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Adherence to Statins, Subsequent Healthcare Costs, and Cardiovascular Hospitalizations

      Statins are the primary agents used to decrease low-density lipoprotein cholesterol. Although adherence to statins improves the clinical outcomes, the affect of statin adherence on healthcare costs has not been well studied. To examine the relation among statin adherence, subsequent hospitalizations, and healthcare costs, we conducted a retrospective cohort study of 381,422 patients, aged 18 to 61 years, using an integrated pharmacy and medical claims database. We measured adherence using the medication possession ratio (MPR) for 12 months and the healthcare costs and cardiovascular disease-related hospitalizations during the subsequent 18 months. Of those studied, 258,013 (67.6%) were adherent (MPR ≥80%), 65,795 (17.3%) had an MPR of 60% to 79%, and 57,614 (15.1%) had an MPR of <60%. The adjusted all-cause total healthcare costs were lowest in the adherent group at $10,198 ± $39.4 (mean ± SE) versus $10,609 ± $77.7 (p <0.001) for an MPR of 60% to 79%, and $11,102 ± $84.3 (p <0.001) for an MPR of <60%. The adherent group had greater statin costs at $838 ± $1.0 versus $664 ± $2.0 (p <0.001) and $488 ± $2.2 (p <0.001). When evaluated by 5 levels of MPR, 0% to 59% and increments of 10% >60%, the adjusted total healthcare costs were lowest for the MPR 90% to 100% group and significantly greater statistically (p <0.001) for each lower level of adherence. Compared to the statin-adherent patients, cardiovascular disease-related hospitalizations were more likely for the patients with an MPR of 60% to 79% (odds ratio 1.12, 95% confidence interval 1.08 to 1.16) and an MPR of 0% to 59% (odds ratio 1.26, 95% confidence interval 1.21 to 1.31). In conclusion, statin adherence is associated with reductions in subsequent total healthcare costs and cardiovascular disease-related hospitalizations.
      Although adherence to statins has been shown to affect clinical outcomes, limited data are available evaluating the healthcare costs associated with better adherence.
      • Ho P.M.
      • Bryson C.L.
      • Rumsfeld J.S.
      Medication adherence—its importance in cardiovascular outcomes.
      The objective of the present study was to evaluate adherence to statins for 12 months to determine the affect on healthcare costs and cardiovascular-related hospitalizations in the subsequent 18 months.

      Methods

      The source of data was the Medco National Integrated database, which contains 30 months of medical and pharmacy claims data for approximately 13 million patients enrolled in >450 different health plans, including fee-for-service, preferred provider, and managed care plans sponsored by insurance companies, employers, and government organizations. The medical claims contain all inpatient, outpatient, nursing home, laboratory, and diagnostic testing claims the health plan has received. The laboratory tests and medical care paid out of pocket or through Medicare are not included in the database.
      The study consisted of a cohort of all patients aged 18 to 61 years as of January 1, 2007, with at least one pharmacy claim for a statin medication from January 1, 2008 to June 30, 2008 and a second claim within 12 months before the last claim seen before June 30, 2008. The statins included in the present analysis are listed in Figure 1. We excluded patients with claims for malignant neoplasms (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] codes 140* to 172* and 174* to 209*), except for those with nonmelanoma skin cancer, or human immunodeficiency virus infection (ICD-9-CM codes 042 and V08), because these diseases can be associated with overwhelming pharmacy and medical costs, independent of the adherence to statins. In addition, we limited our analysis to patients with continuous eligibility for pharmacy and medical benefits from January 1, 2007 through June 30, 2009. The baseline year was January 1, 2007 to December 31, 2007, and the 18-month follow-up was January 1, 2008 to June 30, 2009 (Figure 1). The selection criteria were used to create a de-identified data set that was further analyzed for the present study.
