BACKGROUND: Long-term utilization of prescription drugs for chronic conditions such as hypertension and/or hypercholesterolemia is a reality for millions of individuals, yet therapies may be discontinued before they can exert their beneficial effect. Several studies have measured the mean duration of therapy (ie, persistence) using administrative health databases. However, the terminology and methodology used for measuring persistence varied across studies, making it difficult to compare persistence rates. OBJECTIVES: The objectives of this study were to identify currently used measures of persistence and to propose a standard operational definition for use in administrative database analyses of drug utilization. METHODS: MEDLINE was searched for English-language articles published between January 1997 and June 2005 that quantified the concepts of persistence, adherence, compliance, or continuity with statin or antihypertensive therapy using administrative prescription claims databases. The conceptual and operational definitions of persistence used in the identified studies were categorized and applied to prescription-refill data for a hypothetical patient to compare the durations of persistence resulting from each method. RESULTS: Thirty-one articles were identified and reviewed. Few of the studies explicitly stated the conceptual definition of persistence used. Five methods of measuring persistence were identified: anniversary models, minimum-refills models, refill-sequence models, proportion-of-days-covered models, and hybrid models. When these models were applied to data for the hypothetical patient, total persistence with drug therapy ranged from 7 days to >1 year. CONCLUSIONS: There continue to be inconsistencies in the definition of persistence and the methods by which it is measured. A standard operational definition of persistence should be 2-dimensional, quantifying not only the total duration of therapy, but also the intensity of medication-taking within this interval.
BACKGROUND: Long-term utilization of prescription drugs for chronic conditions such as hypertension and/or hypercholesterolemia is a reality for millions of individuals, yet therapies may be discontinued before they can exert their beneficial effect. Several studies have measured the mean duration of therapy (ie, persistence) using administrative health databases. However, the terminology and methodology used for measuring persistence varied across studies, making it difficult to compare persistence rates. OBJECTIVES: The objectives of this study were to identify currently used measures of persistence and to propose a standard operational definition for use in administrative database analyses of drug utilization. METHODS: MEDLINE was searched for English-language articles published between January 1997 and June 2005 that quantified the concepts of persistence, adherence, compliance, or continuity with statin or antihypertensive therapy using administrative prescription claims databases. The conceptual and operational definitions of persistence used in the identified studies were categorized and applied to prescription-refill data for a hypothetical patient to compare the durations of persistence resulting from each method. RESULTS: Thirty-one articles were identified and reviewed. Few of the studies explicitly stated the conceptual definition of persistence used. Five methods of measuring persistence were identified: anniversary models, minimum-refills models, refill-sequence models, proportion-of-days-covered models, and hybrid models. When these models were applied to data for the hypothetical patient, total persistence with drug therapy ranged from 7 days to >1 year. CONCLUSIONS: There continue to be inconsistencies in the definition of persistence and the methods by which it is measured. A standard operational definition of persistence should be 2-dimensional, quantifying not only the total duration of therapy, but also the intensity of medication-taking within this interval.
Authors: Kensaku Kawamoto; Nancy M Allen LaPointe; Garry M Silvey; Kevin J Anstrom; Eric L Eisenstein; David F Lobach Journal: AMIA Annu Symp Proc Date: 2007-10-11
Authors: Devin M Mann; Nicole L Glazer; Michael Winter; Michael K Paasche-Orlow; Paul Muntner; Daichi Shimbo; William G Adams; Nancy R Kressin; Yuqing Zhang; Hyon Choi; Howard Cabral Journal: Am J Cardiol Date: 2013-02-20 Impact factor: 2.778