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The American Journal of Managed Care July 2009
Adherence to Osteoporosis Medications After Patient and Physician Brief Education: Post Hoc Analysis of a Randomized Controlled Trial
Aimee Der-Huey Shu, MD; Margaret R. Stedman, MPH; Jennifer M. Polinski, MPH, MS; Saira A. Jan, MS, PharmD; Minal Patel, MD, MPH; Colleen Truppo, RN, MBA; Laura Breiner, RN, BSN; Ya-ting Chen, PhD; Thomas W. Weiss, DrPH; and Daniel H. Solomon, MD, MPH
Lipid Profile Changes Associated With Changing Available Formulary Statins: Removing Higher Potency Agents
Daniel S. Longyhore, PharmD; Casey McNulty Stockton, PharmD; and Marie Roke Thomas, PhD
Automated Messaging to Improve Compliance With Diabetes Test Monitoring
Stephen F. Derose, MD, MS; Randall K. Nakahiro, PharmD; and Frederick H. Ziel, MD
Measuring Concurrent Adherence to Multiple Related Medications
Niteesh K. Choudhry, MD, PhD; William H. Shrank, MD, MSHS; Raisa L. Levin, MS; Joy L. Lee, BA; Saira A. Jan, MS, PharmD; M. Alan Brookhart, PhD; and Daniel H. Solomon, MD, MPH
Medicaid Beneficiaries With Congestive Heart Failure: Association of Medication Adherence With Healthcare Use and Costs
Dominick Esposito, PhD; Ann D. Bagchi, PhD; James M. Verdier, JD; Deo S. Bencio, BS; and Myoung S. Kim, PhD
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Medication Adherence and Use of Generic Drug Therapies
Becky A. Briesacher, PhD; Susan E. Andrade, ScD; Hassan Fouayzi, MS; and K. Arnold Chan, MD
Impact of Workplace Health Services on Adherence to Chronic Medications
Bruce W. Sherman, MD; Sharon Glave Frazee, PhD; Raymond J. Fabius, MD, CPE; Rochelle A. Broome, MD; James R. Manfred, RPh; and Jeffery C. Davis, MBA

Medication Adherence and Use of Generic Drug Therapies

Becky A. Briesacher, PhD; Susan E. Andrade, ScD; Hassan Fouayzi, MS; and K. Arnold Chan, MD

Generic prescribing was associated with improved medication adherence in 2 of 5 study conditions, but $0 copayments were associated with improved adherence across all conditions.

Objective: To assess whether lower copayments charged for generic drugs explain the improved drug adherence associated with use of generics.

Methods: We analyzed 2001-2004 healthcare claims data from 45 large employers. Study subjects were age ≥18 years, had 1 or more of 5 study conditions (hypercholesterolemia, hypertension, hypothyroidism, seizure disorders, type 2 diabetes), and new use of generic-only or brand-only drug therapy for that condition. We measured adherence as the medication possession ratio (MPR), and adequate adherence as MPR ≥80%. Logistic regressions were conducted to assess adequate adherence, adjusting for copayments.

Results: We identified 327,629 new users of drug therapy. The proportion starting generic therapies ranged from 9% (hypothyroidism) to 45% (hypertension). After 1 year, 66.2% of individuals with hypothyroidism achieved an MPR ≥80% compared with 53.4% with hypertension, 53.2% with hypercholesterolemia, 52.0% with diabetes, and 42.2% with seizure disorders. Generics were associated with greater adherence than brands in patients with hypercholesterolemia or diabetes (P <.05). Lower adherence was seen in patients with ypertension or hypothyroidism (P <.05). There was no difference in seizure disorders. The likelihood of achieving an MPR ≥80% with $0 copayments compared with $1 to $9 ranged from an adjusted odds ratio (AOR) of 1.32 for seizure disorders (95% confidence interval [CI] = 1.41, 1.43) to an AOR of 1.45 for hypothyroidism (95% CI = 1.43, 1.48).

Conclusion: Generic prescribing was associated with modestly improved adherence in 2 of 5 study conditions. Copayments of $0 were associated with improved adherence across all conditions.


(Am J Manag Care. 2009;15(7):450-456)

Analysis of healthcare claims data from 45 large employers showed that generic prescribing was associated with both increases and decreases in medication adherence as well as no effect, depending on the study condition (hypercholesterolemia, hypertension, hypothyroidism, seizure disorders, or type 2 diabetes).

