ECONOMIC EVALUATION OF AI-POWERED DIGITAL COLPOSCOPY IN WOMEN REFERRED FOR COLPOSCOPIC ASSESSMENT FOLLOWING ABNORMAL HPV SCREENING IN INDIA
Author(s)
Aaryaman Yashasvi Raj, MSc, Sai Vijaya Durga Yalla, PharmD, Reeti Basu, MSc, Kavita Kachroo, MBA, MHA, Jitendra Sharma.
Kalam Institute of Health Technology ( KIHT), Visakhapatnam, India.
Kalam Institute of Health Technology ( KIHT), Visakhapatnam, India.
OBJECTIVES: To evaluate the cost-effectiveness of AI-powered digital colposcopy compared with conventional colposcopy for the triage and diagnostic assessment of women with positive cervical cancer screening results in India, from a healthcare payer’s perspective, using a lifetime horizon cost-utility analysis.
METHODS: A cost-utility analysis was conducted for a hypothetical cohort of 10,000 women aged 30-35 years referred after positive VIA-based cervical cancer screening. A Markov model with annual cycles and lifetime horizon was developed. Diagnostic accuracy inputs were derived from a pooled meta-analysis of 18 studies. Costs were estimated using a bottom-up micro-costing approach based on CGHS 2024 and NHM rate schedules. Utility values were obtained from published Indian literature. Costs and QALYs were discounted at 3% annually. The willingness-to-pay threshold was set at ₹2,30,000/QALY. Uncertainty was assessed through one-way sensitivity analysis and probabilistic sensitivity analysis using 1,000 Monte Carlo simulations.
RESULTS: AI-DC generated 225,380 QALYs at a discounted lifetime cost of ₹70.56 crore compared with 225,208 QALYs and ₹71.58 crore for conventional colposcopy. AI-DC resulted in an incremental gain of 172.36 QALYs with cost savings of ₹1.02 crore, yielding an ICER of ₹−59,057/QALY and demonstrating economic dominance. The net monetary benefit was ₹4.98 crore at the willingness-to-pay threshold. Over the lifetime horizon, AI-DC averted 12 additional cervical cancer deaths compared with conventional colposcopy. Probabilistic sensitivity analysis confirmed robustness of results across simulations.
CONCLUSIONS: AI-powered digital colposcopy is a cost-saving and more effective alternative to conventional colposcopy in the Indian healthcare setting. Adoption of AI-DC within national cervical cancer screening programmes may improve access to timely diagnosis while reducing long-term healthcare costs.
METHODS: A cost-utility analysis was conducted for a hypothetical cohort of 10,000 women aged 30-35 years referred after positive VIA-based cervical cancer screening. A Markov model with annual cycles and lifetime horizon was developed. Diagnostic accuracy inputs were derived from a pooled meta-analysis of 18 studies. Costs were estimated using a bottom-up micro-costing approach based on CGHS 2024 and NHM rate schedules. Utility values were obtained from published Indian literature. Costs and QALYs were discounted at 3% annually. The willingness-to-pay threshold was set at ₹2,30,000/QALY. Uncertainty was assessed through one-way sensitivity analysis and probabilistic sensitivity analysis using 1,000 Monte Carlo simulations.
RESULTS: AI-DC generated 225,380 QALYs at a discounted lifetime cost of ₹70.56 crore compared with 225,208 QALYs and ₹71.58 crore for conventional colposcopy. AI-DC resulted in an incremental gain of 172.36 QALYs with cost savings of ₹1.02 crore, yielding an ICER of ₹−59,057/QALY and demonstrating economic dominance. The net monetary benefit was ₹4.98 crore at the willingness-to-pay threshold. Over the lifetime horizon, AI-DC averted 12 additional cervical cancer deaths compared with conventional colposcopy. Probabilistic sensitivity analysis confirmed robustness of results across simulations.
CONCLUSIONS: AI-powered digital colposcopy is a cost-saving and more effective alternative to conventional colposcopy in the Indian healthcare setting. Adoption of AI-DC within national cervical cancer screening programmes may improve access to timely diagnosis while reducing long-term healthcare costs.
Conference/Value in Health Info
2026-09, ISPOR Asia Pacific 2026, Bangkok, Thailand
Value in Health, Volume 55, Issue S1
Code
EE25
Topic
Economic Evaluation
Topic Subcategory
Thresholds & Opportunity Cost, Value of Information
Disease
SDC: Oncology