THE IMPACT OF POLICY AND DEMOGRAPHIC VARIABLES ON FUTURE PRESCRIPTION COSTS FOR A PUBLICLY FUNDED HEALTH SCHEME IN IRELAND
Author(s)
ConwayLenihan A1, Woods N2
1Cork Institute of Technology, Cork, Ireland, 2University College Cork, Cork, Ireland
Presentation Documents
OBJECTIVES: Ireland has one of the highest pharmaceutical spends per capita in the European Union. The General Medical Services (GMS) is the largest publicly funded health scheme in Ireland, where 40% of the population were eligible to free health care in 2012. This research quantifies the impact of policy and demographic variables on future GMS prescription costs in Ireland. METHODS: Data on GMS coverage , claims rates and average cost per claimant (policy variables) are drawn from the 2012 Health Service Executive-Primary Care Reimbursement Service (HSE-PCRS) population database and combined with 2013 Central Statistics Office (CSO) population projections. Data was aggregated by old health board region, age cohort and sex. A Monte Carlo Simulation model simulated the effects of demographic and policy variables on future GMS prescribing costs between 2016 and 2026. RESULTS: The Irish population is estimated to increase by 10% to 5 million, between 2012 and 2026. The over 70s population is estimated to grow by 64% over this time period with the dependency ratio estimated to be 0.27 in 2026. GMS coverage (percentage of population who are eligible for free health care) rates are estimated to lie between 33% and 46% in 2026. The average cost per claimant is estimated to increase from €847.18 in 2016 to €1032.71 in 2026 and GMS prescription costs are estimated to increase from €1.1 billion to €1.8 billion. The under 11s and over 70s are estimated to have the greatest impact on future GMS prescription costs. The Mid-Western, South-Eastern and males are driving costs in the under 11s, whereas females, the Midlands and Southern regions are driving costs in the over 70s. CONCLUSIONS: This research found an aging population will contribute to future GMS prescription costs and has the potential to cause an increase in GMS coverage rates, claims rates and average cost per claimant.
Conference/Value in Health Info
2016-10, ISPOR Europe 2016, Vienna, Austria
Value in Health, Vol. 19, No. 7 (November 2016)
Code
PHP102
Topic
Economic Evaluation
Topic Subcategory
Cost/Cost of Illness/Resource Use Studies
Disease
Multiple Diseases