  • Copayments of $0 were a more consistent predictor of increased adherence.
  • Cost-related nonadherence and associated negative consequences will likely increase if pharmacy benefits are constructed in such a way as to promote generics without consideration of copayments.
One of the best documented barriers to medication adherence is high out-of-pocket costs, even among individuals with prescription drug insurance.1 Numerous studies have found that increased drug copayments are associated with decreased use of prescription drugs, even for highly effective medications used to treat chronic conditions such as diabetes mellitus, hypertension, and hypercholesterolemia.2-5 As a consequence, it is generally assumed that any government or private health plan policy that reduces copayments will enhance medication adherence.

A current trend in pharmacy benefits is to require relatively small copayments for generic drugs while charging much higher copayments for brand drugs as part of tiered formulary plans. In 2007, employer plans charged, on average, $11 for generic drugs, $25 for preferred brand drugs, and $43 for nonpreferred brand drugs.6 The wide difference in copayments between generic and brand drugs is especially apparent in the Medicare Part D prescription drug plans, where enrollees pay $25 to $60 more for covered brand drugs compared with covered generic drugs.7 These types of tiered pharmacy benefits steer patients toward generics, which lowers total prescription drug cost but also decreases overall prescription drug use, including for essential therapies.2 Little is known about why prescription drug use decreases with the introduction of pharmacy benefits that offer incentives for using generics, but the reductions in prescription use are greater than those observed with uniform copayment increases across all brand and generic drugs.8 This suggests that the relationship between adherence and use of generics may encompass more factors than simply lower copayments. For instance, nonfinancial factors such as chronic disease burden and mood disorders have been found to influence cost-related nonadherence.1 In addition, research finds consistently that tiered copayments are not associated with lower out-of-pocket costs to individuals but rather with lower costs to the employers and health plans.8,9 Higher out-of-pocket costs are associated with decreased adherence.

Few previous studies explicitly evaluated the relationship between generic drugs and medication adherence, and those that did reported mixed findings. Furthermore, none to our knowledge explicitly examined the use of generics and medication adherence rates after accounting for the amount of copayments. Two studies of a plan’s switch to a genericonly formulary found significant reductions in the overall use of prescriptions, including decreases in the essential use of angiotensin-converting enzyme inhibitors and statins by patients with diabetes and coronary artery disease, and increases in self-reported financial burden.10,11 Conversely, a recent study of a tiered pharmacy benefit found adherence was 12.6% higher for patients whose therapy was initiated with generic medications.12 These studies may not be directly comparable, though, because switching to generics may be a behavior distinct from initiating generics. Nevertheless, none of these analyses accounted for the independent role of copayments, or evaluated whether their findings remained constant across different medical conditions. Our prior research revealed variation in adherence across different medical conditions that might have been influenced by differential access to generic drug formulations.13 The objectives of this study were to explicitly test the relationship between use of generics and adherence after adjusting for copayments and to see whether the relationship held across different medical conditions.

METHODS

Study Population and Data Sources

The study data were drawn from the 2001-2004 Market Scan Research databases (MEDSTAT, Ann Arbor, MI). These are secondary data sets of employer-sponsored medical care claims, prescription drug claims, and healthcare encounter data from approximately 45 large US employers and public organizations. The data are based on a nationwide sample but are limited in generalizability for certain groups, particularly for employees and their dependents of small and medium firms and the unemployed. Each year of the data set contains medical care information on 3 million to 6 million individuals, and scientific studies based on this data source have been reported in more than 40 peer-reviewed articles.14 The encounter files contain age, sex, geographic residence, and eligibility information. The prescription claims file includes the national drug codes, date of purchase, quantity dispensed, days supply, and expenditure information for each dispensing. The medical claims file contains payment information, diagnoses, procedure codes, and type of provider. For this analysis, we linked the annual files to create a longitudinal panel of continuous observations for each subject.

The study sample included individuals who were age 18 years or older and had a diagnosis of 1 or more of 5 conditions: hypercholesterolemia, hypertension, hypothyroidism, seizure disorders, and type 2 diabetes. Details of the sample selection are described in a prior study.13 Briefly these conditions were selected because they are common and treated with chronic drug therapy that is available in generic and brand formulations. (For details about the therapeutic drug classes and diagnostic codes, see the eAppendix Table, www.ajmc.com.) In addition, the study subjects must have initiated new drug therapy for that condition between January 1, 2002, and December 31, 2003. Our analysis used a new user study design to compare the patient groups at the same point in time relative to the initiation of therapy.15 New drug therapy was defined as a dispensing of a study drug for that condition after at least 1 year of no dispensing of a study drug for that condition. Individuals were excluded if they had missing values or a value of zero or less for the quantity dispensed of the newly initiated study medication (n = 11,972), had less than 1 year of follow-up observation after the first dispensing of the study medication (n = 588,278), or used both generic and branded therapy during the first year of therapy (n = 16,909).