      Figure thumbnail gr1
      Figure 1Study timeline for data on adherence to statins. X indicates ≥1 claim in first 6 months of follow-up period and ≥1 other claim in 365 days before last claim in first 6 months of 2008. aAdherence to statin based on interval between last claim in first 6 months of 2008 and first claim in previous 365 days. bStatin drug list (all strengths): atorvastatin; fluvastatin; lovastatin; pravastatin; rosuvastatin; simvastatin; and simvastatin/ezetimibe. cICD-9-CM co-morbidities: coronary artery disease (codes 410*, 411*, 412*, 413*, 414*, 996.03); diabetes mellitus (codes 249*, 250*); hypertension (codes 401* to 405*); stroke (430* to 438*; 997.02); peripheral artery disease (code 443.9); heart failure (codes 402.11, 402.91, 404.11, 404.13, 404.91, 404.93, 428*), and depression (codes 296.2*, 296.3*, 298.0, 300.4, 309, 309.1, 309.28, and 311). dICD-9-CM for CVD-related hospitalizations: hypertension (codes 401* to 405*); coronary artery disease (codes 410*, 411*, 412*, 413*, 414*, 996.03); diabetes mellitus (codes 249*, 250*); hypercholesterolemia (code 272*); stroke (codes 430* to 438*, 997.02); peripheral artery disease (code 443.9); and atherosclerosis (code 440*, 444*). eTotal all cause healthcare costs.
      The adherence to statins was estimated by calculating the medication possession ratio (MPR) or the ratio of total days of medication supplied to the total days within a set period. The MPR is the accepted standard for the evaluation of adherence using retrospective data, because it is easy to calculate and performs as well as other claims-based estimates.
      • Ho P.M.
      • Bryson C.L.
      • Rumsfeld J.S.
      Medication adherence—its importance in cardiovascular outcomes.
      • Hudson M.
      • Rhame E.
      • Richard H.
      • Pilote L.
      Comparison of measures of medication persistency using prescription drug database.
      • Choo P.W.
      • Rand C.S.
      • Inui T.S.
      • Lee M.L.
      • Cain E.
      • Cordeiro-Breault M.
      • Canning C.
      • Platt R.
      Validation of patient reports, automated pharmacy records, and pill counts with electronic monitoring of adherence to antihypertensive therapy.
      MPR was calculated according to the total number of days between the dates of the last filling of a statin prescription in the first 6 months of 2008 and the first filling of a statin prescription in the 365 days before the last filling. If the patient had received one or more statins during the 365-day adherence measurement period, the days' supply for all statins were included in the calculation. The MPR was capped at 100%, because it was unlikely that patients would have used the statins at greater than the prescribed frequency.
      For the primary evaluation, we used the MPR to classify the patients into 3 adherence categories: adherent (MPR ≥80%), moderate adherence (MPR 60% to 79%), and low adherence (MPR <0% to 59%). Previous data have recommended using the MPR as a dichotomous variable, with an MPR of 80% considered adherent. Although this proportion is somewhat arbitrary, it has been accepted as the cutoff for adherence in most studies of adherence.
      • Ho P.M.
      • Bryson C.L.
      • Rumsfeld J.S.
      Medication adherence—its importance in cardiovascular outcomes.
      We performed secondary analyses using 5 levels of adherence: MPR of 0% to 59%, 60% to 69%, 70% to 79%, 80% to 89%, and 90% to 100%.
      The number of all medications “on hand” was determined as of the last day of the baseline year. We evaluated the variables likely to be associated with adherence during the baseline period, including the proportion of statin prescriptions filled with generic statins; the proportion of the total statin days' supply filled by mail; and the patient co-payment for statins per month (i.e., the total amount patients paid for their statins, including the co-payment, deductible, and co-insurance per month).
