Artificial intelligence assisted telehealth for nursing: A scoping review

Abstract

Background

Due to the COVID-19 pandemic, telehealth resurfaced as a convenient efficient healthcare delivery method. Researchers indicate that Artificial Intelligence (AI) could further facilitate delivering quality care in telehealth. It is essential to find supporting evidence to use AI-assisted telehealth interventions in nursing.

Objectives

This scoping review focuses on finding users’ satisfaction and perception of AI-assisted telehealth intervention, performances of AI algorithms, and the types of AI technology used.

Methods

A structured search was performed in six databases, PubMed, CINAHL, Web of Science, OVID, PsycINFO, and ProQuest, following the guidance of the Preferred Reporting Items for Systematic Review and Meta-Analysis Extension for Scoping Reviews. The quality of the final reviewed studies was assessed using the Medical Education Research Study Quality Instrument.

Results

Eight of the 41 studies published between 2017 and 2022 were included in the final review. Six studies were conducted in the United States, one in Japan, and one in South Korea. Four studies collected data from participants (n = 3014). Two studies used image data (n = 1986), and two used sensor data from smart homes to detect patients’ health events for nurses (n = 35). The quality of studies implied moderate to high-quality study (mean = 10.1, range = 7.7–13.7). Two studies reported high user satisfaction, three assessed user perception of AI in telehealth, and only one showed high AI acceptability. Two studies revealed the high performance of AI algorithms. Five studies used machine learning algorithms.

Conclusions

AI-assisted telehealth interventions were efficient and promising and could be an effective care delivery method in nursing.