DYNAMIC BUDGET IMPACT ANALYSIS OF SOFTWARE AS A MEDICAL DEVICE (SAMD) ASSISTED LOW DOSE COMPUTED TOMOGRAPHY (LDCT) INTERPRETATION FOR POST TREATMENT SURVEILLANCE OF LUNG CARCINOMA IN SITU
Author(s)
Hsiao Ling Chen, Ph.D.1, Wei-ming Huang, PharmD, MD2, Ming-Yu Hong, MS.3, Chen-Han Chueh, PhD4, Heng-sheng Chao, PhD,MD5, Shuu-Jiun Wang, PhD6, Yi-Wen Tsai, PhD7.
1Institute of Health and Welfare Policy, National Yang Ming Chiao Tung University, Taipei, Taiwan, 2Institute of Health and Welfare Policy, Taipei, Taiwan, 3Institute of Health and Welfare Policy, National Yang Ming Chiao Tung University, Taiwan, New Taipei City, Taiwan, 4University of California San Diego, San Diego, CA, USA, 5Department of Chest Medicine, Taipei Veterans General Hospital, Taipei, Taiwan, 6• College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, 7National Yang Ming Chiao Tung University, Taipei, Taiwan.
1Institute of Health and Welfare Policy, National Yang Ming Chiao Tung University, Taipei, Taiwan, 2Institute of Health and Welfare Policy, Taipei, Taiwan, 3Institute of Health and Welfare Policy, National Yang Ming Chiao Tung University, Taiwan, New Taipei City, Taiwan, 4University of California San Diego, San Diego, CA, USA, 5Department of Chest Medicine, Taipei Veterans General Hospital, Taipei, Taiwan, 6• College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, 7National Yang Ming Chiao Tung University, Taipei, Taiwan.
OBJECTIVES: SaMD-assisted LDCT interpretation may improve reporting efficiency in post-treatment surveillance for lung carcinoma in situ (CIS). Because public payers rely on budget impact estimates to inform reimbursement and price negotiations, such analyses should capture changing service demand across disease trajectories. This study estimated the 5-year budget impact of reimbursing SaMD-assisted LDCT interpretation in Taiwan from 2027 to 2031.
METHODS: A dynamic Markov-based budget impact model was developed from the Taiwan National Health Insurance perspective. Annual incident CIS cohorts were projected using Taiwan cancer registry trends and accumulated over time to estimate the population requiring LDCT surveillance. The reference scenario assumed radiologist-only LDCT interpretation, whereas the new scenario incorporated SaMD as an adjunct to radiologist interpretation. Costs included LDCT examination, SaMD interpretation, and biopsy-related diagnostic costs. Two uptake scenarios were evaluated: conservative adoption increasing from 0.4% to 10.0%, and optimistic adoption increasing from 3.0% to 25.0%. Physician time savings were estimated from observed interpretation and reporting times.
RESULTS: The estimated CIS surveillance population increased from 9,874 in 2027 to 32,593 in 2031. Under conservative uptake, SaMD-assisted LDCT use increased from 39 to 3,259 scans, with annual incremental budget impact rising from NTD 85,345 to NTD 7,049,648 and a cumulative 5-year impact of NTD 10,879,397. Physician time savings totaled 21,294 minutes. Under optimistic uptake, SaMD-assisted LDCT use increased from 296 to 8,148 scans, with annual incremental budget impact rising from NTD 639,405 to NTD 17,604,791 and a cumulative impact of NTD 34,699,633. Physician time savings totaled 67,994 minutes.
CONCLUSIONS: This dynamic Markov-based model captured time-varying LDCT use across CIS cohorts. SaMD-assisted LDCT interpretation may reduce physician reading and reporting time in high-volume surveillance, and the estimated budget impact provides a basis for reimbursement planning.
METHODS: A dynamic Markov-based budget impact model was developed from the Taiwan National Health Insurance perspective. Annual incident CIS cohorts were projected using Taiwan cancer registry trends and accumulated over time to estimate the population requiring LDCT surveillance. The reference scenario assumed radiologist-only LDCT interpretation, whereas the new scenario incorporated SaMD as an adjunct to radiologist interpretation. Costs included LDCT examination, SaMD interpretation, and biopsy-related diagnostic costs. Two uptake scenarios were evaluated: conservative adoption increasing from 0.4% to 10.0%, and optimistic adoption increasing from 3.0% to 25.0%. Physician time savings were estimated from observed interpretation and reporting times.
RESULTS: The estimated CIS surveillance population increased from 9,874 in 2027 to 32,593 in 2031. Under conservative uptake, SaMD-assisted LDCT use increased from 39 to 3,259 scans, with annual incremental budget impact rising from NTD 85,345 to NTD 7,049,648 and a cumulative 5-year impact of NTD 10,879,397. Physician time savings totaled 21,294 minutes. Under optimistic uptake, SaMD-assisted LDCT use increased from 296 to 8,148 scans, with annual incremental budget impact rising from NTD 639,405 to NTD 17,604,791 and a cumulative impact of NTD 34,699,633. Physician time savings totaled 67,994 minutes.
CONCLUSIONS: This dynamic Markov-based model captured time-varying LDCT use across CIS cohorts. SaMD-assisted LDCT interpretation may reduce physician reading and reporting time in high-volume surveillance, and the estimated budget impact provides a basis for reimbursement planning.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
EE78
Topic
Economic Evaluation, Health Policy & Regulatory, Health Technology Assessment
Topic Subcategory
Budget Impact Analysis
Disease
Oncology