Artificial intelligence in health care: Implications for nurse managers

Abstract

The systemic effect of digitalisation, technological developments, improved information processing infrastructures, and the use of data is rapidly transforming health care systems internationally. An increasing pace of development and adoption of artificial intelligence-based technologies have raised expectations, discussions, and concerns. These technologies offer great potential to support different stakeholders in the health care setting; however, all direct and indirect impacts of using these technologies are not always clear. Assessment frameworks have been introduced for generating evidence for decision-makers regarding, for example, health, economic, organisational, social, legal, and ethical implications of these technologies based on a systematic evaluation targeted at safety, efficacy, quality, appropriateness, cost-effectiveness, and efficiency aspects (World Health Assembly, 2014). Research evidence is crucial for assessing these technologies and their impact for appropriate adoption of artificial intelligence in nursing and health care. This special issue of the Journal of Nursing Management is dedicated to artificial intelligence in nursing and health care and it explores implications for nursing management. Artificial intelligence may be defined as human-designed software (potentially also including hardware) systems, which “act in the physical or digital dimension by perceiving their environment through data acquisition, interpreting the collected structured or unstructured data, reasoning on the knowledge, or processing the information, derived from this data and deciding the best action(s) to take to achieve the given goal” (AI HLEG, 2019, p. 6). Several themes emerged from examining the articles included in this special issue. The first subset of studies mainly considered what artificial intelligence-based technologies are relevant for nursing and explored the ethical issues related to artificial intelligence and its applications. Specifically, Chew and colleagues conducted a scoping review to identify artificial intelligence-based technologies that can improve nursing care. The results of 37 studies included in this review provide a useful overview that suggests that these technologies help with the following nursing tasks: documentation, formulating nursing diagnoses and care plans, patient monitoring, and patient care prediction. Further, Su and colleagues conducted a specific bibliometric analysis to understand the impact of artificial intelligence-based technologies on nursing management. The results provide a thorough overview of the studies published on the topic. Finally, Zhu and colleagues examined ethical issues related to a subset of artificial intelligence-based technologies used in elderly care via a scoping review. The results highlight several ethical issues when applying artificial intelligence-based technologies in health care and provide helpful guidance on the next steps needed to evaluate whether these technologies are applied ethically. The second subset of articles focused on understanding the role of artificial intelligence in assessing and improving the quality of care. Specifically, a meta-analysis by Chen and colleagues showed that artificial intelligence-based technologies can be used for improving health care workers' compliance with hand hygiene protocols in four ways, including automated training, electronic counting devices and remote monitoring, real-time hand hygiene reminders and feedback, and automated monitoring. The results of this meta-analysis show that these technologies effectively increase compliance and encourage nurse managers' adoption. A rapid review by Lobo and colleagues describes the literature on technology-based interventions for caregivers of patients suffering from a stroke. The study results show that technology can be used to educate and support caregivers, minimising uncertainty and ensuring a better quality of care for patients after stroke. Zhou and c