      For each patient, we used the medical claims to determine the presence of one or more hospitalizations in the baseline year and follow-up period. We also used medical claims to identify specific co-morbidities using the ICD-9-CM diagnosis codes shown in Figure 1. The primary outcome was the identification of the total all-cause healthcare costs in the subsequent 18-month follow-up period, January 1, 2008 to June 30, 2009, among the low adherence, moderate adherence, and adherent groups. The total all-cause healthcare costs were calculated as the sum of all pharmacy and medical costs (including outpatient services, emergency department services, and hospitalizations) paid by the plan sponsor during the 18-month follow-up period and excluded patient co-payments and deductibles. Secondary analyses were conducted by further analyzing the cost of statins, the cost of medications other than statins, all-cause medical costs, and cardiovascular disease (CVD)-related medical costs. We evaluated the association between the adherence levels and the risk of one or more CVD-related hospitalizations during the 18-month follow-up period using ICD-9-CM codes in Figure 1.
      We compared the baseline demographic factors, co-morbidities, and medication factors between the adherent and nonadherent patients using the chi-square test for binary variables and the t test for continuous variables. Regression analyses were performed to assess the relation between the outcome variables and covariates. Logistic regression analysis was used to reveal the determinants of adherence to statins (defined as an MPR of ≥80%). The predictors included age, gender, co-morbidities, chronic disease score, out-of-pocket costs for medication, and the use of mail-order pharmacy. Logistic regression analysis was also performed for 2 additional models to evaluate the association among 3 levels of adherence and adherence as a continuous variable with clinical outcomes of CVD-related hospitalization, after adjusting for important baseline differences. To determine the average costs in the 18-month follow-up period for each level of adherence, we used generalized linear models and adjusted for baseline differences in age, gender, year 1 co-morbidities, the year 1 total number of medications, and the year 1 total healthcare costs. The least square mean of the costs were generated and compared among the 3 adherence groups. SAS, version 9.1 (SAS Institute, Cary, North Carolina), was used for all the statistical analyses, and 2-sided p values of <0.05 were considered statistically significant.

      Results

      Our analysis identified 381,422 patients who met the inclusion criteria. The patient demographics are listed in Table 1. The mean level of adherence in year 1 was 43.1% in the MPR <60% group, 71.3% in the 60% to 79% adherence group, and 94.5% in the MPR ≥80% adherent group.
      Table 1Patient characteristics stratified by statin adherence in year 1
      VariableAll PatientsAdherence Level
      Low (MPR 0–59%)Moderate (MPR 60–79%)Adherent (MPR 80–100%)p Value
      Adherent vs ModerateAdherent vs Low
      Patients381,422 (100%)57,614 (15.1%)65,795 (17.3%)258,013 (67.6%)<0.0001<0.0001
      Age (years)53.0 ± 6.7151.6 ± 7.3152.0 ± 7.0253.6 ± 6.41<0.0001<0.0001
       18–4444,886 (11.8%)9,772 (17.0%)9,882 (15.0%)25,232 (9.8%)<0.0001<0.0001
       45–54145,002 (38.0%)23,713 (41.2%)27,174 (41.3%)94,115 (36.5%)<0.0001<0.0001
       55–64191,534 (50.2%)24,129 (41.9%)28,739 (43.7%)138,666 (53.7%)<0.0001<0.0001
      Women158,044 (41.4%)25,836 (44.8%)27,071 (41.1%)105,137 (40.8%)0.065<0.0001
      Mean adherence (MPR)82.7 ± 20.2%43.1 ± 12.9%71.3 ± 5.9%94.5 ± 6.1%<0.0001<0.0001
      Co-morbidities
       Coronary artery disease57,811 (15.2%)7,725 (13.4%)9,111 (13.8%)40,975 (15.9%)<0.0001<0.0001
