Artificial intelligent tools: evidence-mapping on the perceived positive effects on patient-care and confidentiality

Abstract

Abstract Background Globally, healthcare systems have always contended with well-known and seemingly intractable challenges like safety, quality, efficient and effective clinical and administrative patient-care services. To firmly confront these and other healthcare challenges, the World Health Organisation proposed a full adoption of artificial intelligence (AI) applications into patient care to stimulate efficiency and guarantee quality in patient management. Purpose This review aimed to establish the extent and type of evidence of the positive effects of the use of AI tools in patient care. Thus, the review mapped evidence by using articles published between January 1, 2010, and October 31, 2023. Methods Consistent with the protocol by Tricco et al., a comprehensive literature search was executed from Nature, PubMed, Scopus, ScienceDirect, Dimensions, Web of Science, Ebsco Host, ProQuest, JStore, Semantic Scholar, Taylor & Francis, Emeralds, World Health Organisation, and Google Scholar. Upholding the inclusion and exclusion standards, 95 peer-reviewed articles were included in this review. Findings We report that the use of AI tools can significantly improve the accuracy of clinical diagnosis to guarantee better patient health outcomes. AI tools also have the ability to mitigate, if not eliminate, most of the factors that currently predict poor patient outcomes. Furthermore, AI tools are far more efficient in generating robust and accurate data in real time and can help ease and accelerate workflow at healthcare facilities. Conclusion If properly integrated into the healthcare system, AI will help reduce patients’ waiting time and accelerate the attainment of Sustainable Development Goals 3.4, 3.8, and 3.b. We propose that AI developers collaborate with public health practitioners and healthcare managers to develop AI applications that appreciate socio-cultural dimensions in patient care.

Keywords

• Artificial Intelligence
• Computer vision system
• Knowledge representation
• Machine intelligence
• Patient data privacy
• Privileged communication