Assigment .apa seven . all instructions attached.

NursingLeadershipandManagement.docx

Nursing Leadership and Management-DBX-DL01 Nora Hernandez-Pupo

Leadership in Quality Improvement

Data to support patient care comes from a variety of sources that contain differing data types. Key activities to use clinical data include identifying the sources of data, understanding the data types and associated methods to work with the data, and identifying the necessary resources to complete your IT project.

The scope of your IT project will determine the level of data access required and the associated data storage needs. Data used in multisite projects will require IRB oversight and often require the execution of a DUA if transferring data outside of the institution or receiving data from another institution.

Identifying and assembling an adequate project team is based on the needs of the project. At a minimum, you will need to include frontline staff that will use the product, a data analyst capable of completing the ETL process on the data, and potentially statisticians to conduct appropriate model building and outcomes analyses.

There are multiple approaches to analyzing data. AI is the latest advance in machine learning approaches that include supervised, in which data is labeled and the algorithm is guided with statistical considerations, and unsupervised, in which unlabeled data is used to infer meaning. While robust, machine learning approaches require interdisciplinary teams and large resource dedication to complete.

All projects require review and potential revision over time. Follow-up and review of implemented programs should be included in the initial planning stages and resource allocation decisions at project inception.

Let us consider the following for the quality improvement project:

You are a new manager on your Heart Failure/Cardiac step-down unit and have high hopes for your floor.

Identify several IT projects that you as the nurse manager of a nursing unit could develop to support the operations of the nursing floor to promote compliance with daily weights for your HF patients.

As you do your RCA analysis you realize that compliance to many of the issues causing experiences on your floor is due to the poor health data literacy within your nursing staff. Why is it important for nurse leaders to develop health data literacy?

As you begin to form your team for your IT projects you question yourself as to who will comprise the team.

Who are the various team members to consider adding to the team? Identify their roles and contributions to the project.

Important Note on the Use of AI Tools

Students may choose to use AI platforms to assist with grammar checks or writing guidance, such as Grammarly. While these tools can be helpful for improving clarity and mechanics, it is essential that all submitted work remains your own. AI-generated text should be treated as a guide, not a substitute for your original writing. Copying and pasting directly from an AI platform, even if done innocently, constitutes a violation of academic honesty.

If you would like additional support in strengthening your writing, please take advantage of the Writing Studio and the Library resources, where you can receive individualized assistance in developing your ideas, refining your grammar, and ensuring your work reflects your own academic voice. These services are designed to help you grow as a writer and succeed with integrity.

Please review the rubric prior to submitting- remember this assignment is 18% of your grade.

REFERENCES Must have DOI Numbers for me to look them up- If I am unable to verify the references points will be deducted.

Great resource to assist you: Reference List: Author/Authors - Purdue OWL® - Purdue University

This paper should be minimally 7-9 pages, but NO MORE than 9 pages, not counting references and cover page.

Submission

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Rubric Details

Maximum Score

100 points

Excellent

The paper demonstrates that the author understands and has applied concepts learned in the course. Concepts are integrated into the writer’s own insights. The writer provides concluding remarks that show analysis and synthesis of ideas.

25

Satisfactory

The paper demonstrates that the author, mostly, understands and has applied concepts learned in the course. Some conclusions, however, are not supported in the body of the paper.

20

Unsatisfactory

The paper demonstrates that the author, to a certain extent, understands and has applied concepts learned in the course

15

Unacceptable

The paper does not demonstrate that the author has understood, and applied concepts learned in the course.

10

Excellent

The topic is focused narrowly enough for the scope of this assignment. A thesis statement provides direction for the paper, either by a statement of a position or hypothesis. The topic is consistently well thought out, thorough offers insight into the topic, and includes cited evidence to support the topic.

25

Satisfactory

The topic is focused but lacks direction. The paper is about a specific topic, but the writer has not established a position. The topic is somewhat well thought out, offers limited insight into the topic, but does not include cited evidence to support the topic.

20

Unsatisfactory

The topic is too broad for the scope of this assignment.

15

Unacceptable

The topic is unclear or unrelated to the discussion topic with little or no supporting evidence.

10

Excellent

In-depth discussion and elaboration in all sections of the paper. Ties together information from all sources. Paper flows from one issue to the next with no headings. The author’s writing demonstrates an understanding of the relationship among material obtained from all sources Mostly, it ties together information from all sources. There is an introduction and a conclusion in the submission.

25

Satisfactory

In-depth discussion and elaboration in most sections of the paper. Mostly, it ties together information from all sources. Paper flows with only some disjointedness. The author’s writing demonstrates an understanding of the relationship among material obtained from all sources. There is an introduction and a conclusion in the submission.

