COMPARISON OF TRADITIONAL STATIN ADHERENCE MEASUREMENT WITH AN ENHANCED METHOD ALLOWING FOR MORE INCLUSIVE PATIENT MEASUREMENT
Author(s)
Jiang JZ*;Taitel M;Rudkin K, Fensterheim L Walgreen Co., Deerfield, IL, USA
Presentation Documents
OBJECTIVES: The methodology used to estimate medication adherence typically identifies patients with sold scripts during a specified index period. We propose a new method for calculating medication adherence that expands the patient population by including patients who filled medications and those who did not fill medication, but were expected to fill or had available medication during the index period. METHODS: During the index period of January 2011, patients filling, expected to fill, or who had statin medication on hand from a national retail pharmacy were included in the study. 12-month adherence metrics were calculated using the traditional method as well as the enhanced method using proportion of days covered (PDC). Patients were also segmented by refill behaviors such as new, returning, late, and continuing therapy and expected non-fillers. RESULTS: We identified 2,278,751 statin patients using the traditional method. The enhanced method identified 556,525 additional expected non-filler patients and 815,775 patients with available medication. Of the additional patients from the enhanced method, 67% eventually refilled their prescriptions in the subsequent 2 months. The enhanced method had an overall 12-month adherence of 0.693 compared to 0.733 for the traditional method. PDCs ranged from (0.420 - 0.794) depending on patient segment. These results are from a single pharmacy chain. Patients switching pharmacies will not be fully captured in these results. CONCLUSIONS: This enhanced method for measuring adherence identifies a more complete patient population of those at risk for hyperlipidemia because it accounts for all patients during the index period. Although the additional patients could be included using the traditional method within a 3-month index period, the new method captures all patients who are on therapy during a shorter index period. This enhanced method allows for quicker analysis to support interventions that improve patient’s adherence.
Conference/Value in Health Info
2013-05, ISPOR 2013, New Orleans, LA, USA
Value in Health, Vol. 16, No. 3 (May 2013)
Code
PRM9
Topic
Methodological & Statistical Research
Topic Subcategory
Confounding, Selection Bias Correction, Causal Inference
Disease
Cardiovascular Disorders