the main part of the NURS-FPX4040 Assessment 3: Evidence-Based Proposal and Annotated Bibliography on Technology in Nursing assignment, which is the body. Given that the paper you will be writing is not experimental, the way you organize the headings and subheadings of your paper is critically important. In some cases, you might have to use more subheadings to properly organize the assignment. The organization will depend on the rubric provided. Carefully examine the rubric, as it will contain all the detailed requirements of the assignment. Sometimes, the rubric will have information that the normal instructions lack.
Another important factor to consider at this point is how to do citations. In-text citations are fundamental as they support the arguments and points you make in the paper. At this point, the resources gathered at the beginning will come in handy. Integrating the ideas of the authors with your own will ensure that you produce a comprehensive paper. Also, follow the given citation format. In most cases, APA 7 is the preferred format for nursing assignments.
How to Write the Conclusion for NURS-FPX4040 Assessment 3: Evidence-Based Proposal and Annotated Bibliography on Technology in Nursing
After completing the main sections, write the conclusion of your paper. The conclusion is a summary of the main points you made in your paper. However, you need to rewrite the points and not simply copy and paste them. By restating the points from each subheading, you will provide a nuanced overview of the assignment to the reader.
How to Format the References List for NURS-FPX4040 Assessment 3: Evidence-Based Proposal and Annotated Bibliography on Technology in Nursing
The very last part of your paper involves listing the sources used in your paper. These sources should be listed in alphabetical order and double-spaced. Additionally, use a hanging indent for each source that appears in this list. Lastly, only the sources cited within the body of the paper should appear here.
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Sample Answer 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 analysis of the experimental data showed that the fall detection and prediction system had a significant impact on patient safety. The researchers noted that the system could detect patient falls by over 99% accuracy. In addition, the system also achieved sensitivity and specificity of 97.8% and 99.1%, respectively, in the fast model. Therefore, the system could efficiently and accurately detect patient falls and help prevent falls, improving patient safety. According to this source, this technology is also relevant to nursing practice since it enhances the care of preventing falls through earlier detection and prediction, which then prompts the nurses to act fast and prevent potential patient falls that could have resulted in an adverse event. It also impacts the work of interdisciplinary healthcare teams as such a team can effectively use the system to improve patient outcomes related to patient falls.
Espinosa, R., Ponce, H., Gutiérrez, S., Martínez-Villaseñor, L., Brieva, J., & Moya-Albor, E. (2019). A vision-based approach for fall detection using multiple cameras and convolutional neural networks: A case study using the UP-Fall detection dataset. Computers In Biology and Medicine, 115, 103520. https://doi.org/10.1016/j.compbiomed.2019.103520
This is another source that addresses the use of fall detection systems to detect potential patient falls and trigger actions to prevent such events. Therefore, these researchers explored the use of a vision-based approach for fall detection. The researchers used several cameras and convolutional neural networks to help detect potential patient falls. The system analyzes images in fixed time windows and extracts features through the use of the optical flow method (Espinosa et al.,2019). The analysis of the data also showed that this technology had an impact on patient care and patient safety. For example, the researcher realized that their multi-vision approach was able to detect human falls and achieve an accuracy of 96%. This shows that the technology was accurate and efficient, hence increasing the possibility of detecting, controlling, and preventing patient falls. According to these sources, this technology is also relevant to nursing practice since it is a technology that can be applied by nurses in the patient care environment to improve patient safety by preventing patient falls. The technology also has an impact on the work of interdisciplinary healthcare teams since a team caring for patients such as older patients can collaborate to use this system and reduce rates of patient falls. This publication was also selected since it showed a high accuracy of the technology in detecting patient falls, which is also key in attempts to reduce patient fall rates.
Summary and Recommendations
The four selected articles were carefully chosen since they adequately address fall monitoring systems as part of patient monitoring systems. Therefore, various key learnings were obtained from the four publications. For example, the use of fall detection systems can greatly reduce fall incidences and improve patient outcomes. Besides, the efficacy of these systems in detecting patient falls largely depends on their accuracy and specificity. Various organizational factors also influence the selection of a technology in healthcare. One of them is organizational policy. Organizations having policies that focus on patient safety and a better patient environment will embrace healthcare technologies that eliminate potential hazards, such as those that can lead to falls or medication errors.
The implementation of a fall detection system in healthcare settings can greatly improve patient outcomes. For example, they can be used to help reduce fall incidences among elderly and frail patients since they are more prone to falls(Hashim et al.,2020). The fall detection system can help detect falls, which allows nurses to act swiftly and prevent falls that could otherwise have led to adverse events. This technology should, therefore, be implemented in the setting since it improves the efficiency of the organization in caring for this population. It also leads to improved outcomes since falls are prevented, hence protecting patients from injuries that could have led to broken body parts, prolonged hospital stays, higher healthcare spending, and litigations. It can also improve the productivity of interdisciplinary teams and improve their satisfaction, hence higher rates of staff retention.