20

Unsatisfactory

The writer has omitted content. Quotations from others outweigh the writer’s own ideas excessively. Sometimes ties together information from all sources. The paper does not flow. Disjointedness is apparent. The author’s writing does not demonstrate an understanding of the relationship between material obtained from all sources. There is an introduction and/or conclusion in the submission, but not both.

15

Unacceptable

Cursory discussion in all the sections of the paper or brief discussion in only a few sections It does not tie together information. Paper does not flow and appears to be created from disparate issues. Headings are necessary to link concepts. Writing does not demonstrate an understanding of any relationship. There is NO introduction or conclusion in the submission.

10

Excellent

5 current sources are used and are peer-review journal articles or scholarly books. Sources include both general background sources and specialized sources. Special-interest sources and popular literature and acknowledged as such if they are cited. All websites utilized are authoritative. All REFERENCES have DOI Numbers for me to look them up

7

Satisfactory

Used 4 current sources, which are peer-review journal articles or scholarly books. All websites utilized are authoritative. 4 REFERENCES have DOI Numbers for me to look them up

5.6

Unsatisfactory

Used 2 current sources which are peer-reviewed journal articles or scholarly books. All websites utilized are credible. 2-3 REFERENCES have DOI Numbers for me to look them up

4.2

Unacceptable

Fewer than 2 current sources are used which are peer-reviewed journal articles or scholarly books. Not all websites utilized are credible, and/or sources are not current. Less than 2 REFERENCES have DOI Numbers for me to look them up

2.8

Excellent

Fewer than 5 incomplete citations and/or quotations, and APA format errors. The paper is developed using APA-approved headings throughout the paper.

6

Satisfactory

More than 5 but fewer than 10 incomplete citations and/or quotations, and APA format errors. The paper is developed using and introduction APA approved heading- but no headings within the rest of the paper.

4.8

Unsatisfactory

More than 10 incomplete citations and/or quotations, or APA format errors. The paper is not developed at the graduate level APA format.

3.6

Unacceptable

The citation style is inconsistent or incorrect. It does not cite sources. The paper submitted is NOT in APA Format.

2.4

Excellent

Fewer than 5 grammatical, spelling, capitalization, or punctuation errors The required word count has been met.

12

Satisfactory

More than 5 but fewer than 10 grammatical, spelling, capitalization & punctuation errors The required word count is 25 words below the minimum required count.

9.6

Unsatisfactory

More than 10 grammatical, spelling, capitalization & punctuation errors The required word count is 50 words below the minimum required count.

7.2

Unacceptable

An unacceptable number of spelling and/or grammar mistakes. The required word count is more than 50 words below the minimum required count.

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LeadershipinQualityImprovementPaperOutline2.docx

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Leadership in Quality Improvement Paper Outline

Adelin Dupont

Florida National University

Nursing Leadership and Management

Dr. Nora Hernandez-Pupo

July 11, 2026

Leadership in Quality Improvement Paper Outline

The quality improvement concern is the variable compliance with daily weights for heart failure patients on a Cardiac/Heart Failure step-down unit. Daily weights are a critical nursing intervention since weight fluctuations may be a sign of fluid retention, worsening of heart failure, and the necessity for clinical care in a timely fashion (Heidenreich et al., 2022).

Scenario & Project Instructions

As the new nurse manager, I will be developing three information technology initiatives to increase daily weight compliance, strengthen nursing workflow, and support safe heart failure treatment. The root cause study indicates that missed daily weights could be tied to irregular processes, delayed recording, lack of real-time feedback, and poor health data literacy among nursing staff (Doll et al., 2024; Kao, 2022).

Three IT projects

· IT Project 1: EHR Daily Weight Compliance Dashboard

This initiative will leverage the electronic health record to identify heart failure patients who have submitted or are missing daily weights by a morning deadline. The dashboard will allow nurses, charge nurses and the nurse manager to discover documentation deficiencies in real time (Kao, 2022).

· IT Project 2: Automated Daily Weight Reminder and Escalation Alert

This project will generate automatic EHR reminders when a heart failure patient does not have a documented daily weight. If the weight is still missing the charge nurse will be alerted so follow-up can occur prior to the conclusion of the shift.

· IT Project 3: Smart Scale Integration With Barcode Patient Verification This project will link smart scales to the EHR with barcode patient authentication, so weights may be uploaded straight to the patient record. This can reduce errors from manual data entry and increase the accuracy of heart failure monitoring data. (Heidenreich et al., 2022; Kao, 2022).

Data Analysis & AI

· Supervised machine learning employs labeled data, such as historical records indicating completed or missing daily weights, to forecast future compliance risk. Unsupervised machine learning employs unlabeled data to identify patterns, like shifts, staffing circumstances, or workflow trends related to missed daily weights (Rony et al., 2024).

