Factors of Hyperlipidemia Medication Adherence in a Nationwide Health Plan

Over 800,000 Americans die from cardiovascular disease (CVD) every year. Approximately 75% of fatal cardiac events are due to heart attack (acute myocardial infarction [AMI]) and stroke (cerebrovascular accident [CVA]).¹ Those who survive these events have a reduction in life expectancy of up to 15 years² and quality of life of nearly 50%.^3-5 The direct and indirect societal costs attributable to CVD exceed $475 billion annually.¹

A substantial body of clinical research supports lipid-lowering therapies (LLTs) as the primary therapeutic modality for reducing the risk of cardiovascular outcomes. Statins are the primary treatment modality and may confer lipid reductions of 10% to 60%.⁶ In the primary prevention of CVD, lipid reductions with low to medium potency statins have been shown to reduce the incidence of fatal and nonfatal cardiovascular outcomes signifi cantly (by 30% to 40%).^7,8 High potency statins may deliver a larger reduction in the risk of AMI and CVA (36% to 48%).⁹ Depending on patient need, statins, as well as fibric acid derivatives, bile acid sequestrants, niacin preparations, cholesterol absorption inhibitors, and free fatty acid products, can be individualized to help meet clinical, economic, and humanistic goals.⁶

There are significant clinical data demonstrating the effi cacy of LLT in CVD; however, translating the benefi ts from clinical trials into realworld outcomes is hampered, in part, by low medication adherence. Clinical trials demonstrate that adequate medication adherence over 5 years is necessary to reduce the negative clinical outcomes associated with CVD.^7,8 However, in clinical trials for LLT, full medication adherence is achieved through treatment oversight using clinical staff or by incorporating inclusion criteria that preselect patients on the basis of demonstrated medication adherence.¹⁰

Real-world adherence with LLT does not typically achieve the levels observed in clinical trials. In a study of 34,501 Medicaid patients, medication adherence with LLT dropped from 45% to 36% 3 months after LLT initiation and 79% to 56% 6 months after initiation.¹¹ Retrospective observational studies have found that women,^11,12 nonwhite race, usage of a Medicaid plan (odds ratio [OR]: 1.60), and age >75 years were associated with medication nonadherence.¹³ Clinically, patients with depression and dementia,¹³ a hospitalization in the year prior to the start of LLT,¹¹ or treatment with anxiolytics¹⁴ were associated with nonadherence. Treatment attributes including higher daily doses of LLT¹⁵ and medication switching reduced medication adherence.¹² Across studies, signifi cant heterogeneity exists in the patient populations evaluated, model variables included, definitions of medication adherence, and reporting.

The purpose of this study was to study factors associated with nonadherence in a nationally representative sample of patients receiving LLT for dyslipidemia using several new factors not included in previous studies. This study described characteristics of adherent and nonadherent patients; identifi ed factors with signifi cant impact on nonadherence; and suggested strategies to operationalize these results.

METHODS

Data

Data for this study were derived from paid pharmacy and medical claims and serum lipid laboratory data from a commercial health plan with members in 14 states from 4 regions of the United States. Data covered January 1, 2006, to April 30, 2009. Patient inclusion criteria included: receipt of LLT (“index drug”) between May 1, 2007, and April 30, 2008; 1-year continuous eligibility before and after the date of index drug receipt (“index date”); and a 1-year period without an LLT claim prior to receipt of the index LLT. Medicare and Medicaid enrollees were excluded.

Pharmacy claims included demographic and pharmacy utilization information such as medications, costs, quantities, and days of supply. Medical claims captured International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9- CM) codes and their respective diagnosis dates. Serum lipid values were retrieved for a sub-sample of patients for whom laboratory data were available. Data were de-identified and the study was approved by the Institutional Review Board at The University of Southern California.

Unit of Analysis

The unit of analysis was the patient’s first observed episode of LLT. Each patient’s pharmacy, medical claims, and laboratory data (where available) were summarized into 1 patient-level claims data set with multiple summary variables based on the index date of first LLT. The index drug was the key variable from which adherence estimates were derived.

Percentage of days covered (PDC) was used to estimate medication adherence. PDC was defi ned as the days' supply of LLT dispensed in the fi rst year following the index date divided by 365 days, multiplied by 100. The days’ supply of LLT was calculated as the total amount of medication provided divided by the frequency of administration (60 tablets, dosed twice daily equals a 30-day supply). PDC offers the advantage of measuring both medication adherence and persistence,¹⁶ both of which are important aspects of disease control in dyslipidemia. From a health plan perspective, the fixed observation period (1 year) used in PDC calculations aligns with a typical member enrollment period and payer decision-making timelines. PDC <80% was used as the cutoff for nonadherence with LLT and was the primary outcome variable.

Predictors of Suboptimal Adherence

Potential predictors of nonadherence included patient demographics; dichotomous variables based on selected ICD-9-CM codes; and variables capturing pharmacy and healthcare provider utilization in the year before the receipt of the index drug. Characteristics of the index drug such as copayment level and therapeutic class were also used as predictive covariates. Prior adherent behavior was defi ned as the ratio of total number of prescriptions filled and refi lled to the total number of unique medications used. A sub-analysis of patients with laboratory data was also performed. Evaluated here were the predictive value of baseline low-density lipoprotein (LDL) values; unique laboratory visits; and elapsed time between the most recent LDL laboratory and index date on nonadherence. This analysis was also meant to act as a sensitivity analysis to test the robustness of the full primary model.

Statistical Methods