Aim: To explore the feasibility of applying artificial intelligence in nurse-patient interaction to assist nurses in grasping patient status and reducing their working hours.
Background: Artificial intelligence has been reshaping the health care industry and has immense potential in nursing care, but there is still a lack of suitable artificial intelligence methods to improve the efficiency of the nurse-patient interaction that takes much time of nurses.
Methods: An artificial intelligence-based intelligent surveillance system was developed to reduce nurses' working hours in nurse-patient interaction, and a two-wave follow-up design was adopted in this study. The data were collected in a nursing home in Guangzhou, China. The first and second waves of data were recorded in the same format on the same patients by the same nurses. The only difference is the deployment of artificial intelligence technology between the two waves of data.
Results: Artificial intelligence-based intelligent surveillance can provide statistical health data for nurses to grasp the patients' status more intuitively, reducing the average nurse-patient interaction time per patient from 18 to 10 min. In addition, artificial intelligence's real-time response to the abnormal health status of patients not only avoids more serious secondary injuries for patients but also prevents nurses from consuming energy in detecting emergencies.
Conclusion: The application of artificial intelligence has great potential to reduce nurses' working hours in nurse-patient interaction. There are still many limitations in artificial intelligence technology at this stage, and it is not feasible to completely rely on artificial intelligence. However, as a tool to assist decision-making, it can still have beneficial impacts on nursing management.
Implications for nursing management: Artificial intelligence has great potential in daily nurse-patient interaction, and nursing facility managers and nurses need to be more open to this new technology.
Keywords: artificial intelligence; intelligent surveillance; nurse-patient interaction; statistical health data; working hours.
© 2022 John Wiley & Sons Ltd.