Discussion: The Application of Data to Problem-Solving

In the modern era, there are few professions that do not to some extent rely on data. Stockbrokers rely on market data to advise clients on financial matters. Meteorologists rely on weather data to forecast weather conditions, while realtors rely on data to advise on the purchase and sale of property. In these and other cases, data not only helps solve problems, but adds to the practitioner’s and the discipline’s body of knowledge.

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Of course, the nursing profession also relies heavily on data. The field of nursing informatics aims to make sure nurses have access to the appropriate date to solve healthcare problems, make decisions in the interest of patients, and add to knowledge.

In this Discussion, you will consider a scenario that would benefit from access to data and how such access could facilitate both problem-solving and knowledge formation.

To Prepare:

Reflect on the concepts of informatics and knowledge work as presented in the Resources.

Consider a hypothetical scenario based on your own healthcare practice or organization that would require or benefit from the access/collection and application of data. Your scenario may involve a patient, staff, or management problem or gap.

Post a description of the focus of your scenario. Describe the data that could be used and how the data might be collected and accessed. What knowledge might be derived from that data? How would a nurse leader use clinical reasoning and judgment in the formation of knowledge from this experience? Discussion: The Application of Data to Problem-Solving

Learning Resources

Note: To access this week’s required library resources, please click on the link to the Course Readings List, found in the Course Materials section of your Syllabus.

Required Readings

McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.

Chapter 1, “Nursing Science and the Foundation of Knowledge” (pp. 7–19)

Chapter 2, “Introduction to Information, Information Science, and Information Systems” (pp. 21–33)

Chapter 3, “Computer Science and the Foundation of Knowledge Model” (pp. 35–62)

24Slides. (2018). How to make an infographic in PowerPoint. Retrieved September 27, 2018, from https://24slides.com/presentbetter/how-make-infographic-powerpoint/

Nagle, L., Sermeus, W., & Junger, A. (2017). Evolving role of the nursing informatics specialist. In J. Murphy, W. Goossen, & P. Weber (Eds.), Forecasting Competencies for Nurses in the Future of Connected Health (212–221). Clifton, VA: IMIA and IOS Press. Retrieved from https://serval.unil.ch/resource/serval:BIB_4A0FEA56B8CB.P001/REF

Sweeney, J. (2017). Healthcare informatics. Online Journal of Nursing Informatics, 21(1).

Note: You will access this article from the Walden Library databases.

In the video Health Informatics and Population Health: Trends in Population Health, contributors discuss how current and future generations of patients are more knowledgeable, and more involved in their healthcare than in past generations. The internet and advances in artificial intelligence make access to databases with information on health diagnostics, personal lab results, and treatment options readily available (2018). Nurses need to make use of these advances in technology, a database that gives real-life tips and suggestions on hands-on patient care would be invaluable for bedside nurses. Nurses are taught basic nursing skills in school, but only through personal experience and dissemination of knowledge from other nurses do they acquire additional skills needed to care for patients in real life. This database would include suggestions for patient care that would consist of tips on tasks such as inserting a Foley catheter on an obese female patient, how to assist a trauma patient onto a bedpan, the best way to remove adhesive from a patient with impaired skin integrity. Nurses are smart and have unlimited ingenuity, and this database would include nurses’ contributions from all over the world. The data bank would serve to develop knowledge formation of different techniques and skills and assist in problem-solving when a nurse is presented with a skills dilemma. Nurse leaders should use this database to promote a better quality of patient care and to help other nurses by disseminating knowledge they have acquired throughout their careers. Database developers should seek the input of experienced nurse leaders, relying on their sound clinical judgment to determine the safety and accuracy of the information and techniques shared in the database. With this data base, nurses could take a virtual team approach to problem-solving involving patient treatment and care. In the article Evolving Role of the Nursing Informatics Specialist, the authors think that in the future, “Teams will work across boundaries of organizations and will be organized around a particular patient” (Nagle, Sermeus, & Junger, 2017, p. 215). This type of database can be maintained and accessed via the internet or cloud, “cloud storage is data storage provided by networked online servers that are typically outside of the institution whose data are being housed”(McGonigle & Mastrian, Chapter 3). I believe a hybrid of public and private cloud would be the best way to generate collaboration and inclusiveness while protecting the integrity of the data collected and disseminated.

References

Laureate Education (Producer). (2018). Health Informatics and Population Health: Trends in

Population Health [Video file]. Baltimore, MD: Author.

McGonigle, D., & Mastrian, K. G. (). Nursing informatics and the foundation of knowledge (4th ed.). [Ereader]. Retrieved from https://ereader.chegg.com/#/books/9781284142990/cfi/6/20!/4@0.00:0

Nagle, L. M., Sermeus, W., & Junger, A. (2017). Evolving role of the nursing informatics specialist. Forecasting Informatics Competencies for Nurses in the Future of Connected Health, 212-221. http://dx.doi.org/10.3233/978-1-61499-738-2-212

RE: Discussion – Week 1

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Response to Terra Plank

Technology will continue to transform the way nursing care is delivered. ICU units often have automated deterioration detection using electronic medical record data (EMR), which can reduce the risk of failure to rescue. Automated deterioration detection using EMR data is a crucial aid in caring for patients in the ICU, but variable EMR detection approaches and performance can limit its usefulness. You talked about how the patient’s data from the monitors flows into their EMR, where the data collected uses algorithms to create warnings such as sepsis. According to Despins (2018), algorithms to detect the occurrence of severe sepsis or septic shock incorporate a combination of data points, which can include information from microbiology culture orders, vital signs, laboratory values, and the presence of vasopressors such as norepinephrine infusions (p.326 ).

