Case Study: Evaluating Artificial Intelligence (AI) in Clinical Practice
Harmony Health System, a large regional healthcare network, recently implemented an AI-powered clinical decision- making support tool in their emergency department (ED). The system uses machine learning, a type of AI, to analyze real-time electronic health record (EHR) data to identify clients at high risk for sepsis and alerts clinicians to act before symptoms become critical.
Initial Outcomes
Within the first three months of implementation, the tool flagged thirty-eight (38) patients showing early signs of sepsis by detecting patterns such as changes in heart rate, blood pressure, white blood cell count, and fever. Twenty-five (25) of those patients received earlier interventions than would have occurred through traditional workflows. As a result, the average length of stay decreased by 0.8 days for flagged patients.
Staff Reactions
Clinical staff expressed mixed feelings about the tool. Some appreciated the additional safety net it provided, while others voiced concerns about over-reliance on AI at the expense of clinical judgment. Issues such as data privacy, given the system’s constant surveillance of EHRs, and disruptions to workflow during triage and patient handoffs were also raised.
Concurrent Innovations at Harmony Health System
Alongside the sepsis tool, Harmony Health System is implementing other innovations. Remote patient monitoring using wearable devices is being introduced to support chronic disease management. Voice-assisted charting tools are being tested to reduce documentation burden and improve efficiency. In addition, a distributed digital ledger system (often referred to as blockchain) based patient identification system is being piloted to secure data exchange and enhance interoperability.
The Chief Nursing Officer (CNO) is leading a task force to assess nurse readiness and training needs as these technologies roll out. Despite these advances, many patients remain unaware that AI plays a role in their care. Meanwhile, the IT department has reported minor integration issues between the new technologies and existing legacy systems.
Stakeholder Perspectives
Stakeholders have highlighted both opportunities and challenges.
· An ED nurse commented, “It’s helpful, but I don’t want it to become a crutch. What happens when the alert doesn’t fire?”
· The CNO noted, “AI should enhance—not replace—nursing judgment. But further training is needed to ensure nurses are confident using it.”
· A patient advocate stressed, “Transparency matters. Clients should know AI is influencing their care decisions.”
After reviewing the case study, answer the following prompts:
1. Summarize the key innovations introduced at Harmony Health System. Briefly explain what each technology does and how it aims to improve healthcare delivery or outcomes.
2. Analyze the benefits and risks of implementing AI and other emerging technologies at a system level. Consider issues like safety, efficiency, equity, privacy, and ethical implications. Support your response with at least one scholarly or professional source
3. Discuss how these technologies affect nursing practice, including roles, workflows, collaboration, and patient care responsibilities. Reflect on potential shifts in how nurses work and advocate for their patients in tech-enhanced environments.
4. Reflect on one emerging trend in healthcare informatics (such as predictive analytics, wearables, or blockchain). Explain why you find it promising and how it might transform patient care over the next 5–10 years.
Universal Design Assignment Instructions
Choose one format for your response:
· Written Essay (2-3 pages double spaced in APA format. The 2-3 pages does not include the cover page and the reference page.)
· attach a reference page which includes a minimum of 2 peer-reviewed scholarly journals within 5 years.
See rubric for additional details.
Suggested Resources
American Nurses Association (2022). Nursing Informatics: Scope and Standards of Practice.
Nashwan, A. J., Cabrega, J. C. A., Othman, M. I., Khedr, M. A., Osman, Y. M., ElAshry, A. M., Naif, R., & Mousa, A. A. (2025). The evolving role of nursing informatics in the era of artificial intelligence. International Nursing Review, 72(1), e13084. https://doi.org/10.1111/inr.13084Links to an external site.
Hardy, L. R. (2024). Health informatics: An interprofessional approach. Elsevier.
LaBoone, P. A., & Marques, O. (2024). Overview of the future impact of wearables and artificial intelligence in healthcare workflows and technology. International Journal of Information Management Data Insights, 4(2), Article 100294. https://doi.org/10.1016/j.jjimei.2024.100294Links to an external site.
Center for Connected Medicine. (2024, December 6). Early successes, untapped potential, lingering questions: AI adoption in healthcare report 2024. https://connectedmed.com/resources/ai-adoption-in-healthcare-report-2024/
Watson A.L. (2024). Ethical considerations for artificial intelligence use in nursing informatics. Nursing Ethics. 31(6):1031-1040. doi: 10.1177/09697330241230515Links to an external site.
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