NURS FPX 4045 Assessment 1 Nursing Informatics in Health Care

Student Name

Capella University

NURS-FPX4045 Nursing Informatics: Managing Health Information and Technology

Prof. Name

Date

Nursing Informatics in Health Care

Implementing technologies such as Clinical Decision Support Systems (CDSS) is essential for enhancing patient experiences. By providing diagnostic support, optimizing therapeutic regimens, and guiding clinicians through intricate choices, CDSS contributes directly to higher satisfaction levels (Laraichi et al., 2024). Nurse Informaticists (NIs) play a pivotal role in deploying these systems, reducing medication errors through instant alerts, and reinforcing overall patient safety.

Nursing Informatics and the Nurse Informaticist

Nursing informatics merges nursing practice with computing and information science to manage and disseminate clinical data, knowledge, and expertise. Through this discipline, nurses gain the capacity to navigate electronic health records effectively, leading to evidence-informed care (Nashwan et al., 2025). The NI, a nurse with specialized IT proficiency, champions the integration of emerging technologies—training staff, overseeing system upgrades, and ensuring that digital tools translate into improved clinical interventions (American Nurses Association [ANA], 2024). A notable exemplar is Dr. Virginia Saba, whose Clinical Care Classification (CCC) system heightened the precision of nursing documentation (Lopez et al., 2023).

Nurse Informaticists and Other Health Care Organizations

Across the United States, institutions such as the Cleveland Clinic and Mayo Clinic have enlisted NIs to refine their electronic platforms. At Cleveland Clinic, informaticists have tailored electronic health records to enhance workflow efficiency and data accuracy (Cleveland Clinic, 2024). Meanwhile, Mayo Clinic’s NIs have implemented CDSS modules for acute kidney injury management, delivering risk stratification and personalized, evidence-based recommendations at critical decision points (Mayo Clinic, 2024). These initiatives underscore the NI’s function as a bridge between clinical requirements and technological solutions.

Impact of Full Nurse Engagement in Health Care Technology

Engaging frontline nurses in the design and utilization of digital tools yields measurable gains in productivity, care quality, and cost containment. Nurses’ participation ensures that CDSS features align with real-world workflows, minimizing redundant testing and supporting timely interventions (Laraichi et al., 2024). Workflow integration is further enhanced when NIs facilitate multidisciplinary coordination, validate usability, and guide iterative refinements—ultimately translating into both clinical and financial returns (Zhai et al., 2022; Lewkowicz et al., 2020).

Opportunities and Challenges

Nursing informatics creates avenues for elevating patient care via robust data management and decision support. Real-time alerts and analytic dashboards enable proactive treatment adjustments, while targeted training empowers staff to adopt systems confidently (ANA, 2024). Conversely, barriers such as user resistance and privacy concerns necessitate comprehensive change management and stringent security measures—including encryption, multi-factor authentication, and routine audits—to safeguard patient information (Shojaei et al., 2024).

Summary of Recommendation and Justification of the Role

Enhance Diagnostic Accuracy and Safety Hiring NIs to spearhead CDSS projects ensures clinicians receive timely, evidence-based guidance, thereby reducing errors and improving outcomes (Laraichi et al., 2024).
Elevate Data-Driven Care NIs convert complex datasets into actionable insights, supporting nurses in making informed decisions that bolster care quality (Nashwan et al., 2025).
Ensure Secure and Compliant Implementations By overseeing IT governance and staff education on HIPAA and related standards, NIs maintain the confidentiality and integrity of patient records (Shojaei et al., 2024).
Maximize Return on Investment Effective CDSS integration, guided by NIs, curtails unnecessary procedures and tests, yielding significant cost savings over time (Lewkowicz et al., 2020).

Conclusion

Embedding Nurse Informaticists into healthcare teams is a strategic imperative for any organization aiming to leverage digital innovations. Through their dual expertise in clinical practice and information technology, NIs facilitate seamless CDSS adoption, optimize multidisciplinary collaboration, and foster data-driven decision making—ultimately advancing patient safety, care quality, and operational efficiency.

