Evolving Technology and Informatics
When recalling the idea of myriad inputs and outputs, you may envision volumes of data in an unorganized space. Also consider that all the health data collected is potentially more than will ever be useable. How are nurse informaticists able to marshal the data in productive ways? How are nurse informaticists able to know which data to employ?
Evidence-based practice again has a role to play in the relationship between advanced technologies and nursing informatics. Each advance or new technology—and the data it produces—may add to the large amount of unmanageable data. Through the use of evidence-based practice, a nurse informaticists can begin to organize and apply this data, finding new ways to create and apply wisdom in practice. This week, you focus on new and evolving areas of information technology in order to understand how they may inform evidence-based practice. Evolving Technology and Informatics Essay Paper
Students will:
Analyze how big data, machine learning, deep learning, cognitive science, or artificial intelligence informs evidence-based practice in nursing
Analyze big data, machine learning, deep learning, cognitive science, and artificial intelligence for improved outcomes in professional nursing practice
Evolving Technology and Evidence-Based Practice
Technology is only as useful as its ability to be implemented, and complexity and usefulness are not necessarily equivalent. Consider the stethoscope, a technology without a circuit board or touchscreen, in use for centuries, and one that collects critical patient data. In contemporary times, however, technology has evolved into areas once deemed science fiction, such as artificial intelligence and machine learning. In this Discussion, you examine how these and similar technologies inform evidence-based practice in nursing.
To Prepare
Select a topic from one of the following and review the literature related to the use of the following in nursing practice.
Big data
Machine learning
Deep learning
Cognitive science
Artificial intelligence
Walden Library recommends the following:
Navigate to the Nursing Research databases (https://academicguides.waldenu.edu/az.php?s=19981) in the Walden Library.
Select a database with which to start. You can try more than one.
Perform a basic search with one of the concepts presented. Use quotation marks around a phrase like “big data.” Do not select any limiters yet.
Look at results, especially the title and subject words, to see related concepts and terms to add to your search.
Use or between related words, which means you’ll take either term. Example: machine learning or artificial intelligence
Add a second concept in Box 2 to focus your search. It helps to keep concepts separate, especially when multiple boxes are provided. Try: nursing in Box 2.
Refine your results depending on what you find. Don’t be afraid to try other words or combinations of words to get sizeable list, and then you can apply limits.
To apply limits, scroll down in the left column to limit by date (last 5 years) and limit the results to peer-reviewed scholarly journals only. It helps to do this after you know that you have performed a successful search and identified possible synonyms and sub-topics.
To retrieve the full text of individual items, click on the Find@Walden button and follow the prompts. Sometimes this step takes persistence, since there are so many different publishers supplying content to these databases.
Reflect and consider how a topic may inform evidence-based practice in nursingRequired resources.
Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data—evolution, challenges and research agenda. International Journal of Information Management, 48, 63–71.
https://www.dropbox.com/s/voze2o2fpd1lrxu/Artificial%20Intelligence%20in%20the%20era%20of%20Big%20Data%20.pdf?dl=0
McBride, S., & Tietze, M. (2016). Nursing informatics for the advanced practice nurse: Patient safety, quality, outcomes, and inter professionalism. New York, NY: Springer Publishing.
Chapter 18, “Data Management and Analytics: The Foundations for Improvement”
http://www.dropbox.com/s/f7wkhffd8kd0cqb/Ch18.pdf?dl=0Chapter 27, “‘Big Data’ and Advanced Analytics”
https://www.dropbox.com/s/qworxvrn1hdlkm8/CH26.pdf?dl=0Post a response explaining how the topic you selected informs evidence-based practice and improved outcomes in nursing. Be specific and provide examples.
BUY A PLAGIARISM-FREE PAPER HERE
Evolving Technology and Informatics
Post a response explaining how the topic you selected informs evidence-based practice and improved outcomes in nursing. Be specific and provide examples.
