Review the concepts of technology application as presented in the Resources.
Reflect on how emerging technologies such as artificial intelligence may help fortify nursing informatics as a specialty by leading to increased impact on patient outcomes or patient care efficiencies.
In a 4 page project proposal written to the leadership of your healthcare organization, propose a nursing informatics project for your organization that you advocate to improve patient outcomes or patient-care efficiency. Your project proposal should include the following:
Describe the project you propose.
Identify the stakeholders impacted by this project.
Explain the patient outcome(s) or patient-care efficiencies this project is aimed at improving and explain how this improvement would occur. Be specific and provide examples.
Identify the technologies required to implement this project and explain why.
Identify the project team (by roles) and explain how you would incorporate the nurse informaticist in the project team.
transitioning from a universal, reactive approach to a targeted, proactive one, this initiative will dramatically improve patient safety, optimize nursing workflows, and generate a significant return on investment through the prevention of costly fall-related injuries. This project will position our organization as a leader in patient safety innovation and a model for technology-driven quality improvement.
2.0 Project Description
The proposed project, titled "Proactive Patient Safety through Predictive Analytics," involves the development and implementation of a predictive risk-scoring system. This system will utilize a machine learning model to continuously analyze a wide array of patient data points sourced from our Electronic Health Record (EHR) and other smart hospital technologies. The AI will integrate data such as:
Patient Demographics: Age, medical history, and past fall events.
Clinical Data: Medication administration records (e.g., sedatives, diuretics), lab results, and vitals.
Environmental Data: Data from smart beds that monitor patient movement and from wearable sensors.
Nursing Documentation: Braden scale scores and existing fall risk assessments.
The AI will process this information to generate a dynamic, real-time fall risk score for each patient. This score will be presented to nurses on their mobile devices and within the EHR. When a patient's risk score exceeds a predetermined threshold, the system will trigger an alert, prompting nurses to implement immediate, personalized interventions. This targeted approach allows for the efficient allocation of nursing resources to patients who are at the greatest risk, fundamentally transforming our fall prevention strategy from a broad, manual effort to a precise, data-driven one.
3.0 Stakeholders and Project Benefits
This project will impact a wide range of stakeholders across the organization.
Stakeholders:
Patients and Families: The primary beneficiaries of improved safety and reduced risk of injury.
Nursing Staff: The end-users of the system who will be empowered with data to make better care decisions.
Hospital Leadership: Responsible for strategic initiatives, quality, and financial performance.
Quality and Safety Department: The team responsible for monitoring and reporting on patient safety metrics.
IT Department: The technical team responsible for implementation, integration, and ongoing maintenance.
Physicians and Allied Health Professionals: Will use the system's data to inform their care plans.
Patient Outcomes and Patient-Care Efficiencies
The project is specifically aimed at improving two critical areas:
Improved Patient Outcomes: A Direct Reduction in Patient Falls.
Explanation: The predictive analytics system will shift our focus from reacting to fall events to actively preventing them. Current fall risk assessments are often static, based on initial admission data. Our proposed system provides a dynamic, real-time risk score. For example, a patient may be low-risk in the morning but their risk score could spike after receiving a sedative or experiencing a drop in blood pressure. The system would immediately alert the nurse to this change, allowing for a proactive intervention, such as placing a bed alarm, providing assistance to the restroom, or adjusting medication timing. This targeted intervention prevents the fall from occurring in the first place, leading to a direct reduction in patient injuries, fractures, and head trauma.
Sample Answer
Project Proposal: Predictive Analytics for Patient Fall Prevention
To: Healthcare Organization Leadership From: [Your Name], Nursing Informatics Specialist Date: September 21, 2025 Subject: Proposal for a Nursing Informatics Project to Implement a Predictive Analytics System to Reduce Patient Falls
1.0 Executive Summary
This proposal outlines a nursing informatics project to implement an artificial intelligence (AI)-powered predictive analytics system to significantly reduce patient falls within our organization. Patient falls represent a major challenge in healthcare, leading to increased patient injury, prolonged hospital stays, and substantial financial burdens. Our current fall prevention protocols, while important, are often reactive and resource-intensive. This project will leverage emerging AI technology to analyze real-time patient data, identify individuals at a high risk of falling before an event occurs, and empower our nursing staff with actionable, evidence-based alerts. By