Login / Signup

Reimbursement Lag of New Drugs Under Taiwan's National Health Insurance System Compared With United Kingdom, Canada, Australia, Japan, and South Korea.

Yi-Ru ShihKai-Hsin LiaoYen-Hui ChenFang-Ju LinFei-Yuan Hsiao
Published in: Clinical and translational science (2020)
Drug lag-delayed approval or reimbursement-is a major barrier to accessing cutting-edge drugs. Unlike approval lag, reimbursement lag is under-researched. We investigated the key determinants of reimbursement lag under Taiwan National Health Insurance (NHI), and compared this lag with those in the United Kingdom, Canada, Australia, Japan, and South Korea. Using retrospective data on 190 new NHI-reimbursed drugs from 2007 to 2014, we studied reimbursement lag in Taiwan vs. other countries, and investigated associated factors using generalized linear models (GLMs). The median reimbursement lags during before ("first-generation") and after ("second-generation") NHI drug reimbursement scheme in Taiwan were 378 and 458 days, respectively. The "first-generation" lag was shorter only than that in South Korea, whereas the "second-generation" lag only exceeded those of the United Kingdom and Japan. In GLM models, higher drug expenditure and the introduction of the "second-generation" NHI were two statistically significant parameters associated with reimbursement lag among antineoplastic and immunomodulating agents. For other drug classes, the reimbursement price proposed by pharmaceutical companies and use of price-volume agreements were two statistically significant parameters associated with longer reimbursement lags. The current reimbursement lag in Taiwan is longer than 1 year, but only longer than those of the United Kingdom and Japan. The determinants differ between drug categories. A specific review process for antineoplastic and immunomodulating drugs may expedite reimbursement. There is a clear need for systematic data collection and analysis to ascertain factors associated with reimbursement lag and thereby inform future policy making.
Keyphrases
  • health insurance
  • healthcare
  • drug induced
  • public health
  • mental health
  • emergency department
  • quality improvement
  • electronic health record
  • big data
  • high resolution
  • atomic force microscopy
  • deep learning
  • neural network