Role of artificial intelligence in healthcare insurance: systematic literature review

Abstract

Background: The use of artificial intelligence (AI) has been shown to enhance human life quality by making it easier, safer, and more efficient. However, there is currently limited evidence about the applicability of AI in health insurance and easing the complexity of insurance operations. This study seeks to systematically review the literature related to the application, challenges, and opportunities of applying AI in the healthcare insurance industry.

Methods: A systematic review approach was utilized, guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The method included an exploratory and narrative design, a two-phase search strategy, eligibility criteria, and analysis.

Results: The search yielded 520 eligible articles. Twelve articles were eligible, evaluated, and analyzed in this study. Most articles discussed AI’s use in healthcare insurance to detect fraud, improve underwriting accuracy and transparency, and resolve medical information asymmetry. For claim processes, virtual agents, chatbots, customer engagement, telematics, and underwriting, algorithms were essential. However, technical skill is needed to create and deploy AI systems, and privacy was an issue due to massive data and algorithms that could abuse user data.

Discussion: The implementation of AI encounters various challenges, such as insufficient knowledge among users, a deficit in technical expertise and support, shortcomings in data strategy, and a growing reluctance towards AI. Privacy presents a challenge in AI, especially because of the widespread use of large data sets and algorithms that could misuse consumer information.

Keywords

Artificial intelligence / healthcare / systematic literature review / healthcare insurance / machine learning / medical information

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