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Paying for Formerly Free Medicines in Spain After 1 Year of Co-Payment: Changes in the Number of Dispensed Prescriptions

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Abstract

Background

After more than three decades of free medicines for the elderly in Spain, in the context of heavy austerity reforms of public financing, a set of cost-sharing reforms on pharmaceutical prescriptions with regional variants have been established in Spain since July 2012.

Objective

The purpose of this analysis is to present the first attempt to provide accurate estimates of the overall impact at the regional level of these cost-sharing reforms.

Methods

We estimated the impact of the reforms on the quantity of dispensed medicines during the first 14 months. We estimated 17 autoregressive integrated moving average (ARIMA) time series models of the monthly number of prescriptions dispensed in pharmacies for the period January 2003–May 2012 in each one of the 17 regions (Autonomous Communities) of Spain. We calculated dynamic forecasts for the horizon June 2012–July 2013 in order to estimate the counterfactual (number of prescriptions that would had been observed without the intervention), and we estimated the impact of cost-sharing changes as the difference between the observed number of accumulated prescriptions at 3, 6, 12, and 14 months and the number predicted by our time-series models (in percentages).

Results

During the last decade the number of dispensed prescriptions has experienced rapid and continuous increases. In the first 14 months after the co-payment reform, the total number of prescriptions decreased dramatically, by more than 20 % in Catalunya, Valencia, and Galicia, by more than 15 % in nine other regions, and by more than 10 % in 15 of the 17 Spanish regions. The results of our model suggest that the new co-payment caused an abrupt shift in the mean level of the time series. No shift in trend has been detected; the previous positive trend remains unchanged in most of the Autonomous Communities.

Conclusion

After decades of unsuccessfully trying to reduce drug spending in the Spanish National Health System through actions on prices and on prescribers, the co-payment established in mid-2012 led to a dramatic reduction in the use of drugs. The health effects of this reduction are not known.

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Acknowledgments

This research has been financed by the Catalan Agency for Health Information, Assessment and Quality (CAHIAQ). The funder has played no role in the study, and the researchers are completely independent of the funders.

Conflict of interest

There is no relevant conflict of interest to disclose.

The plan for the analysis of data was designed by all of the authors. Beatriz G. Lopez-Valcarcel and Santiago Rodríguez-Feijoó conducted the statistical analysis. Jaume Puig-Junoy wrote a substantial proportion of the manuscript. He is the guarantor for the overall content of the manuscript and was also in charge of coordinating the manuscript preparation and submission process. All of the authors critically reviewed drafts of the manuscript prior to submission.

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Correspondence to Jaume Puig-Junoy.

Appendix

Appendix

See Table 3.

Table 3 Autoregressive integrated moving average (ARIMA) estimated models

Y t is the number of prescriptions in month t

t = {1(January 2003), 2(February 2003), … ,}

Log(Y t ) is the natural logarithm of Y t

\( \varepsilon_{t} \) is a white noise series

Definition of dichotomous variables for the treatment of external effects

$$ D_{t}^{{\{ {\text{Month}}\;{\text{year}}\} }} = \left\{ {\begin{array}{*{20}l} 1 & {{\text{if}}\,t = \{ {\text{Month}}\;{\text{Year}}\} } \\ 0 & {{\text{in}}\;{\text{other}}\;{\text{case}}} \\ \end{array} } \right., $$
$$ D_{t}^{{\{ {\text{Month}}\;{\text{Year}}1\} \_\{ {\text{Month}}\;{\text{Year}}2\} }} = \left\{ {\begin{array}{*{20}l} 1 & {{\text{if}}\;{\text{\{Month}}\;{\text{Year}}1{\text{\} }} \le t \le {\text{\{Month}}\;{\text{Year}}1{\text{\} }}} \\ 0 & {{\text{in}}\;{\text{other}}\;{\text{case}}} \\ \end{array} } \right., $$
$$ D_{t}^{{\{ {\text{Month}}\;{\text{Year}}\} \_\{ {\text{End}}\} }} = \left\{ {\begin{array}{*{20}l} 1 & {{\text{If}}\;t \ge \{ {\text{Month}}\;{\text{Year}}\} } \\ 0 & {{\text{in}}\;{\text{other}}\;{\text{case}}} \\ \end{array} } \right., $$
$$ D_{t}^{{\{ {\text{Month}}\} }} = \left\{ {\begin{array}{*{20}l} 1 & {{\text{if}}\;t = \{ {\text{Month}}\} } \\ 0 & {{\text{in}}\;{\text{other}}\;{\text{case}}} \\ \end{array} } \right.. $$

\( \phi_{j} \), autoregressive parameters

\( \theta_{j} \), moving average parameters

\( \gamma_{j} \), other model parameters (constant, dichotomous and linear trend)

L is the lag operator.

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Puig-Junoy, J., Rodríguez-Feijoó, S. & Lopez-Valcarcel, B.G. Paying for Formerly Free Medicines in Spain After 1 Year of Co-Payment: Changes in the Number of Dispensed Prescriptions. Appl Health Econ Health Policy 12, 279–287 (2014). https://doi.org/10.1007/s40258-014-0097-6

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