Artificial intelligence (AI) is a relatively new concept in healthcare, particularly in nursing practice. Other once revolutionary technologies developed for high quality, safe patient care are now commonplace in care delivery and education, ranging from electronic health records (EHRs) to mobile health (mHealth), telehealth and sensors for remote patient monitoring and simulation.
New data-driven, intelligent innovations in the healthcare space bring capabilities and the hope of adding value to nursing care delivery. Big tech companies entering the healthcare AI arena use big data-enabled AI solutions for more accurate image recognition, amplified web searching and enhanced e-commerce experiences. AI in healthcare is gaining traction, together, AI and nursing can lead to enhancements in standard patient care processes and workflows to improve quality of care, impact cost and optimize the patient and provider experience (the Quadruple Aim).
AI is recognized as the aptitude exhibited by smart machines through perceiving, thinking, planning, learning, and the ability to manipulate objects. The concept and development of AI, defined as computer systems able to perform tasks that usually require human intelligence can enhance and expedite a critical component of nursing care delivery, namely decision making.
Historically and still today, decision making in clinical practice and operations is made based on little or no data. Guessing and using problem-solving methods have become the standard for determining patients’ health status, interpreting complex radiology results, and matching patient demand for appropriate nurse staffing. 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.
Existing nursing technologies collect and consume healthcare data that are used to predict future events that could disrupt care delivery. However, available data is often incomplete, unclean and lives in different systems within organizations.
Big Data has arrived and is available readily from multiple sources in vast amounts. Difficult to aggregate and analyze, nurses have yet to grasp and use data to its full potential and reap its many benefits. With a greater comprehension of AI, nurses can be at the forefront of embracing and encouraging its use in clinical practice.
Enter predictive analytics, which falls under the umbrella of AI. 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.
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. For instance, prediction can help nurses determine the appropriate number of days a patient should stay in the hospital. With this information, nurses can implement seamless care planning and management to prevent complications, improve patient satisfaction and patient flow, and reduce costly readmissions.
While automated and intelligent, AI and predictive analytics nevertheless require strong nursing judgment to make the proper decisions so the right nurse can provide the right care at the right time for the right patient. Clinical decision support system (CDSS) functionality offers nurses a means to promote and enhance care delivery by using rules-based tools. Together, AI and nursing can extendCDSS used in care. 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.
The newest arm of the Quadruple Aim, which addresses the wellbeing of nurses, physicians and other care providers, is enhanced by predictive analytics to alleviate nurse dissatisfaction and burnout. Innovations in technology, including predictive analytics applications, can increase nurse satisfaction and improve this facet of the Quadruple Aim. Intelligent computer systems also assist the nursing process, and critical and organized thinking to expedite decision making by developing valuable nursing skills and knowledge.
Why should nurses care about these innovations? When brought together, predictive analytics, AI and nursing can evolve nurses’ thinking about care delivery and operational tasks in functionally disruptive ways to serve the Quadruple Aim. With this shift, nurses can begin to advocate for the adoption and use of AI in patient care delivery.
Leveraging AI and prediction will further the healthcare industry’s movement towards the development of data-driven solutions. It will also enhance the quality of nursing care more cost-effectively, improving population outcomes and optimizing patient and nurse satisfaction in the transforming healthcare landscape.
The views and opinions expressed in this blog or by commenters are those of the author and do not necessarily reflect the official policy or position of HIMSS or its affiliates.
Powered by the HIMSS Foundation and the HIMSS Nursing Informatics Community, the Online Journal of Nursing Informatics is a free, international, peer reviewed publication that is published three times a year and supports all functional areas of nursing informatics.