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.
 

• 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.

 

 

 

 

 

  1.  

Aims to improve: Chronic disease management and prevention of acute events. It allows clinicians to proactively adjust treatment based on real-world data, keeping patients healthier at home and reducing costly hospitalizations.

Voice-Assisted Charting Tools:

What it does: Employs Natural Language Processing (NLP) technology to convert spoken clinician notes directly into structured data entries within the EHR.

Aims to improve: Efficiency and reduce documentation burden. By streamlining charting, nurses and providers can spend less time typing and more time on direct patient care, potentially mitigating burnout.

Distributed Digital Ledger System (Blockchain) Patient Identification:

What it does: Pilots a blockchain-based system for securing patient data and identity across disparate systems. The ledger acts as an unchangeable, shared record of patient data access and identity confirmation.

Aims to improve: Data security and interoperability. It aims to ensure that patient records are securely and accurately exchanged between different facilities or providers without compromising privacy.

 

2. Analysis of System-Level Benefits and Risks

 

Implementing AI and other emerging technologies at a system level presents both powerful benefits and complex risks that must be carefully managed.

Sample Answer

 

 

 

 

 

 

 

Innovations and the Evolving Role of Nursing at Harmony Health System

 

The introduction of new technologies at Harmony Health System represents a significant strategic shift toward data-driven, efficient, and interconnected patient care. The case study reveals the promise and peril of these advancements, highlighting the crucial need for robust nursing leadership and thoughtful implementation to ensure that technology genuinely enhances, rather than hinders, human clinical judgment and patient trust.

 

1. Summary of Key Innovations

 

Harmony Health System is implementing four key technological innovations, each designed to address specific challenges in healthcare delivery:

AI-Powered Clinical Decision Support Tool (Sepsis Alert):

What it does: Uses machine learning to analyze real-time Electronic Health Record (EHR) data (heart rate, blood pressure, white blood cell count, fever patterns) to identify the early, subtle signs of sepsis in Emergency Department (ED) patients.

Aims to improve: Safety and timeliness of care. The goal is to prompt early intervention, reduce the severity of sepsis, and improve patient outcomes. Initial results show a decrease in average length of stay by 0.8 days for flagged patients.

Remote Patient Monitoring (RPM) with Wearable Devices:

What it does: Utilizes wearable technology to collect continuous physiological data (e.g., heart rate, activity, sleep) from patients managing chronic diseases outside the clinical setting.