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The American Journal of Managed Care August 2010
Clinical and Economic Outcomes After Introduction of Drug-Eluting Stents
Charanjit S. Rihal, MD, MBA; James L. Ryan, MHA; Mandeep Singh, MBBS; Ryan J. Lennon, MS; John F. Bresnahan, MD; Juliette T. Liesinger, BA; Bernard J. Gersh, MBChB, DPhil; Henry H. Ting, MD, MBA; David R. Holmes, Jr, MD; and Kirsten Hall Long, PhD
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Antihypertensive Medication Adherence and Subsequent Healthcare Utilization and Costs
Donald G. Pittman, PharmD; Zhuliang Tao, MPH; William Chen, PhD; and Glen D. Stettin, MD
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Ogochukwu C. Molokwu, PharmD, MScMed
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Kellie J. Ryan, MPH Matthew D. Rousculp, PhD, MPH. Reply by Bruce Y. Lee, MD, MBA Julie H. Y. Tai, MD Rachel R. Bailey, MPH
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Teresa B. Gibson, PhD; Xue Song, PhD; Berhanu Alemayehu, DrPH; Sara S. Wang, PhD; Jessica L. Waddell, MPH; Jonathan R. Bouchard, MS, RPh; and Felicia Forma, BSc
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Cheryl L. Damberg, PhD; Stephen M. Shortell, PhD, MPH, MBA; Kristiana Raube, PhD, MPH; Robin R. Gillies, PhD; Diane Rittenhouse, MD, MPH; Rodney K. McCurdy, MHA; Lawrence P. Casalino, MD, PhD; and John Adams, PhD
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Richard J. Gilfillan, MD; Janet Tomcavage, RN, MSN; Meredith B. Rosenthal, PhD; Duane E. Davis, MD; Jove Graham, PhD; Jason A. Roy, PhD; Steven B. Pierdon, MD; Frederick J. Bloom Jr, MD, MMM; Thomas R. Graf, MD; Roy Goldman, PhD, FSA; Karena M. Weikel, BA; Bruce H. Hamory, MD; Ronald A. Paulus, MD, MBA; and Glenn D. Steele Jr, MD, PhD
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Russell L. Knoth, PhD; Susan C. Bolge, PhD; Edward Kim, MD, MBA; and Quynh-Van Tran, PharmD
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Antihypertensive Medication Adherence and Subsequent Healthcare Utilization and Costs

Donald G. Pittman, PharmD; Zhuliang Tao, MPH; William Chen, PhD; and Glen D. Stettin, MD

Retrospective analysis of antihypertensive medication adherence and subsequent total healthcare costs demonstrated a significant, continuous, and inversely proportional effect of adherence on total healthcare costs.

Objectives: To evaluate the relationship between adherence to antihypertensive medications (AHMs) and subsequent hospitalizations, emergency department (ED) visits, and costs of care.

 

Study Design: Retrospective analysis of a national pharmacy benefits database of deidentified pharmacy and medical claims among patients with a diagnosis of hypertension. Adherence was estimated using the medication possession ratio (MPR).

 

Methods: Multivariate logistic and 2-part general linear models were estimated to study the relationship between adherence level (estimated by the MPR) and subsequent association with healthcare costs and cardiovascular (CV)-related hospitalizations and ED visits.

 

Results: We identified 625,620 patients with at least 2 claims for AHMs and divided them into 3 cohorts based on year 1 MPR of less than 60% (62,388 patients with low adherence), 60% to 79% (96,226 patients with moderate adherence), and 80% or higher (467,006 patients with high adherence). Patients with high adherence to AHMs were more likely to be older and male, have higher chronic disease scores and lower AHM copayments, and fill a greater percentage of prescriptions by mail order. Year 2 total mean (SD) adjusted healthcare costs were significantly lower for patients with an MPR of 80% or higher ($7182 [$27]) vs 60% to 79% ($7560 [$59]) or less than 60% ($7995 [$73]) (P <.001 for both). In addition, patients with low or moderate adherence had higher age- and sex-adjusted odds of CV-related hospitalizations (odds ratio [OR], 1.33; 95% confidence interval [CI], 1.25-1.41) and ED visits (OR, 1.45; 95% CI, 1.33-1.58) (P <.001 for both).

 

Conclusion: Adherence to AHMs is associated with significantly lower total healthcare costs and with significantly lower odds of CV-related hospitalizations and ED visits.

 

(Am J Manag Care. 2010;16(8):568-576)

Adherence to antihypertensive medications (AHMs) is associated with lower total healthcare costs and with reduced odds of cardiovascular-related hospitalizations and emergency department visits.

