Technological developments and advances have led to new technological innovations and tools that have continually helped healthcare fields, including nursing practice. Such new innovations can be vital to improving nursing care by minimizing the time taken or spent in non-nursing activities and tasks in a bid to support and enhance patient care. Therefore, this discussion focuses on a technology topic and application that has been used in nursing practice or in the lives of my patients. One such topic is artificial intelligence, which has widely been applied to enhance patient outcomes (Yin et al.,2021). Predictive analytics involving artificial intelligence algorithms has been used to analyze large volumes of datasets with a major focus on forecasting patient-related measures such as potential patient deterioration, which then prompts nurses to preemptively intervene (Choudhury & Asan, 2020). Such a step helps prevent adverse events and, hence, improves patient outcomes.
Artificial intelligence-powered clinical decision support systems also help nurses make evidence-based decisions through a synthesis of patient data sets with the latest guidelines and research. Such a step supports accurate diagnoses and formulation of patient-centered care plans, which then enhances the efficacy of care and patient safety (Popescu et al.,2021). AI has also been applied to help foster remote patient monitoring through continuous assessment of health parameters and vital signs. Thus, the patient’s conditions can be monitored remotely in real-time to inform the necessary intervention, lower the chances of readmissions, and improve patient outcomes. It has also fostered precision healthcare through molecular and genetic data analysis. AI can impact the future of nursing practice in various ways; for example, it can enhance interdisciplinary collaboration by allowing interdisciplinary teams to seamlessly communicate and share data to support holistic and more coordinated patient care (Secinaro et al.,2021). It is also likely to support better patient personalized care and improve patient satisfaction.
Choudhury, A., & Asan, O. (2020). Role of artificial intelligence in patient safety outcomes: systematic literature review. JMIR Medical Informatics, 8(7), e18599. https://doi.org/10.2196/18599
Popescu, C., Golden, G., Benrimoh, D., Tanguay-Sela, M., Slowey, D., Lundrigan, E., … & Turecki, G. (2021). Evaluating the clinical feasibility of an artificial intelligence–powered, web-based clinical decision support system for the treatment of depression in adults: longitudinal feasibility study. JMIR Formative Research, 5(10), e31862. https://doi.org/10.2196/31862
Secinaro, S., Calandra, D., Secinaro, A., Muthurangu, V., & Biancone, P. (2021). The role of artificial intelligence in healthcare: a structured literature review. BMC Medical Informatics and Decision Making, 21, 1-23. Doi: 10.1186/s12911-021-01488-9
Yin, J., Ngiam, K. Y., & Teo, H. H. (2021). Role of artificial intelligence applications in real-life clinical practice: systematic review. Journal of Medical Internet Research, 23(4), e25759. https://doi.org/10.2196/25759