Medication Adherence

We used the medication possession ratio (MPR) to measure prescription drug adherence.16 The MPR is the days supply of medication dispensed during the follow-up year divided by the number of days in the year. A recent review of adherence measures shows MPR is a reliable measure of adherence.17 Our calculation included dispensings for the initial study drug therapy as well as for all other study drug therapies for that condition. Overlaps in the dispensing days of different generic drug therapies were eliminated, under the assumption that leftover supplies from earlier refills were discarded to begin the newer medication (eg, a change in therapy). Overlaps in the dispensing days of the same generic drug therapies were summed, under the assumption that earlier refills still were taken by the patient as part of the same regimen (eg, an early refill). The value of the days supply was truncated if the supply extended beyond the time period of observation. In addition, MPR values >100% were truncated to a value of 100%. Overadherence is difficult to interpret as we were unable to differentiate between inappropriate behaviors (eg, overuse, early refills) and appropriate behaviors (eg,

changes in drug regimens, combination therapies, multiple dispensings to achieve a specific dose). Adequate adherence was defined as MPR ≥80%, although sensitivity analyses were conducted at MPR ≥60%.

Other Measures

Generic formulations of the study drugs were identified using a generic product indicator variable for each drug in each year of the database to flag generic preparations. The study copayment was identified as the modal value of all copayments provided for any study medications dispensed during the year, as used previously.18,19 The mean copayment (standard deviation) for each condition was as follows: seizure disorders $15.10 ($13.50 SD); hypothyroidism $9.90 ($7.70 SD); type 2 diabetes $13.50 ($12.90 SD); hypercholesterolemia $18.80 ($15.50 SD); and hypertension $13.10 ($12.50 SD). Based on the modal copayment distribution, individuals were categorized as having copayment levels of $0, low ($1-$9), medium ($10-$29), and high ($30+). In addition, we evaluated the effect of prescription drug adherence with the following covariates: age, sex, plan type, geographic residence, and comorbidity level. Comorbidity level was generated using the Diagnostic Cost Group Hierarchical Condition Category (DCG/HCC) system (DxCG, Boston, MA).20,21 The DCG/HCC risk adjuster creates a single score for each individual based on the diagnosis fields of claims records. Each individual was assigned an index date based on the first dispensing of the newly initiated drug therapy. Data from the year before the index date were used to calculate the comorbidity risk score. Data from the year after the index date were used to measure adherence and copayment level.

Statistical Analysis

Bivariate statistics were used to assess the unadjusted means and frequency distributions of the study variables. Logistic regression models were used to estimate the associations (adjusted odds ratios [AORs] and 95% confidence intervals [CIs]) between adequate adherence and generic medication use for each disease state. Multicollinearity was assessed using the variance inflation factor (VIF) and the general rule of thumb that a VIF value of more than 10 indicates severe multicollinearity. None of the VIF values for our copayment variables or generic variables in any of the models exceeded the value of 4, and most were less than 2.5.

RESULTS

We identified 327,629 individuals with 1 of 5 chronic medical conditions and newly initiated drug therapy for that condition (Table 1). The average age of the subjects was 57 years, 53% were female, and the mean comorbidity score was 0.56 ± 0.60. Approximately 40% of the subjects lived in the southern part of the United States, followed by 31% in the north-central region. Preferred provider organizations were the most common type of health coverage (38%), followed by comprehensive plans (31%) and point-of-service plans (21%). About 48% of the individuals had hypercholesterolemia, 38% had hypertension, 13% had type 2 diabetes, 9% had hypothyroidism, and 1% had seizure disorders.

Table 2 shows a distribution of individuals by use of generics and copayment levels for study medication. The proportion who initiated therapy with generic drugs was 6% for hypercholesterolemia, 9% for hypothyroidism, 27% for seizure disorders, 37% for type 2 diabetes, and 45% for hypertension. In general, most generic users had copayments within the range of $1 to $9, comprising 58% to 74% of these populations in each disease group. However, brand users had a wider range of copayments, which varied by disease. For instance, copayments of $30 or more were paid by 53% of brand users who had hypercholesterolemia, compared with 12% of brand users who had hypothyroidism. Interestingly, brand users and generic users were equally likely to pay $0 copayments, except in 1 case: 12% of brand users who had  hypercholesterolemia paid $0 copayments compared with 6% of generic users who had hypercholesterolemia.

 
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