Systematic Review : Cost-Effectiveness Analysis of Artificial Intelligence in Cancer Treatment

Abstract

Cancer is one of the leading causes of death and is estimated to cause huge global economic losses. Artificial intelligence (AI) has massively assisted in the diagnosis, prognosis, and determination of the most effective therapy for cancer patients. The utilization of AI is estimated to reduce healthcare expenditures. This study aimed to systematically review the implementation of AI and its cost-effectiveness in cancer treatment. The study followed PRISMA guidelines and utilized the PubMed database. The search strategy was conducted up to 2 September 2023 using three main keywords; “Cost-effectiveness analysis”, “Cancer”, and “Artificial intelligence”. From 1746 retrieved articles, a total of 11 articles were included in the analysis. Studies found two types of AI interventions in cancer; screening type intervention(n = 6; 55%) and surgery type (n = 5; 45%). Prostate cancer was the most frequently studied (n = 3; 27%). The cost-effectiveness analysis showed that the implementation of AI was cost-effective (n=5, 46%), particularly in cancer screening intervention. The review highlights two main groups of AI interventions in cancer care: screening and cancer surgery. From a cost-effectiveness point of view, AI intervention in screening was the most cost-effective strategy in cancer. On the other hand, the AI implementation in surgery showed inconsistent findings, with many studies not fully addressing the full economic evaluation.

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