The increase in interest expense of pharmaceuticals is one of the main factors behind the increase in public health spending in developed countries. This increase is largely explained by demographic factors, such as increasing average age and life expectancy of the population, and, in general, a greater demand for health care. Due to this increase, many leading health authorities in several countries have introduced numerous regulatory actions that have affected the market system, especially on the supply side. These measures are many and varied, as are to set reference prices or lower profits of producers and distributors.
The objective of this study is to quantify the impact of regulatory measures implemented by Spanish healthcare system between 1995 and 2006. The impact is analyzed in three main categories: expenditure per capita, prescriptions per capita, and average prices of health products financed by the Catalan public sector. The authors of this article implement an integrated autoregressive moving time series model (ARIMA for its acronym in English) using dummy variables to represent the various cost containment measures which have been implemented. The data used are the monthly totals charged by pharmacies in prescriptions between January 1995 and December 2006. Data were supplied by the Catalan Health Service.
The results of the regression performed indicate that a large part of the measures implemented to contain health care costs have not been effective in reducing expenditure per capita, the average prices of prescriptions or the number of prescriptions per patient. Especially, the results show that four of the interventions examined, from a total of 16, had a significant negative impact on per capita expenditure, eight interventions had a significant impact on prices (only one with positive impact) and three more had a positive impact on the number of prescriptions per capita (with only one resulting in a reduction). In short, all the interventions reviewed, only four were effective in controlling total spending.