The selected topic is big data, which describes hard to manage, large data volumes that may be structured or unstructured and are routinely collected with each interaction. Within the context of health care, big data refers to the massive amounts of information collected in interactions between health care providers and patients or populations. It includes all the information that cannot be generated, stored and analyzed using traditional informatics systems because the information is presented in a vast scale (Bauer, 2017).
Big data has been more common within health care in the face of the popular move to digitize medical records and rapidly improve medical technologies so that larger amounts of unique information can be collected at every interaction. For instance, all the data (vitals) collected by a wearable device that alerts an individual diagnosed with diabetes to the risk of an activity causing insulin shock or a heart attack can be considered big data. Other sources of big data include information collected from healthcare testing machines (such as electrocardiograms), medical exam results, hospital records, and patient medical records. In addition, medical research also presents big data that must be properly managed and analyzed to be meaningful, such as generating population data to understand how an airborne pandemic would spread in a city so as to predict and prepare for a future pandemic (McBride & Tietze, 2016).
Big data plays a significant role in informing evidence-based practice and improving outcomes in nursing. Firstly, the collection and analysis of big data enables nurses and other medical personal to make informed decisions about medical services and treatment. For instance, nurses who have access to big data can use them to identify the warning signs that a patient is likely to have a serious illness episode before it occurs. Through treating or preventing illness at an early age, nursing care would be simpler and less costly that treating an illness once it occurs (Wicker, 2020).
Secondly, big data can be used to in data analytics to develop key performance indicators that would then be used to make resource allocation and funding decisions. For instance, it can be used to identify underserved areas or populations and create a critical health map that would inform the deployment of mobile health clinics and other resources. Big data helps to improve access to quality nursing care by streamlining administrative processes and helping nurses to make informed decisions about allocating resources and funds (McBride & Tietze, 2016).
Thirdly, big data captures a comprehensive picture of the care experience. This allows the nurse to consolidate the patient data, thereby allowing for accurate and rapid communication with patients and other providers. This is especially useful when a patient uses different providers so that analytics is able to combine data from different sources, such as integrating data from different hospital facilities (Rivas & Wac, 2018). Fourthly, big data harnesses data-driven findings to predict and solve nursing care issues earlier than would have not been possible without collecting and analyzing big data. With big data, nurses are able to leverage analytics capabilities and technologies to make sense of large data as soon as it is generated so that it is applied in nursing decisions when the data is most current and relevant (Gogia, 2019).
Finally, big data is harnessed in evidence-based practice by developing facts that improve the judgement made, and not supplement the judgement. It allows for the development of facts, numbers and analysis that draws correlations between different variables and factors. With an understanding of these relationships, and use of analytics to model the relationships, nurses are able to predict outcomes when different variables are controlled thus allowing for improved nursing outcomes to be achieved (McGonigle & Mastrian, 2018). For instance, if data analysis reveals that using face masks and hand hygiene significantly reduces risk of contracting Covid-19, then this would be considered as evidence to support standard practice to advocate for use of face masks and hand hygiene to stop the spread of Covid-19.
References
Bauer, J. (2017). Statistical Analysis for Decision Makers in Healthcare: Understanding and Evaluating Critical Information in Changing Times (2nd ed.). CRC Press.
Gogia, S. (2019). Fundamentals of Telemedicine and Telehealth. Elsevier Science.
McBride, S., & Tietze, M. (2016). Nursing informatics for the advanced practice nurse: Patient safety, quality, outcomes, and inter professionalism. Springer Publishing.
McGonigle, D., & Mastrian, K. (2018). Nursing informatics and the foundation of knowledge (4th ed.). Jones and Bartlett Learning.
Rivas, H. & Wac, K. (2018). Digital Health: Scaling Healthcare to the World. Springer International Publishing.
Wicker, Z. & Browning, B. (2020). Visualizing Health Care Statistics: A Data Mining Approach (2nd ed.). Jones & Bartlett Learning. Evolving Technology and Informatics Essay Paper