Capella FlexPath MSN Class Samples:
FPX 6414
FPX 6412
FPX 6214
FPX 6021
FPX 6016
FPX 6030 Practicum
FPX 6008
FPX 6210
FPX 6103
FPX 5007
FPX 6011
FPX 6210
FPX 6004
FPX 6610
Capella 6414 Assessment 3
Assessment 3: Tool Kit for Bioinformatics
Student Name
Capella University
School of Nursing and Health Sciences, Capella University
NURS-FPX 6414 Assessment 3:
Advancing Health Care Through Data Mining
Prof. Name:
Date
Executive Summary
Assessment 3: Tool Kit for Bioinformatics
Healthcare delivery has seen significant advancements through the integration of technology, particularly in the field of bioinformatics. Bioinformatics leverages technology and data to enhance healthcare delivery and decision-making. With a focus on bioinformatics, the healthcare industry aims to improve patient care and outcomes through the implementation of policies and practices. The recent COVID-19 pandemic has profoundly impacted the world, causing acute respiratory infections. Understanding the causes of the infection is crucial for its prevention and containment. This requires extensive analysis of patient data to identify factors that contribute to the spread of the infection (Meng et al., 2020). It has been observed that patients with multiple serious diseases are more susceptible to contracting COVID-19.
Best Practice Advisory Alert (BPA) and Clinical Decision Support (CDS) have proven invaluable in promoting healthier lives for millions of people. Many healthcare settings utilize CDS in the form of BPA to send timely alerts to patients regarding their medical conditions (Baumgart, 2020). NURS-FPX 6414 Assessment 3: Tool Kit for Bioinformatics. Electronic Health Records (EHRs) enable healthcare professionals to leverage patient data and make informed decisions. BPA alerts are delivered to patients through pop-ups, providing regular reminders about their treatments. This not only benefits the patients by keeping them updated on their therapies but also helps hospitals reduce readmission rates.
References
Baumgart, D. C. (2020). Digital advantage in the COVID-19 response: perspective from Canada’s largest integrated digitalized healthcare system. Npj Digital Medicine, 3(1). https://doi.org/10.1038/s41746-020-00326-y
NURS-FPX 6414 Assessment 3: Tool Kit for Bioinformatics
Meng, L., Dong, D., Li, L., Niu, M., Bai, Y., Wang, M., Qiu, X., Zha, Y., & Tian, J. (2020). A Deep Learning Prognosis Model Helps Alert for COVID-19 Patients at High-Risk of Death: A Multi-Center Study. IEEE Journal of Biomedical and Health Informatics, 24(12), 3576–3584. https://doi.org/10.1109/JBHI.2020.3034296