· AI necessitates interdisciplinary teams and resources, as its safe deployment relies on clinical expertise, data integrity, technological assistance, privacy safeguards, and outcome assessment. Nurse leaders, data analysts, informaticists, statisticians, frontline nurses, and IT personnel must collaborate to ensure that AI technologies are ethical, accurate, and practical (Ball Dunlap & Michalowski, 2024; Rony et al., 2024).

Health Data Literacy

· Because nursing managers need to know how data are acquired, processed and used to direct quality improvement decisions nurse leaders need to be health data literate. High levels of data literacy among leaders allow them to spot documentation gaps, comprehend dashboards, and enable staff education on the utilization of clinical data (Doll et al., 2024).

· In this project, the nurse manager will need to educate staff understand that daily weight documentation is not just a routine activity, but an important clinical data point used to guide heart failure management. Greater data literacy results in better decision-making, safer use of technology, and more substantial quality improvement outcomes (Ball Dunlap & Michalowski, 2024; Doll et al., 2024).

Data Sources & Data Types

· Data sources will include EHR flowsheets, nursing notes, physician orders, drug administration records, intake and output records, vital signs, smart scale data, staffing records and quality improvement reports. These sources will help to establish if a daily weight is missed and which process challenges lead to noncompliance (Kao, 2022).

· Data categories will include numeric data (e.g. weight values), time-stamped data (e.g. documentation times), categorical data (e.g. shift and unit assignment) and text data (e.g. nursing remarks). The resources needed will include access to EHR, smart scale technologies, data governance assistance, staff training, IT support, data analyst support, and leadership oversight (Doll et al., 2024).

Project Team Members

· The project team will consist of the nurse manager as the project leader and frontline nurses and nursing assistants as workflow specialists who execute daily weights. Charge nurses will be shift champions monitoring compliance and supporting real time follow-up.

· A nurse informaticist will support design of EHR dashboard, alerts, and workflow integration. A data analyst will conduct the clinical data extraction, transformation, and loading process. A statistician will help in model creation, data analysis, and outcomes analysis (Ball Dunlap & Michalowski, 2024).

· Other team members include an IT professional, who helps with system integration; a quality improvement specialist, who helps evaluate processes; a heart failure provider or APRN, who provides clinical assistance; and a patient or family adviser, who helps ensure patient-centered planning. Clinical, operational, technological, and ethical competence is required for technology projects, making interdisciplinary collaboration necessary (Rony et al., 2024).

Follow-Up & Sustainability

· Follow-up will be initiated during the planning phase and will continue after implementation. During initial implementation, the nurse manager will assess compliance with daily weights weekly, and then monthly if the process is stabilized.

· Audit-and-feedback reports, staff education, charge nurse follow-up, dashboard review during huddles, and Plan-Do-Study-Act cycles will enhance sustainability. If alarms become too frequent or documentation is still lacking or workflow impediments still exist that impact daily weight compliance, the projects will be updated over time.

Conclusion

This quality improvement framework emphasizes the utilization of nurse leadership, health data literacy, electronic health record tools, smart scale integration, and interdisciplinary collaboration to enhance daily weight compliance among heart failure patients. The final study will elucidate how these IT projects might enhance nurse operations, augment documentation precision, and facilitate safer heart failure management.

References

Ball Dunlap, P. A., & Michalowski, M. (2024). Advancing AI Data Ethics in Nursing: Future Directions for Nursing Practice, Research, and Education. JMIR nursing, 7, e62678. https://doi.org/10.2196/62678

Doll, J., Anzalone, A. J., Clarke, M., Cooper, K., Polich, A., & Siedlik, J. (2024). A Call for a Health Data-Informed Workforce Among Clinicians. JMIR medical education, 10, e52290. https://doi.org/10.2196/52290

Heidenreich, P. A., Bozkurt, B., Aguilar, D., Allen, L. A., Byun, J. J., Colvin, M. M., Deswal, A., Drazner, M. H., Dunlay, S. M., Evers, L. R., Fang, J. C., Fedson, S. E., Fonarow, G. C., Hayek, S. S., Hernandez, A. F., Khazanie, P., Kittleson, M. M., Lee, C. S., Link, M. S., Milano, C. A., … WRITING COMMITTEE MEMBERS (2022). 2022 American College of Cardiology/American Heart Association/Heart Failure Society of America Guideline for the Management of Heart Failure: Executive Summary. Journal of cardiac failure, 28(5), 810–830. https://doi.org/10.1016/j.cardfail.2022.02.009

Kao D. P. (2022). Electronic Health Records and Heart Failure. Heart failure clinics, 18(2), 201–211. https://doi.org/10.1016/j.hfc.2021.12.004

Rony, M. K. K., Parvin, M. R., & Ferdousi, S. (2024). Advancing nursing practice with artificial intelligence: Enhancing preparedness for the future. Nursing Open, 11(1), e2070. https://doi.org/10.1002/nop2.2070