Table Summary

Section	Technology/Focus	NI Role	Outcomes	Key References
Nursing Informatics in Health Care	CDSS adoption	Lead implementation, real-time alerts	Improved patient satisfaction, safety	Laraichi et al. (2024)
Nursing Informatics and the Nurse Informaticist	EHR & classification systems	Staff training, system design	Enhanced data management, documentation	Nashwan et al. (2025); Lopez et al. (2023)
Nurse Informaticists and Other Health Care Organizations	CDSS for AKI, EHR optimization	Bridge clinical needs and IT solutions	Personalized care, workflow efficiency	Cleveland Clinic (2024); Mayo Clinic (2024)
Impact of Full Nurse Engagement in Health Care Technology	Cross-disciplinary integration	Facilitate collaboration, validate usability	Reduced errors, cost savings	Zhai et al. (2022); Lewkowicz et al. (2020)
Opportunities and Challenges	Data security, change management	Develop security protocols, manage training	Staff adoption, compliance	ANA (2024); Shojaei et al. (2024)
Summary of Recommendation and Justification of the Role	CDSS & IT governance	Project leadership, governance	ROI, safety, care quality	Laraichi et al. (2024); Nashwan et al. (2025); Shojaei et al. (2024); Lewkowicz et al. (2020)

References

American Nurses Association. (2024). What is nursing informatics and why is it so important. https://www.nursingworld.org/content-hub/resources/nursing-resources/nursing-informatics/

Cleveland Clinic. (2024). Nursing informatics. https://consultqd.clevelandclinic.org/nursing/nursing-informatics

Laraichi, O., Daim, T., Alzahrani, S., Hogaboam, L., Bolatan, G. I., & Moughari, M. M. (2024). Technology readiness assessment: Case of clinical decision support systems in healthcare. Technology in Society, 79, 102736. https://doi.org/10.1016/j.techsoc.2024.102736

Lewkowicz, D., Wohlbrandt, A., & Boettinger, E. (2020). Economic impact of clinical decision support interventions based on electronic health records. BMC Health Services Research, 20(1), 871. https://doi.org/10.1186/s12913-020-05688-3

Lopez, K. D., Langford, L. H., Kennedy, R., McCormick, K., Delaney, C. W., Alexander, G., Englebright, J., Carroll, W. M., & Monsen, K. A. (2023). Future advancement of health care through standardized nursing terminologies: Reflections from a friends of the National Library of Medicine workshop honoring Virginia K. Saba. Journal of the American Medical Informatics Association, 30(11), 1878–1884. https://doi.org/10.1093/jamia/ocad156

NURS FPX 4045 Assessment 1 Nursing Informatics in Health Care

Mayo Clinic. (2024). Clinical decision support systems for personalized management of patients with acute kidney injury. https://www.mayoclinic.org/medical-professionals/pulmonary-medicine/news/clinical-decision-support-systems-for-personalized-management-of-patients-with-acute-kidney-injury/mac-20524049

Nashwan, A. J., Cabrega, J. A., Othman, M. I., Khedr, M. A., Osman, Y. M., Ashry, A. M. E., Naif, R., & Mousa, A. A. (2025). The evolving role of nursing informatics in the era of artificial intelligence. International Nursing Review, 72(1). https://doi.org/10.1111/inr.13084

Shojaei, P., Gjorgievska, V. E., & Chow, Y.-W. (2024). Security and privacy of technologies in health information systems: A systematic literature review. Computers, 13(2), 41. https://doi.org/10.3390/computers13020041

Zhai, Y., Yu, Z., Zhang, Q., Qin, W., Yang, C., & Zhang, Y. (2022). Transition to a new nursing information system embedded with clinical decision support: A mixed-method study using the HOT-fit framework. BMC Medical Informatics and Decision Making, 22(1), 310. https://doi.org/10.1186/s12911-022-02041-y