Conclusion
This write-up has explored fall detection systems as a type of patient monitoring system. Four articles have been annotated, and they show the efficacy of these systems in detecting patient falls. In addition, these systems can improve patient safety satisfaction and also enhance the efficiency of an interdisciplinary team.
References
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
Espinosa, R., Ponce, H., Gutiérrez, S., Martínez-Villaseñor, L., Brieva, J., & Moya-Albor, E. (2019). A vision-based approach for fall detection using multiple cameras and convolutional neural networks: A case study using the UP-Fall detection dataset. Computers In Biology and Medicine, 115, 103520. https://doi.org/10.1016/j.compbiomed.2019.103520
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
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
Wang, X., Ellul, J., & Azzopardi, G. (2020). Elderly fall detection systems: A literature survey. Frontiers in Robotics and AI, 7, 71. https://doi.org/10.3389/frobt.2020.00071
Sample Answer 2 for NURS-FPX4040 Assessment 3: Evidence-Based Proposal and Annotated Bibliography on Technology in Nursing
Healthcare technologies have significantly transformed healthcare delivery in the modern world. Health organizations use technologies to improve care safety, quality, and efficiency. Real-time location is a technology used in healthcare to track and manage staff, and medical equipment in healthcare environments. Health organizations use real-time location technology to enhance efficiency, theft, or property loss. The monitoring also safeguards patient safety in healthcare organizations. Real-time location technology has been selected for this essay because it is a new healthcare technology. Health organizations are yet to explore its potential in driving safety, efficiency, and excellence in service delivery. Articles for the annotated bibliography were obtained from databases, including EMBASE, CINAHL, and PubMed. Search terms were utilized for article acquisition. They include real-time location technology, real-time location technology in health, and the impacts of real-time location technology. Articles published over the last five years were included.
Annotated Bibliography
Budak, A., Kaya, İ., Karaşan, A., & Erdoğan, M. (2020). Real-time location systems selection by using a fuzzy MCDM approach: An application in humanitarian relief logistics. Applied Soft Computing, 92, 106322. https://doi.org/10.1016/j.asoc.2020.106322
The above study investigated the usage of real-time location technologies and their population increase. It examined performance criteria and evaluated the technologies. Using a combined fuzzy-based decision-making approach, the authors selected the most appropriate real-time location technologies. The study revealed that real-time location technology could be applied to humanitarian relief logistics warehouses to monitor relief activities. Alternatives including ultra-wideband, UHF FRID, Wi-Fi, and Active FRID were considered for real-time location technology. The results revealed that real-time location technology could enhance efficiency in humanitarian warehouses. The benefits can be translated into other environments, including healthcare. The study shows that real-time location technology can be used in nursing to enhance human resources management efficiency and minimize care safety events. This resource was selected because it provides a range of real-time location technology uses in healthcare. It also expands on the existing technologies used for real-time monitoring and evaluation.
Poongodi, M., Sharma, A., Hamdi, M., Maode, M., & Chilamkurti, N. (2021). Smart healthcare in smart cities: Wireless patient monitoring system using IoT. The Journal of Supercomputing, 77(11), 12230–12255. https://doi.org/10.1007/s11227-021-03765-w
The above study investigates the use of smart healthcare systems to improve patient outcomes. Specifically, the researchers examined the use of smart navigation systems for ambulances. They discovered that too much time is wasted between information facilitation and patient transfer for specialized treatments in healthcare facilities. As a result, the authors developed a patient monitoring and ambulance tracking system to make timely diagnosis and referral decisions in healthcare. The system uses monitors and transmits breath rate, temperature, and heartbeat to healthcare providers before ambulance deployment. Patients can also request an ambulance instantly without calling the hospital for ambulance deployment. Patients can also track ambulance locations and get instant navigation to the nearest facilities for effective disease management. The article shows the relevance of smart healthcare systems. They can facilitate timely decision-making, patient transfers, and elimination of adverse events in disease management. This article was selected because it provides novel approaches to using smart healthcare technologies to improve patient outcomes. Healthcare providers also learn about other technologies that can be incorporated into smart technologies to improve care outcomes.
