Background: Since 2011, Indian Cancer Society-Cancer Cure Fund (ICS-CCF), established through donations of mutual fund dividends, has funded $27 million in treatment costs for 9800 underprivileged patients. For governance, a Due Diligence Team (DDT) of cancer experts from academic tertiary centers reviewed every planned treatment and authorized covering the treatment costs for evidence-based care. Since expert time is scarce, in 2019, ICS-CCF introduced NAVYA AI (AI) system to scale the prior authorization operation. AI is a clinically validated system that matches clinical data with evidence and expert recommended treatment options. The system can adapt to institutional guidelines such as ICS-CCF authorization criteria on published survival rates. In this prospective study, we explore application of AI in prior authorization, by assessing concordance with DDT expert decisions and potential time savings. Methods: Clinical data of beneficiaries were input in AI and if the output treatment options matched the planned treatment, the application was authorized, otherwise rejected. If AI did not output a decision, the application was deferred to DDT. Concordance between AI and DDT decisions, and DDT time spent on deferred applications, weremeasured. Results: From April 22nd, 2020 to June 9th, 2021, 1994 beneficiary applications were simultaneously reviewed by AI and DDT, of which 601 (30%) were breast cancer patients. AI “authorized” (1563/1994) or “rejected” (16/1994), 79.18% (1579/1267) of applications; and “deferred” 20.81% (415/1994) of applications. AI and DDT were 99.37% (1553/1563) concordant to authorize and 100% (16/16) concordant to reject a beneficiary application. DDT spent an average of 3.4 minutes/deferred application. Conclusions: A clinically validated AI system, 99% concordant with cancer experts in authorizing or rejecting 79% of beneficiary applications, promises a fivefold decrease in experts’ time, the scarcest resource for preauthorization. Subsequent to this study, ICS-CCF is awarding financial support directly based on AI authorize decisions. Similarly, health insurance organizations may consider a prospective study of the AI system in raising quality and efficiency of prior authorization thereby saving cost of time, money and expertise.

Citation Format: Tushar Vora, Nehal Khanna, Anant Gokarn, Ann Rawat, Naresh Ramarajan, Gitika Srivastava, Usha Thorat. Enhancing impact and efficiency of financial support for cancer through use of AI: A nascent initiative of Indian cancer society [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-16-02.