Assignment: The Impact of Standardized Nursing Terminology
Assignment: The Impact of Standardized Nursing Terminology
Among the Resources in this module is the Rutherford (2008) article Standardized Nursing Language: What Does It Mean for Nursing Practice? In this article, the author recounts a visit to a local hospital to view the recent implementation of a new coding system.
During the visit, one of the nurses commented to her, “We document our care using standardized nursing languages but we don’t fully understand why we do” (Rutherford, 2008, para. 1).
How would you respond to a comment such as this one?
CLICK HERE TO ORDER
To Prepare:
Review the concepts of informatics as presented in the Resources, particularly Rutherford, M. (2008) Standardized Nursing Language: What Does It Mean for Nursing Practice?
Reflect on the role of a nurse leader as a knowledge worker.
Consider how knowledge may be informed by data that is collected/accessed.
The Assignment:
In a 2- to 3-page paper, address the following:
Nurs 6051
Assignment due by 3-28
To Prepare:
Review the concepts of informatics as presented in the Resources, particularly Rutherford, M. (2008) Standardized Nursing Language: What Does It Mean for Nursing Practice?
Reflect on the role of a nurse leader as a knowledge worker.
Consider how knowledge may be informed by data that is collected/accessed.
The Assignment:
In a 2- to 3-page paper, address the following:
Explain how you would inform this nurse (and others) of the importance of standardized nursing terminologies.
Describe the benefits and challenges of implementing standardized nursing terminologies in nursing practice. Be specific and provide examples.
Be sure to support your paper with peer-reviewed research on standardized nursing terminologies that you consulted from the Walden Library
Objective : https://doi.org/10.1093/jamia/ocz150
This study focuses on the task of automatically assigning standardized (topical) subject headings to free-text sentences in clinical nursing notes. The underlying motivation is to support nurses when they document patient care by developing a computer system that can assist in incorporating suitable subject headings that reflect the documented topics. Central in this study is performance evaluation of several text classification methods to assess the feasibility of developing such a system.
Seven text classification methods are evaluated using a corpus of approximately 0.5 million nursing notes (5.5 million sentences) with 676 unique headings extracted from a Finnish university hospital. Several of these methods are based on artificial neural networks. Evaluation is first done in an automatic manner for all methods, then a manual error analysis is done on a sample.
We find that a method based on a bidirectional long short-term memory network performs best with an average recall of 0.5435 when allowed to suggest 1 subject heading per sentence and 0.8954 when allowed to suggest 10 subject headings per sentence. However, other methods achieve comparable results. The manual analysis indicates that the predictions are better than what the automatic evaluation suggests.