Price, J. R., Mookerjee, S., Dyakova, E., Myall, A., Leung, W., Weiße, A. Y., Shersing, Y., Brannigan, E. T., Galletly, T., Muir, D., Randell, P., Davies, F., Bolt, F., Barahona, M., Otter, J. A., & Holmes, A. H. (2021). Development and Delivery of a Real-time Hospital-onset COVID-19 Surveillance System Using Network Analysis. Clinical Infectious Diseases, 72(1), 82–89. https://doi.org/10.1093/cid/ciaa892
The above study investigated the design and implementation of a hospital-onset COVID-19 infection (HOCI) surveillance system. The system was adopted for an acute healthcare setting to target prevention interventions. The HOCI incorporated elements of a real-time location system to guide disease detection and prevention interventions. The study was conducted in a large teaching hospital in London, United Kingdom. The researchers utilized patients who tested positive for COVID-19 between 4 March and 14 April 2020. The researchers used electronic healthcare systems to collect data and develop a novel surveillance system for detecting and reporting HOCI incidents. The results revealed that the real-time surveillance system detected COVID-19 changing rates and informed decisions made to prevent disease spread and manage cases. The article shows that HOCI technology is important to nursing and healthcare in facilitating disease monitoring, evaluation, and implementation of change interventions. Healthcare providers can use the article to develop innovative systems for timely disease surveillance and management.
Dwivedi, R., Mehrotra, D., & Chandra, S. (2022). Potential of Internet of Medical Things (IoMT) applications in building a smart healthcare system: A systematic review. Journal of Oral Biology and Craniofacial Research, 12(2), 302–318. https://doi.org/10.1016/j.jobcr.2021.11.010
The above study is a systematic review that identified the role of Internet of Medical Things applications in improving the healthcare system. The article also analyzed previous studies demonstrating the effectiveness of the Internet of Medical Things to the patient and healthcare teams. Additionally, the researchers explore technologies that supplement the Internet of Medical Things and the challenges encountered in developing a smart healthcare system. The results of this study revealed that the Internet of Medical Things has resolved difficulties associated with remote monitoring, robotics, telemedicine, and sensors. It also revealed challenges linked to the Internet of Medical Things adoption, including data privacy and security, data management, upgradation, and scalability of the adopted systems. The article demonstrates the relevance of the Internet of Medical Things, including real-time location technology. The technology improves efficiency, quality, and safety in healthcare systems. This article was selected because it explores the potential of the Internet of Things and its associated technologies, including real-time location technology. The article also identifies challenges organizations experience when adopting new technologies to enhance service delivery.
Summary of Recommendation
The reviewed articles support the need for real-time location technology in healthcare. The findings show that real-time location technology facilitates efficiency in healthcare. The technology also enables timely decision-making. This can be seen in wireless transmission of patient data to healthcare providers for patient-centered care. Health organizations can also use real-time location technology to automate processes such as resource deployment in times of need. The articles also show that real-time location technology helps manage challenges associated with other technologies in health, including telehealth and sensor technologies. The articles identified challenges linked with real-time location technology and the use of the Internet of Things. They include data privacy and confidentiality issues, data security, systems scalability and upgradation, and management of large amounts of data. Despite the challenges, the benefits associated with real-time location technology such as efficiency, safety, and quality of patient care should guide organizational decisions. The technology can improve patient safety and quality of care by facilitating remote patient monitoring. Organizations can also achieve efficient resource management, translating into improved performance. Therefore, healthcare organizations should prioritize real-time location technology to improve outcomes.
References
Budak, A., Kaya, İ., Karaşan, A., & Erdoğan, M. (2020). Real-time location systems selection by using a fuzzy MCDM approach: An application in humanitarian relief logistics. Applied Soft Computing, 92, 106322. https://doi.org/10.1016/j.asoc.2020.106322
Dwivedi, R., Mehrotra, D., & Chandra, S. (2022). Potential of Internet of Medical Things (IoMT) applications in building a smart healthcare system: A systematic review. Journal of Oral Biology and Craniofacial Research, 12(2), 302–318. https://doi.org/10.1016/j.jobcr.2021.11.010
Poongodi, M., Sharma, A., Hamdi, M., Maode, M., & Chilamkurti, N. (2021). Smart healthcare in smart cities: Wireless patient monitoring system using IoT. The Journal of Supercomputing, 77(11), 12230–12255. https://doi.org/10.1007/s11227-021-03765-w
Price, J. R., Mookerjee, S., Dyakova, E., Myall, A., Leung, W., Weiße, A. Y., Shersing, Y., Brannigan, E. T., Galletly, T., Muir, D., Randell, P., Davies, F., Bolt, F., Barahona, M., Otter, J. A., & Holmes, A. H. (2021). Development and Delivery of a Real-time Hospital-onset COVID-19 Surveillance System Using Network Analysis. Clinical Infectious Diseases, 72(1), 82–89. https://doi.org/10.1093/cid/ciaa892