       Diabetes mellitus96,950 (25.4%)15,253 (26.5%)16,375 (24.9%)65,322 (25.3%)0.024<0.0001
       Hypertension198,661 (52.1%)28,587 (49.6%)32,587 (49.5%)137,487 (53.3%)<0.0001<0.0001
       Stroke12,893 (3.4%)1,848 (3.2%)2,093 (3.2%)8,952 (3.5%)<0.00010.002
       Peripheral artery disease4,574 (1.2%)693 (1.2%)780 (1.2%)3,101 (1.2%)0.7300.985
       Heart failure6,821 (1.8%)1,039 (1.8%)1,163 (1.8%)4,619 (1.8%)0.6960.830
       Depression32,623 (8.6%)5,113 (8.9%)5,918 (9.0%)21,592 (8.4%)<0.0001<0.0001
      Mean total medications3.4 ± 2.72.2 ± 2.32.9 ± 2.53.7 ± 2.7<0.0001<0.0001
      Mean generic statin use (%)35.6 ± 46.64%33.0 ± 45.52%34.5 ± 45.97%36.5 ± 47.03%<0.0001<0.0001
      Mean statins by mail (%)48.9 ± 48.00%27.3 ± 43.14%40.0 ± 46.81%56.0 ± 47.49%<0.0001<0.0001
      Mean statin co-pay ($/mo)$16.20 ± 14.58$19.32 ± 24.52$17.33 ± 12.55$15.22 ± 11.68<0.0001<0.0001
      ≥1 Hospitalizations28,875 (7.6%)4,495 (7.8%)4,976 (7.6%)19,404 (7.5%)0.7130.021
      ≥1 Emergency department visits54,304 (14.2%)9,508 (16.5%)10,023 (15.2%)34,773 (13.5%)<0.0001<0.0001
      Year 1 total healthcare costs$6,523 ± 15,499$5,630 ± 13,548$6,314 ± 18,999$6,776 ± 14,893<0.0001<0.0001
      Data are presented in ± SD.
      Overall, the most common co-morbidities were hypertension, coronary artery disease, and diabetes mellitus. Also, 8.6% of the patients had a history of depression. The adherent group was older, more likely to be men, and had a greater proportion of patients with an ICD-9-CM claims diagnosis of coronary artery disease, hypertension, or stroke. In addition, the adherent group had significantly more generic statin use, a lower statin co-payment, and greater mail order statin use. In the fully adjusted multivariate logistic regression analysis that modeled the predictors of adherence, the patients who received >80% of their statins by mail (odds ratio [OR] 2.16, 95% confidence interval [CI] 2.13 to 2.19) were older (OR 1.02 for each year, 95% CI 1.02 to 1.03) or had more total active medications available at the end of the baseline year (OR 1.27 for each additional medication, 95% CI 1.27 to 1.28) and were more likely to be adherent. In contrast, patients with an ICD-9-CM for depression (OR 0.82, 95% CI 0.80 to 0.84) or who had paid >$10/mo in co-payments for their statins were less likely to be adherent (OR 0.75, 95% CI 0.73 to 0.76).
      The adjusted all-cause total healthcare costs and medical costs were lowest and the statin costs were greatest in the adherent group (Table 2). The costs associated with the 5 levels of MPR from 0% to 59% and increments of 10% >60% are shown in Figure 2. In an additional analysis that evaluated the association between MPR as a continuous variable and healthcare costs, we found similar statistically significant associations between a greater MPR and lower medical and total healthcare costs. Adherent patients had adjusted CVD-related medical costs of $2,395 ± 20.5 SE compared to patients with moderate ($2,583 ± $40.4) and low ($2,689 ± $43.9) adherence (p <0.001). The CVD-related total healthcare costs were not significantly different statistically among the groups.
      Table 2Costs of care during 18 months of follow-up by level of adherence to statins in year 1*
      Year 1 MPRStatin Prescription CostsAll Other Prescription CostsAll-Cause Medical CostsCardiovascular Medical CostsAll-Cause Total Healthcare Costs
      Low adherence (MPR 0–59%; n = 57,614)$488 ± 2.2
      p <0.001;
      $2,906 ± 14.9
      p <0.001;
      $7,708 ± 81.9
      p <0.001;
      $2,689 ± 43.9
      p <0.001;
      $11,102 ± 84.3
      p <0.001;
      Moderate adherence (MPR 60–79%; n = 65,795)$664 ± 2.0
      p <0.001;
      $2,684 ± 13.7
      p = NS.
