Title : The impact of AI in nursing and preventative healthcare
Abstract:
Artificial Intelligence (AI) is transforming the field of nursing and preventative healthcare, offering innovative solutions to improve patient outcomes, streamline workflows, and enhance personalized care. In this paper, we explore the multifaceted roles AI plays in nursing, focusing on predictive analytics, decision support, and remote monitoring. AI-driven predictive models allow for early identification of potential health risks, enabling nurses to intervene proactively. For instance, algorithms can analyze patient data to predict hospital readmissions, infection risks, or chronic disease progression, thus supporting nurses in prioritizing care and optimizing resources. Moreover, AI-based decision support systems are enhancing clinical decision-making by providing evidence-based recommendations, reducing diagnostic errors, and improving treatment protocols. These systems augment the nurse's role by increasing accuracy and efficiency, particularly in high-pressure environments like emergency care. Additionally, AI-powered remote monitoring tools, such as wearable devices and telehealth platforms, are revolutionizing preventive healthcare. Nurses can now remotely track patients’ vital signs, manage chronic conditions, and provide timely interventions, reducing the need for hospital visits and allowing for continuous, real-time care. However, the integration of AI into nursing also presents challenges, including concerns over data privacy, ethical considerations, and the need for ongoing training and adaptation within the nursing workforce. This paper also discusses strategies for overcoming these barriers to ensure that AI is leveraged to complement, rather than replace, the human touch that is central to nursing care. The presentation will highlight both the current and future impacts of AI on nursing practice and preventative healthcare, offering insights into how these technologies can be effectively integrated to improve care quality, patient safety, and healthcare efficiency.
Audience Take Away Notes
- Early Risk Identification: Nurses will learn how to use AI-driven predictive models to identify patients at risk for complications, allowing for early intervention and more effective prioritization of care
- Enhanced Decision-Making: Attendees will understand how AI-based decision support systems can provide evidence-based recommendations, reducing diagnostic errors and improving treatment outcomes
- Remote Patient Monitoring: Nurses will discover how to utilize AI-powered wearables and telehealth tools for continuous patient monitoring, enabling real-time interventions and improved management of chronic conditions
- Workflow Optimization: The session will show how AI can automate routine tasks, such as documentation and scheduling, allowing nurses to focus more on patient-centered care and reducing burnout
- Ethical and Practical Considerations: Nurses will learn best practices for navigating AI-related challenges like data privacy and ethical concerns, ensuring responsible and effective integration into everyday practice
