Data from: Using big data to assess prescribing patterns in Greece: the case of chronic obstructive pulmonary disease

Introduction: Chronic Obstructive Pulmonary Disease (COPD) is one of the
top leading causes of death and disability, and its management is focused
on reducing risk factors, relieving symptoms, and preventing
exacerbations. The study aim was to describe COPD prescribing patterns in
Greece by using existing health administrative data for outpatients.
Methods: This is a retrospective cross-sectional study based on
prescriptions collected by the largest social insurance fund, during the
first and last trimester of 2012. Selection criteria were the prescription
of specific active substances and a COPD diagnosis. Extracted information
included active substance, strength, pharmaceutical form and number of
packages prescribed, diagnosis, time of dispensing, as well as
insurees' age, gender, percentage of co-payment and social security
unique number. Statistical analysis included descriptive statistics and
logistic regression. Results: 174,357 patients received medicines for COPD
during the study period. Patients were almost equally distributed between
male and female, and age above 55 years was strongly correlated with COPD.
Most patients received a long-acting beta agonist plus inhaled
corticosteroid combination (LABA +ICS), followed by long-acting muscarinic
agonist (LAMA). 63% patients belonging in the 35-54 age received LABA+ICS.
LAMA was prescribed more frequently among males and was strongly
correlated with COPD. Conclusion: The study provides big data analysis of
Greek COPD prescribing patterns. It highlights the need for appropriate
COPD classification in primary care illustrating the role of electronic
prescribing in ensuring appropriate prescribing. Moreover, it indicates
possible gender differences in treatment response or disease severity, and
the impact of statutory co-payments on prescribing.