      $7,261 ± 75.5
      p <0.001;
      $2,583 ± 40.4
      p <0.001;
      $10,609 ± 77.7
      p <0.001;
      Adherent (80–100%; n = 258,013)$838 ± 1.0$2,651 ± 7.0$6,709 ± 38.3$2,395 ± 20.5$10,198 ± 39.4
      Data are presented as mean ± SE.
      p Values from comparisons with MPR 80–100% (adherent) group.
      *Adjusted for age, gender, coronary artery disease, diabetes, hypertension, stroke, peripheral arterial disease, congestive heart failure, depression, year 1 total healthcare costs, and number of medications.
      p <0.001;
      p = NS.
      Figure thumbnail gr2
      Figure 2Relation between year 1 adherence and subsequent healthcare costs at 18 months (adjusted for age, gender, coronary artery disease, diabetes, hypertension, stroke, peripheral artery disease, congestive heart failure, depression, year 1 total healthcare costs, and number of medications). ap < 0.001 versus MPR of 80% to 100%; bp < 0.01 versus MPR of 80% to 100%; cp = NS versus MPR of 80% to 100%.
      We identified 25,570 unique patients with CVD-related hospitalizations in the study cohort. When fully adjusted for the baseline characteristics, the odds of a CVD-related event were greater for patients with low and moderate adherence compared to those with high adherence (Table 3). The baseline characteristics that were predictors for CVD-related hospitalization included coronary artery disease (OR 4.22, 95% CI 4.09 to 4.34), diabetes (OR 1.51, 95% CI 1.47 to 1.56), hypertension (OR 1.16, 95% CI 1.13 to 1.20), stroke (OR 1.22, 95% CI 1.16 to 1.29), peripheral arterial disease (OR 1.50, 95% CI 1.39 to 1.63), and heart failure (OR 1.21, 95% CI 1.14 to 1.30), and depression (OR 1.50, 95% CI 1.44 to 1.56). When adherence was evaluated in logistic regression analysis as a continuous predictor, a 10% increase in the MPR was associated with a decreased risk of CVD-related hospitalizations (OR 0.95, 95% CI 0.95 to 0.96).
      Table 3Risk of CVD-related hospitalization in 18-month follow-up period
      Adherence Level Year 1Unique Patients (n)CVD-Related Hospitalization
      Gender/Age-Adjusted OR (95% CI)Fully adjusted
      Adjusted for age, gender, coronary artery disease, diabetes, hypertension, stroke, peripheral arterial disease, congestive heart failure, depression, year 1 hospitalization, year 1 emergency department visits, and number of medications in year 1.
      OR (95% CI)
      MPR 0–59% (n = 57,614)4,041 (7.01%)1.14
      p <0.05 compared to MPR 80–100%.
       (1.10–1.18)
      1.26
      p <0.05 compared to MPR 80–100%.
       (1.21–1.31)
      MPR 60–79% (n = 65,795)4,374 (6.65%)1.06
      p <0.05 compared to MPR 80–100%.
       (1.02–1.09)
      1.12
      p <0.05 compared to MPR 80–100%.
       (1.08–1.16)
      MPR 80–100% (n = 258,013)17,155 (6.65%)1 (referent)1 (referent)
      low asterisk Adjusted for age, gender, coronary artery disease, diabetes, hypertension, stroke, peripheral arterial disease, congestive heart failure, depression, year 1 hospitalization, year 1 emergency department visits, and number of medications in year 1.
      p <0.05 compared to MPR 80–100%.