Sepsis is a difficult condition to define and diagnose that requires time-sensitive therapies to prevent mortality and morbidity. One in four persons with sepsis will die. Early detection of sepsis leads to appropriate treatments and better outcomes. Critical care nurses work in complex, highly interruptive environments that require dual tasking, and most ICU nurses can accelerate the filtering and sense-making needed to respond to the multiple stimuli in an ICU. Unfortunately, the amount of task switching necessary to accomplish this level of response can lead to fatigue, and eventually, desensitization toward alarms occurs. According to Rincon, Manos, & Pierce (2017), “recent studies in ICUs indicate that biomedical devices can produce as many as one critical alert every 92 seconds with fewer than 15% being clinically relevant” (p. 460). You said you got a sepsis warning on your patient. How does your system alert you for a sepsis warning? Is it by a sound and visual display in the EMR?

References

Despins, L. (2018). Automated Deterioration Detection Using Electronic Medical Record Data in Intensive Care Unit Patients: A Systematic Review. CIN: Computers, Informatics, Nursing, 36(7), 323-330.

Rincon, T. A., Manos, E. L., & Pierce, J. D. (2017). Telehealth Intensive Care Unit Nurse Surveillance of Sepsis. CIN: Computers, Informatics, Nursing, 35(9), 459-464.

Name: NURS_5051_Module01_Week01_Discussion_Rubric
Grid View
List View
Excellent Good Fair Poor
Main Posting
45 (45%) – 50 (50%)
Answers all parts of the discussion question(s) expectations with reflective critical analysis and synthesis of knowledge gained from the course readings for the module and current credible sources.

Supported by at least three current, credible sources.

Written clearly and concisely with no grammatical or spelling errors and fully adheres to current APA manual writing rules and style.
40 (40%) – 44 (44%)
Responds to the discussion question(s) and is reflective with critical analysis and synthesis of knowledge gained from the course readings for the module.

At least 75% of post has exceptional depth and breadth.

Supported by at least three credible sources.

Written clearly and concisely with one or no grammatical or spelling errors and fully adheres to current APA manual writing rules and style.
35 (35%) – 39 (39%)
Responds to some of the discussion question(s).

One or two criteria are not addressed or are superficially addressed.

Is somewhat lacking reflection and critical analysis and synthesis.

Somewhat represents knowledge gained from the course readings for the module.

Post is cited with two credible sources.

Written somewhat concisely; may contain more than two spelling or grammatical errors.

Contains some APA formatting errors.
0 (0%) – 34 (34%)
Does not respond to the discussion question(s) adequately.

Lacks depth or superficially addresses criteria.

Lacks reflection and critical analysis and synthesis.

Does not represent knowledge gained from the course readings for the module.

Contains only one or no credible sources.

Not written clearly or concisely.

Contains more than two spelling or grammatical errors.

Does not adhere to current APA manual writing rules and style.
Main Post: Timeliness
10 (10%) – 10 (10%)
Posts main post by day 3.
0 (0%) – 0 (0%)
0 (0%) – 0 (0%)
0 (0%) – 0 (0%)
Does not post by day 3.
First Response
17 (17%) – 18 (18%)
Response exhibits synthesis, critical thinking, and application to practice settings.

Responds fully to questions posed by faculty.

Provides clear, concise opinions and ideas that are supported by at least two scholarly sources.

Demonstrates synthesis and understanding of learning objectives.

is professional and respectful to colleagues.

Responses to faculty questions are fully answered, if posed.

Response is effectively written in standard, edited English.
15 (15%) – 16 (16%)
Response exhibits critical thinking and application to practice settings.

is professional and respectful to colleagues.

Responses to faculty questions are answered, if posed.

Provides clear, concise opinions and ideas that are supported by two or more credible sources.

Response is effectively written in standard, edited English.
13 (13%) – 14 (14%)
Response is on topic and may have some depth.

Responses posted in the discussion may lack effective professional communication.

Responses to faculty questions are somewhat answered, if posed.

Response may lack clear, concise opinions and ideas, and a few or no credible sources are cited.
0 (0%) – 12 (12%)
Response may not be on topic and lacks depth.

Responses posted in the discussion lack effective professional communication.

Responses to faculty questions are missing.

No credible sources are cited.
Second Response
16 (16%) – 17 (17%)
Response exhibits synthesis, critical thinking, and application to practice settings.

Responds fully to questions posed by faculty.

Provides clear, concise opinions and ideas that are supported by at least two scholarly sources.

Demonstrates synthesis and understanding of learning objectives.

is professional and respectful to colleagues.

Responses to faculty questions are fully answered, if posed.

Response is effectively written in standard, edited English.
14 (14%) – 15 (15%)
Response exhibits critical thinking and application to practice settings.

is professional and respectful to colleagues.

Responses to faculty questions are answered, if posed.

Provides clear, concise opinions and ideas that are supported by two or more credible sources.

Response is effectively written in standard, edited English.
12 (12%) – 13 (13%)
Response is on topic and may have some depth.

Responses posted in the discussion may lack effective professional communication.

Responses to faculty questions are somewhat answered, if posed.

Response may lack clear, concise opinions and ideas, and a few or no credible sources are cited.
0 (0%) – 11 (11%)
Response may not be on topic and lacks depth.

Responses posted in the discussion lack effective professional communication.

Responses to faculty questions are missing.

No credible sources are cited.
Participation
5 (5%) – 5 (5%)
Meets requirements for participation by posting on three different days.
0 (0%) – 0 (0%)
0 (0%) – 0 (0%)
0 (0%) – 0 (0%)
Does not meet requirements for participation by posting on 3 different days.
Total Points: 100
Name: NURS_5051_Module01_Week01_Discussion_Rubric

Discussion: The Application of Data to Problem-Solving