Author Affiliations: Division of Pharmacoepidemiology & Clinical Pharmacology, Faculty of Science, Utrecht Institute for Pharmaceutical Sciences, Utrecht University (Drs Geers, Bouvy, and Heerdink), and Division of Laboratory and Pharmacy, Department of Clinical Pharmacy, University Medical Center Utrecht, (Dr Heerdink), Utrecht, the Netherlands.
In their study on the implications of therapeutic complexity on adherence to cardiovascular medications, Choudhry et al1 describe predictors that are associated with poor adherence. They suggest that a number of these predictors could also be aimed at improving adherence, including reducing copayments, reducing the frequency with which prescriptions need to be filled, and creating a “pharmacy home” or a single pharmacy at which a patient refills his or her prescriptions.1,2 In the Netherlands, virtually all of these recommendations are implemented. In the Dutch health care system, larger supplies with a maximum of 90 days may be prescribed; no copayment with long-term medication exists; virtually all patients use a single pharmacy; all prescription medication is captured by the database; and hardly any mail-order pharmacies are present.3
We investigated whether in the Dutch situation adherence would be better, and whether a similar association with therapeutic complexity as found by Choudhry et al1 would be seen. From the PHARMO database we selected a sample of patients who initiated statin therapy between January 1 and December 31, 2004, and investigated whether therapeutic complexity predicted nonpersistence and poor drug-taking compliance after 12 months of follow-up.4 A patient was considered nonpersistent if a continuous gap of 60 days or more was present, and a patient had poor compliance if the Continuous Measure of Medication Acquisition (CMA) was lower than 80%.5 We used binary logistic regression to calculate the odds ratios for either nonpersistence or poor compliance. We investigated the following variables, calculated in the year previous to new statin use: (1) number of pharmacy visits, (2) number of medications filled, (3) number of long-term medication classes, (4) number of single medication dispensings (ie, single pharmacy pick-ups like an antibiotic course), (5) refill consolidation, (6) number of dose changes within each drug class, (7) number of prescribing physicians, and (8) number of switches within each drug class (eg, enalapril to ramipril). We included 6614 new statin users and identified 4189 statin users (63%) with a 60-day continuous gap during follow-up. Of the remaining 2425 continuous statin users, 111 (5%) had a CMA lower than 80%. The odds ratios and mean values for each investigated variable are presented in the Table for both persistence and compliance.
We observed a statistical significant correlation between therapeutic complexity and nonpersistence for the number of visits, number of fills, number of single dispensings, number of prescribing physicians, and total number of switches within each drug class. However, odds ratios approached 1, indicating a low predictive value. For compliance, only the number of single dispensings reached statistical significance, again with a very poor predictive value.
We were able to also link therapeutic complexity to both nonpersistence and poor compliance in the Dutch health care system, but odds ratios were too low to be clinically meaningful. We agree with Choudhry and coworkers1 that therapeutic complexity should be reduced, but we believe differences in health care systems have a much larger impact on both (non)persistence and (poor) compliance because we could not identify any clinical meaningful relation between therapeutic complexity and adherence. Predicting medication adherence remains an important challenge.6
Correspondence: Dr Heerdink, Division of Pharmacoepidemiology & Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, PO Box 80 082, 3508 TB Utrecht, the Netherlands (firstname.lastname@example.org).
Author Contributions:Study concept and design: Geers, Bouvy, and Heerdink. Acquisition of data: Geers and Heerdink. Analysis and interpretation of data: Geers, Bouvy, and Heerdink. Drafting of the manuscript: Geers and Heerdink. Critical revision of the manuscript for important intellectual content: Geers, Bouvy, and Heerdink. Statistical analysis: Geers and Heerdink. Administrative, technical, and material support: Geers. Study supervision: Bouvy and Heerdink.
Financial Disclosure: None reported.
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