      Discussion

      The objective of the present study was to evaluate whether adherence to statins for 12 months was associated with the subsequent healthcare costs and CVD-related hospitalizations. In the present large, national sample of insured patients receiving statins, we found approximately 1/3 of the 381,422 patients were nonadherent to statins in the baseline year and that nonadherence was associated with a $400 to $900 per patient greater total healthcare cost and increased likelihood of a CVD-related hospitalization in the subsequent 18 months. In the adherent group, greater statin drug costs were offset by the lower medical costs, leading to lower total healthcare costs. If we extrapolate these findings to the >24 million patients who receive statins in the United States,
      • Mann D.
      • Reynolds K.
      • et al.
      Trends in statin Use and low-density lipoprotein cholesterol Levels among US Adults: Impact of the 2001 National Cholesterol Education Program Guidelines.
      increasing adherence for the estimated 8 million nonadherent patients would have the potential to improve patient outcomes and save the healthcare system >3 billion dollars annually.
      Our findings of statin nonadherence and the association with worse outcomes are consistent with previous research. Jackevicius et al
      • Jackevicius C.A.
      • Mamdani M.
      • Tu J.V.
      Adherence with statin therapy in elderly patients with and without acute coronary syndromes.
      found approximately 60% of patients were nonadherent to statin medications after hospitalization for acute coronary syndromes, and nonadherence was even greater for the patients taking statins for chronic coronary artery disease or primary prevention. Frolkis et al
      • Frolkis J.P.
      • Pearce G.L.
      • Nambi V.
      • Minor S.
      • Sprecher D.L.
      Statins do not meet expectations for lowering low-density lipoprotein cholesterol levels when used in clinical practice.
      found low-density lipoprotein cholesterol levels in practice were significantly less than those projected by the package insert guidelines and suggested that this gap could be explained by reduced patient adherence in clinical practice settings compared to that in a trial population. Furthermore, in patients after myocardial infarction, Rasmussen et al
      • Rasmussen J.N.
      • Chong A.
      • Alter D.A.
      Relationship between adherence to evidence-based pharmacotherapy and long-term mortality after acute myocardial infarction.
      found that statin adherence was associated with an 81% relative risk reduction in recurrent myocardial infarction and a 53% relative risk reduction in all-cause mortality. Ho et al
      • Ho P.M.
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      • Rumsfeld J.S.
      Medication nonadherence is associated with a broad range of adverse outcomes in patients with coronary artery disease.
      described an approximate 12% to 25% relative reduction in mortality. Among patients with chronic coronary artery disease, nonadherence to statins was associated with a 35% increased relative risk of CVD-related hospitalizations.
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      • Karaca-Mandic P.
      Varying pharmacy benefits with clinical status: the case of cholesterol-lowering therapy.
      In patients new to statin therapy, those with an MPR of ≥80% had significantly lower rates of CVD-related hospitalizations than patients with a lower MPR.
      • Aubert R.E.
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      • Xia F.
      • Garavaglia S.B.
      Is there a relationship between early statin compliance and a reduction in healthcare utilization?.
      Previous studies of statin adherence and cost have been conflicting. Peterson et al
      • Peterson A.M.
      • McGhan W.F.
      Pharmacoeconomic Impact of non-compliance with statins.
      found short-term (≤1 year) adherence to statins showed little correlation between the overall total medical and drug costs. In contrast, studies that evaluated patients with hypercholesterolemia
      • Sokol M.C.
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      • Epstein R.S.
      Impact of medication adherence on hospitalization risk and healthcare cost.
      and patients new to statins
      • Aubert R.E.
      • Yao J.
      • Xia F.
      • Garavaglia S.B.
      Is there a relationship between early statin compliance and a reduction in healthcare utilization?.
      found associations between better adherence to statins and lower total healthcare costs. Previous studies of adherence and cost used slightly different measures of adherence than our study; however, most approaches to measuring adherence were highly correlated and thus comparable.
      • Hess L.M.
      • Raebel M.A.
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      • Malone D.C.
      Measurement of adherence in pharmacy administrative databases: a proposal for standard definitions and preferred measures.
      These findings suggest that practitioners should vigilantly look for poor adherence and address opportunities to enhance adherence, including emphasizing the value of a patient's regimen, making the regimen simple, and customizing the regimen to the patient's lifestyle.
