Using pharmacy claims data to study adherence to glaucoma medications: methodology and findings of the Glaucoma Adherence and Persistency Study (GAPS)
- PMID: 17962457
- DOI: 10.1167/iovs.07-0290
Using pharmacy claims data to study adherence to glaucoma medications: methodology and findings of the Glaucoma Adherence and Persistency Study (GAPS)
Abstract
Purpose: To develop methods for investigating adherence to glaucoma medications by using a modified claims data-based measure of adherence, validation by chart review, and patient and physician interviews.
Methods: Data from administrative claims of 13,956 subjects receiving an initial glaucoma medication, and data from overlapping samples of 300 patients' charts, 300 interviews of patients, and 103 interviews of physicians were analyzed and compared.
Results: The mean medication possession ratio (MPR) was 0.64 (median 0.57) for the 13,956 subjects. Although 59% potentially had an ocular hypotensive agent at 12 months, only 10% had such medication available continuously. Chart review revealed that 31% of subjects "new to therapy" in claims data had actually been previously treated; and that 90% of the 17% who had medication added to initial monotherapy were misclassified by claims-based algorithms as medication switches or no change. Twenty percent of surveyed patients received samples on a regular basis and had lower MPR than those who did not (P < 0.05).
Conclusions: Large pharmacy databases offer insight into medication usage but are vulnerable to errors from sampling (since patients who receive samples will be considered to have poor adherence), misidentification of newly treated patients, and misclassification of added versus switched medications. That a large proportion of patients stop and restart medications makes MPR a robust measure of adherence over time that reflects the resumption of medication after a gap in adherence. The data confirm that adherence to treatment with glaucoma medications is poor, similar to adherence in patients with other chronic diseases.
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