Co-prescription patterns of cardiovascular preventive treatments: a cross-sectional study in the Aragon worker' health study (Spain).

OBJECTIVES

To identify cardiovascular disease (CVD) preventive treatments combinations, among them and with other drugs, and to determine their prevalence in a cohort of Spanish workers.

DESIGN

Cross-sectional study.

SETTING

Aragon Workers' Health Study (AWHS) cohort in Spain.

PARTICIPANTS

5577 workers belonging to AWHS cohort. From these subjects, we selected those that had, at least, three prescriptions of the same therapeutic subgroup in 2014 (n=4605).

PRIMARY AND SECONDARY OUTCOME MEASURES

Drug consumption was obtained from the Aragon Pharmaceutical Consumption Registry (Farmasalud). In order to know treatment utilisation, prevalence analyses were conducted. Frequent item set mining techniques were applied to identify drugs co-prescription patterns. All the results were stratified by sex and age.

RESULTS

42.3% of men and 18.8% of women in the cohort received, at least, three prescriptions of a CVD preventive treatment in 2014. The most prescribed CVD treatment were antihypertensives (men: 28.2%, women 9.2%). The most frequent association observed among CVD preventive treatment was agents acting on the renin-angiotensin system and lipid-lowering drugs (5.1% of treated subjects). Co-prescription increased with age, especially after 50 years old, both in frequency and number of associations, and was higher in men. Regarding the association between CVD preventive treatments and other drugs, the most frequent pattern observed was lipid-lowering drugs and drugs used for acid related disorders (4.2% of treated subjects).

CONCLUSIONS

There is an important number of co-prescription patterns that involve CVD preventive treatments. These patterns increase with age and are more frequent in men. Mining techniques are a useful tool to identify pharmacological patterns that are not evident in the individual clinical practice, in order to improve drug prescription appropriateness.