Artificial Intellegence in Nursing

Artificial Intelligence (AI) combines electronic data collection and robust datasets to give machines the capability to process information. In this article I’ll discuss how AI can facilitate health care management (patient monitoring, wound care), specific nursing care (post-anesthesia care, clinical decision support, medication management), communication with the health care team (electronic medical record (EMR) data, timely communication, patient handoffs), and support for nursing scheduling and management.

AI: Facilitating health care management

There are several wearable devices that can monitor ECGs, heart rate, blood pressure, and oxygen saturation and detect arrhythmias. The Abbott Confirm Rx Insertable Cardiac Monitor, for example, can detect abnormal heart rhythms and recognize and analyze these rhythms, leading to quicker recognition of the need for patients to access care for further evaluation and treatment [1]. Nurses play an important role in facilitating the use of these devices and in teaching patients how to utilize the data to better care for themselves.

AI can help with wound care using specialized image capture, analyzing the images, and noting characteristics such as tissue type, color, depth, and size. An automated analysis allows for standardized and objective measurement, allowing nurses to track a patient’s wound healing accurately. The AI-powered tool, Vac Veriflow Therapy System, identifies early signs of infection, delayed healing, tracks the healing process, and gives real-time feedback to the nurse [2]. This particular AI-powered tool combines negative pressure wound therapy with AI-powered wound assessment, allowing the nurse to make informed decisions and tailor treatment plans accordingly.

AI: Enhancing decision-making and timeliness of nursing care

AI can improve post-anesthesia care. AI-powered monitoring systems with advanced algorithms continually assess and analyze vital signs, ensuring early detection of complications and changes in the patient’s condition. The Early Sense sensor is placed underneath a patient’s mattress to monitor respiratory rate, heart rate, and movement [3]. This system continually analyzes data and notifies the nurse of any significant changes or signs of distress. AI can use predictive analysis to identify risk factors and effectively detect the probability of post-operative infections. This information allows the nurse to respond proactively and monitor for high-risk situations, improving patient safety and outcomes.

AI has the ability to aid clinical decision-making as algorithms can analyze patient data and make evidence-based recommendations to nurses in real-time. The data comes from medical records, lab results, imaging studies, pathology reports, genetic profiles, and medical literature. The results generate tailored treatment options that nurses can consider. These recommendations do not replace nurse decision-making and judgment but can decrease the time required to put nursing plans into action [4].

AI algorithms can improve medication management by reconciling medication lists; flagging inconsistencies, duplicate and conflicting drug orders, and medication errors. The algorithm alerts the nurse to issues

that require attention. AI-powered robots, ‘intelligent medication carts’ can verify medications, reducing medication errors. AI can also anticipate patient medication needs and use predictive analytics to effectively manage inventory.

AI: Improving communication

AI can reduce charting time for nurses by automating data entry with information from a patient’s medical forms, diagnostic imaging results, and laboratory reports. AI can populate information into a patient’s chart and retrieve patient information with a spoken command, reducing errors and reducing the time a nurse spends charting. This technology does not replace the nurse’s contributions and allows for individualization as the nurse can add data that doesn’t populate automatically [5].

AI also analyzes messages the nurse receives and can prioritize them through identification of keywords and assessment of content. A message with the phrase ‘critical condition’ can be marked urgent and get to the nurse more quickly. Algorithms can also be designed to highlight critical lab values and prioritize sending to the nurse.

AI can facilitate patient handoffs. In lieu of compiling information to relay, AI-powered tools can analyze patient data and compile a summary of information for the nurse to share. For example, the iShift platform by the University of California San Diego uses natural language processing to compile concise handoff reports creating an efficient process and reducing the chance of miscommunication. This automated summary provides the foundation for the communication which the nurse can customize and add in any nuances specific to the patient as appropriate [5].

AI and Nursing Scheduling and Management

AI technology can create staffing schedules, ensuring they are balanced, accounting for staff paid time off, and ensuring each nurse is working shift amounts in congruence with their contracted number of hours. AI can generate fair schedules and analyze historical data such as nurse availability and preferences, patient census, seniority, and skill sets to further create a fair and efficient schedule, meeting the organization’s needs and the staff’s preferences [5].

By analyzing historical data and using predictive modeling, AI can forecast staffing needs and coverage gaps and identify nurses with matching skill sets while complying with contractual requirements and labor regulations. The Kronos Workforce Advisor tool in use at the University of Pittsburgh Medical Center has reduced administrative burden and assured fair shift distributions leading to improved employee satisfaction and patient care [5].

AI can streamline nursing processes and facilitate nursing judgment and clinical decision-making. There are many aspects of AI that can be useful to nurses as they work to improve patient safety and outcomes while improving staff satisfaction. Although expensive, AI can benefit nursing practice.

A nurse is an educated, trained professional with a vast array of knowledge and skills. While the use of AI can help to augment and enhance the work of a nurse, it cannot replace the nurse. AI is based on algorithms and ordered rules and cannot perform nursing skills such as insertion of IV or other catheters. AI lacks consciousness and ethical judgment, has no emotional intelligence, can misinterpret context, and lacks the element of human touch and empathy. There is also a need to consider ethical concerns and biased algorithms leading to biased outcomes. AI in healthcare can help us improve efficiency, safety, and patient outcomes, and ultimately allow the nurse more time to practice nursing.

Cynthia Delmas, RN, Founder, The New Bedford Health Initiative

DNP Student, University of Massachusetts Medical School

References

1. About the Confirm Rx Insertable Cardiac Monitor. (n.d.). Www. cardiovascular.abbott https://www.cardiovascular.abbott/us/en/hcp/ products/cardiac-rhythm-management/insertable-cardiac-monitors/ confirm-rx/about.html

2. V.A.C. VERAFLOTM Therapy. (n.d.). Www.acelity.com. https://www.acelity. com/healthcare-professionals/history-of-innovation/vac-veraflo-therapy

3. EarlySense launches streamlined sensor for nursing homes, plans wellnessfocused home sensor. (2016, September 27). MobiHealthNews. https://www. mobihealthnews.com/content/earlysense-launches-streamlined-sensornursing-homes-plans-wellness-focused-home-sensor

4. Clancy, T. R. (2020). Artificial intelligence and nursing: the future is now. JONA: The Journal of Nursing Administration, 50(3), 125-127.

5. Seibert, K., Domhoff, D., Bruch, D., Schulte-Althoff, M., Fürstenau, D., Biessmann, F., & Wolf-Ostermann, K. (2021). Application scenarios for artificial intelligence in nursing care: rapid review. Journal of medical Internet research, 23(11), e26522.