Open AccessUsing Big Data to Assess Prescribing Patterns in Greece: The Case of Chronic Obstructive Pulmonary Disease
Author(s) -
Kyriakos Souliotis,
Chara Kani,
Manto Papageorgiou,
Dimitrios Lionis,
Konstantinos Gourgoulianis
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0154960
Subject(s) - copd , medicine , lama , medical prescription , logistic regression , pulmonary disease , disease , retrospective cohort study , descriptive statistics , pediatrics , emergency medicine , physical therapy , pharmacology , statistics , mathematics
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.