METHODS: Cross-sectional survey design was used for the present study. Pricing data from ten counties including one from South-East Asia, two from Western Pacific and seven from Eastern Mediterranean regions were used in this study. Purchasing power parity (PPP)-adjusted mean unit prices for 26 anti-cancer drug presentations (similar pharmaceutical form, strength, and pack size) were used to compare prices of anti-cancer drugs across three regions. A structured form was used to extract relevant data. Data were entered and analysed using Microsoft Excel®.
RESULTS: Overall, Taiwan had the lowest mean unit prices while Oman had the highest prices. Six (23.1%) and nine (34.6%) drug presentations had a mean unit price below US$100 and between US$100 and US$500 respectively. Eight drug presentations (30.7%) had a mean unit price of more than US$1000 including cabazitaxel with a mean unit price of $17,304.9/vial. There was a direct relationship between income category of the countries and their mean unit price; low-income countries had lower mean unit prices. The average PPP-adjusted unit prices for countries based on their income level were as follows: low middle-income countries (LMICs): US$814.07; high middle income countries (HMICs): US$1150.63; and high income countries (HICs): US$1148.19.
CONCLUSIONS: There is a great variation in pricing of anticancer drugs in selected countires and within their respective regions. These findings will allow policy makers to compare prices of anti-cancer agents with neighbouring countries and develop policies to ensure accessibility and affordability of anti-cancer drugs.
METHODS: We selected two medicines on the 2013 Thai national list of essential medicines (NLEM) [letrozole and imatinib] and three unlisted medicines for the same indications [trastuzumab, nilotinib and dasatinib]. We created timelines of access policies and programs for these products based on scientific and grey literature. Using IMS Health sales data, we described the trajectories of sales volumes of the study medicines between January 2001 and December 2012. We compared estimated average numbers of patients treated before and after the implementation of policies and programs for each product.
RESULTS: Different stakeholders implemented multiple interventions to increase access to the study medicines for different patient populations. During 2007-2009, the Thai Government created a special NLEM category with different coverage requirements for payers and issued compulsory licenses; payers negotiated prices with manufacturers and engaged in pooled procurement; pharmaceutical companies expanded patient assistance programs and lowered prices in different ways. Compared to before the interventions, estimated numbers of patients treated with each medicine increased significantly afterwards: for letrozole from 645 (95% CI 366-923) to 3683 (95% CI 2,748-4,618); for imatinib from 103 (95% CI 72-174) to 350 (95% CI 307-398); and for trastuzumab from 68 (95% CI 45-118) to 412 (95% CI 344-563).
CONCLUSIONS: Government, payers, and manufacturers implemented multi-pronged approaches to facilitate access to targeted cancer therapies for the Thai population, which differed by medicine. Routine monitoring is needed to assess clinical and economic impacts of these strategies in the health system.
METHOD: Assessment of utilization (items dispensed) and expenditure of key LLAs (mainly statins) between 2001 and 2015 in Scotland alongside initiatives.
RESULTS: Multiple interventions over the years have increased international nonproprietary name prescribing (99% for statins) and preferential prescribing of generic versus patented statins, and reduced inappropriate prescribing of ezetimibe. This resulted in a 50% reduction in expenditure of LLAs between 2001 and 2015 despite a 412% increase in utilization, increased prescribing of higher dose statins (71% in 2015) especially atorvastatin following generic availability, and reduced prescribing of ezetimibe (reduced by 72% between 2010 and 2015). As a result, the quality of prescribing has improved.
CONCLUSION: Generic availability coupled with multiple measures has resulted in appreciable shifts in statin prescribing behavior and reduced ezetimibe prescribing, resulting in improvements in both the quality and efficiency of prescribing.
METHODS: A validated computer simulation model (the IMS CORE Diabetes Model) was used to estimate the long-term projection of costs and clinical outcomes. The model was populated with published characteristics of Thai patients with type 2 diabetes. Baseline risk factors were obtained from Thai cohort studies, while relative risk reduction was derived from a meta-analysis study conducted by the Canadian Agency for Drugs and Technology in Health. Only direct costs were taken into account. Costs of diabetes management and complications were obtained from hospital databases in Thailand. Both costs and outcomes were discounted at 3 % per annum and presented in US dollars in terms of 2014 dollar value. Incremental cost-effectiveness ratio (ICER) was calculated. One-way and probabilistic sensitivity analyses were also performed.
RESULTS: IGlar is associated with a slight gain in quality-adjusted life years (0.488 QALYs), an additional life expectancy (0.677 life years), and an incremental cost of THB119,543 (US$3522.19) compared with NPH insulin. The ICERs were THB244,915/QALY (US$7216.12/QALY) and THB176,525/life-year gained (LYG) (US$5201.09/LYG). The ICER was sensitive to discount rates and IGlar cost. At the acceptable willingness to pay of THB160,000/QALY (US$4714.20/QALY), the probability that IGlar was cost effective was less than 20 %.
CONCLUSIONS: Compared to treatment with NPH insulin, treatment with IGlar in type 2 diabetes patients who had uncontrolled blood glucose with oral anti-diabetic drugs did not represent good value for money at the acceptable threshold in Thailand.