Patient’s overview of using Artificial Intelligence (AI) in health care: A Systematic Review

Document Type : Review Article/ Systematic Review Article/ Meta Analysis

Authors

1 MSc in Medical Informatics, Health Information Technologies Unit of Economic Health Department, Mashhad University of Medical Sciences, Mashhad, Iran

2 Bachelor degree in Medical Records, Mashhad University of Medical Sciences, Mashhad, Iran

3 Mashhad University of Medical Sciences

10.30483/rijm.2024.254543.1341

Abstract

Background: Given that artificial intelligence (AI) is a newly emerging field transforming the practice of medicine, the end-user perspective is of paramount importance for its success and acceptance.

Objectives: This systematic review aimed to capture an overview of qualitative and quantitative surveys related to patients' opinions on the use of AI within healthcare settings.

Materials and Methods: In this systematic review, a query was conducted on PubMed for original studies that surveyed patients' opinions using qualitative and quantitative methods. The key inclusion criteria were papers assessing patient viewpoints assessed by interviews and those exploring opinions via questionnaires. The data extraction process involved collaborative analysis to ensure reliability.

Results: This systematic review analyzed 26 studies on patient perspectives of AI in healthcare. The majority of articles used quantitative surveys (65.4%) or qualitative interviews (19.2%), with convenience and purposive sampling being the most common. Cancer patients were the most frequent group studied (26.9%), with research on AI applications in cancer care. The key factors examined in quantitative surveys were prior AI exposure, perceptions of the advantages/drawbacks of AI, and privacy/trust concerns. Qualitative studies focused on AI knowledge, usage barriers, benefits, and facilitators.

Conclusion: This literature review examined how demographic factors, trust, and knowledge impact patient perspectives on integrating AI in healthcare. The obtained results highlighted the need for educational initiatives to address knowledge gaps and facilitate the smooth integration of AI-powered solutions, leveraging their potential to enhance patient care and service delivery.

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Razavi International Journal of Medicine
Volume 12, Issue 3
August 2024
Pages 1-11

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