      • Osterberg L.
      • Blaschke T.
      Adherence to medication.
      Our findings that older age, the presence of cardiovascular diagnoses, and more total medications available were associated with an MPR >80% suggest that patients with a greater real or perceived risk of CVD might be more adherent. Patients should be asked open-ended questions about side effects, why they are taking the statin, and the benefits of taking the statin, because these questions often identify patients having trouble adhering to a regimen.
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      Adherence to medication.
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      McGinnis et al
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      found that statin adherence is complex and affected by multiple factors. Clinicians should confirm adherence, identify the reasons for nonadherence, and implement interventions to improve adherence, including patient education and follow-up.
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      • Steiner J.F.
      Factors related to adherence to statin therapy.
      One method recommended to improve adherence is to provide full monetary coverage for statins, specifically for higher risk patients (e.g., after myocardial infarction). Several analyses have determined that lowering the co-payments or providing statins without a co-payment would improve adherence and reduce hospitalizations, emergency department visits and, most likely, costs, especially in the highest risk populations.
      • Aubert R.E.
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      Is there a relationship between early statin compliance and a reduction in healthcare utilization?.
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      • Fendrick A.M.
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      In our data, we found an increased likelihood of adherence in patients with lower statin co-payments. In addition, the pharmacy delivery channel can have an affect on adherence. Patients who primarily received their statin through the mail were significantly more likely to be adherent to statins than those who received their statins from the retail channel. Both mail channel use and a lower co-payment are often associated with a 90-day supply per fill. This could partially explain the better adherence associated with these factors.
      The present study had several limitations. First, we measured adherence and clinical outcomes using administrative claims data. Administrative claims might not capture medications, medical care, and costs paid for, or obtained outside of, the patient's insurance plan (e.g., medication samples, care or medications paid for by the patient or by another insurance plan for patients who are dual insured). Incomplete administrative claims could lead to misclassification of adherent patients as nonadherent and an underestimation of the total healthcare costs and hospitalizations. This would be expected to bias our results toward the null hypothesis, suggesting that the real cost savings associated with better statin adherence might be greater than we estimated. Furthermore, the lack of access to medical records or patient histories precluded the present analysis from identifying the reasons for nonadherence, including the role of side effects or medication intolerance. Another important limitation of the present study was that we excluded patients >64 years because we did not have access to Medicare claims. Given that older patients have a greater risk of CVD and are more likely to benefit from treatment with, and adherence to, statins, our findings could underestimate the cost benefits associated with statin adherence in the Medicare population.
      Finally, it is possible that the association between adherence and lower costs and hospitalizations resulted from an unmeasured confounder, as suggested by the “healthy adherer” effect,
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      Medication adherence—its importance in cardiovascular outcomes.
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      • Solomon D.H.
      Adherence to lipid-lowering therapy and the use of preventive health services: an investigation of the healthy user effect.
      in which patients might adopt healthier lifestyles, along with adherence behaviors. For example, adherent patients might be more adherent to other CVD medications such as β blockers or angiotensin-converting enzyme inhibitors or more likely to follow therapeutic lifestyle modification recommendations. The benefits associated with statin adherence might be partially attributable to adherence to these other medications or behaviors. However, to limit this effect, we controlled for a priori selected baseline covariates available to us in the claims data. Although these limitations must be considered, we believe these associations primarily reflect the effect of better statin adherence on improved costs and outcomes, and these findings have broad implications for improving adherence to statins and the resultant value to our healthcare.

      Acknowledgment

      We thank Lorraine Tully, RHIT (Medco Health Solutions), for assistance with medical coding; Ray Brown, BSPharm (Medco Health Solutions), for analytic contributions; and Diane Graul (Medco Health Solutions) for administrative support. We thank Steven Haffner, MD and Cindy Fenton, MD (Medco Health Solutions Consultants), for assistance with all study phases.

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