![]() Intelligent computer systems also assist the nursing process, and critical and organized thinking to expedite decision making by synthesizing valuable nursing skills and knowledge. Innovations in technology, including predictive analytics applications, can increase nurse satisfaction and improve this facet of the Quadruple Aim. The newest arm of the Quadruple Aim, which addresses the wellbeing of nurses, physicians and other care providers (Bodheimer & Sinsky, 2014), is enhanced by predictive analytics to alleviate untoward effects of taxing patient care that cause nurse dissatisfaction and burnout. AI and Predictive Analytics Impact on the Quadruple Aim The difference is that AI, particularly predictive analytics, adds breadth and precision to decision making for healthier care experiences for those giving and receiving care. Clinical decision support system (CDSS) functionality offers nurses a means to promote and enhance care delivery by using rules-based tools. While automated and intelligent, AI and predictive analytics nevertheless require, in tandem, strong nursing judgment to make the proper decisions for enabling the right nurse to provide the right care, at the right time for the right patient. With this information, nurses can implement seamless care planning and management to prevent complications, improve patient satisfaction and patient flow, and reduce costly readmissions. For instance, prediction can help nurses determine the appropriate number of days a patient should stay in the hospital. ![]() Through the use of predictive data, nurses can gain actionable insights that enable greater accuracy, timely, and appropriate interventions in a prescriptive way for both patient and nurses. This type of advanced analytics allows nurses to discover previously unknown patterns in multiple sources of clinical and operational data that can guide better decision making. With a greater comprehension of AI, nurses can be at the forefront of embracing and encouraging its use in clinical practice.Įnter predictive analytics, which falls under the umbrella of AI. Difficult to aggregate and analyze, nurses have yet to grasp and use data to its full potential and reap its many benefits. Big Data has arrived and is available readily from multiple sources in vast amounts. However, available data is often incomplete, unclean and lives in disparate systems within organizations. Existing nursing technologies collect and consume healthcare data that are enabled to foretell future events that could hinder care delivery. Also, events that impact the quality of care, such as patient length of stay, hospital readmissions, and patients leaving without being seen in Emergency Departments are difficult to forecast accurately. Guessing and using heuristic methods have become the standard for determining impending patients’ health deterioration and disease progression, interpreting complex radiology results, and matching patient demand for appropriate nurse staffing. Data tends to be used retrospectively in its descriptive form, devoid of prescription. ![]() Historically and still today, decision making in clinical practice and operations is made based on little or no data. The concept and development of AI, defined as computer systems able to perform tasks that usually require human intelligence (English Oxford, 2018) can enhance and expedite a critical component of nursing care delivery, namely decision making. Better Decision Making with PredictionĪrtificial Intelligence is recognized as the aptitude exhibited by smart machines through perceiving, thinking, planning, learning, and the ability to manipulate objects (NITI Aayog, 2018). AI in healthcare is gaining traction, and nurses can harness its power to enhance standard patient care processes and workflows to improve quality of care, impact cost and optimize the patient and provider experience. Big tech companies entering the healthcare AI arena including IBM Watson, Microsoft, and Intel join other prominent industry players such as Google and Amazon to use Big Data-enabled AI solutions for more accurate image recognition, amplified web searching and to enhance the e-commerce experience. New data-driven, intelligent innovations in the healthcare space bring capabilities and the hope of adding value to nursing care delivery. Other once revolutionary technologies developed for high quality, safe patient care are now commonplace in care delivery and education, ranging from electronic health record (EHR) to mobile health (mHealth), telehealth and sensors for remote patient monitoring and simulation. Available at AI Enters the Nursing ArenaĪrtificial intelligence (AI) is a relatively new concept in healthcare, particularly in nursing practice. Online Journal of Nursing Informatics (OJNI), 22(2). Artificial Intelligence, Nurses and the Quadruple Aim.
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