  • High adherence to AHMs (medication possession ratio [MPR], 80%-100%) reduces adjusted total healthcare costs up to $813 per patient annually compared with low or moderate adherence to AHMs (MPR, <80%).
  • The relationship between medication adherence and healthcare costs was continuous and inversely proportional such that healthcare costs increased significantly as the MPR decreased.
  • Benefits of improved adherence and evidence of total cost savings provide incentive for patient-, provider-, and health system-level interventions to improve AHM adherence.
More than 74.5 million Americans have hypertension, with an estimated cost of $76.6 billion per year.1 Previous clinical trials in hypertension have shown that reduction of blood pressure is associated with significant decreases in the incidence of stroke, ischemic heart disease, congestive heart failure, and renal failure across age, sex, race/ethnicity, type of antihypertensive used, and severity of hypertension.2,3 Despite this benefit, it is estimated that only 35% of patients with hypertension achieve optimal control.3,4

In observational studies, nonadherence to antihypertensive medications (AHMs) is an important factor in the failure to achieve better blood pressure control5-7 and is associated with a higher risk of hospitalization and mortality among patients with diabetes mellitus.8 Bramley et al7 found that high adherence to AHMs, identified as a medication possession ratio (MPR) of 80% to 100%, was associated with better blood pressure control compared with low-to-medium levels of adherence. Two recent studies describe an association between better adherence to AHMs and decreased subsequent cardiovascular (CV) events9 and stroke10 among patients with newly diagnosed hypertension, but neither study evaluated costs of care. A 2009 review of the importance of medication adherence relative to CV outcomes stated that there is a clear need for more research to better understand the association between adherence and healthcare costs because surprisingly little is known among populations with CV disease.11

Pivotal earlier studies12-14 demonstrated that better adherence to AHMs is associated with reduced costs of care. However, results from these studies may have been influenced by analysis of adherence and costs in the same year, and all relied on data from the 1990s. In addition, these prior studies evaluated the effect of adherence on costs among limited populations that included a large employer14 and Medicaid populations.12,13

Given the limitations of prior work and the growing recognition about the importance of medication adherence,15 more robust studies are needed to evaluate current cost implications associated with adherence to AHMs. The present national retrospective cohort study of 625,620 insured patients with a diagnosis of hypertension evaluated the relationship between adherence to AHMs in 2007 and hospitalizations, emergency department (ED) visits, and costs of care in 2008.

METHODS

Data were extracted from the information warehouse of Medco Health Solutions, Inc. The information ware-house is a data repository that includes deidentified demographic and pharmacy claims history, including retail and mail-order use. The information warehouse has deidentified medical claims data on more than 10 million patients that can be matched to pharmacy claims.

The study included all patients aged 18 to 63 years with an International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), diagnosis of hypertension (codes 401.x-405.x), and with 2 or more claims within 1 primary class of AHMs, at least 1 of which was between July 1, 2007, and December 31, 2007, and another within 12 months before the last claim in 2007. We excluded patients with claims for cancer (codes 140.x-172.x and 174.x-208.x) or human immunodeficiency virus (codes 042.x-044.x), as these diseases can be associated with overwhelming pharmacy and medical costs independent of adherence to AHMs. In addition, we excluded patients who were not continuously eligible for prescription drug coverage; who did not have medical or pharmacy data from July 1, 2006, through December 31, 2008; or who were 64 years or older as of January 1, 2007, because the information warehouse of Medco Health Solutions, Inc, does not reliably receive complete medical claims for patients covered by Medicare. For analysis  purposes, we defined year 1 as January 1, 2007, through December 31, 2007, and year 2 as January 1, 2008, through December 31, 2008 (Figure 1). The selection criteria

were used to create a deidentified data set that was further analyzed for this study.

Adherence to AHM class was estimated by calculating the MPR, or the ratio of total days of medication supplied to total days in a period. The MPR is the accepted standard for evaluation of adherence using retrospective data because it is easy to calculate and performs as well as other claims-based estimates.16 The MPR was calculated based on the total number of days between the dates of the last fill in year 1 and the first fill in the 365 days before the last fill. This MPR evaluation included a look back through July 1, 2006, to provide a full year of data on adherence. For patients receiving multiple AHMs, the MPR was calculated for each AHM separately, and the overall MPR was the mean of the individual MPR values.11 The MPR was capped at 100%, as it is unlikely that patients use AHMs at greater than the prescribed frequency.16 For the primary evaluation, we used year 1 MPR to classify the patients into the following 3 categories: high adherence (MPR, >80%), moderate adherence (MPR, 60%-79%), and low adherence (MPR, <60%). As a secondary analysis of costs of care, we divided the MPR into 5 levels (0%-19%, 20%-39%, 40%-59%, 60%-79%, and 80%-100%). Previous literature recommends using the MPR as a dichotomous variable, with an 80% MPR considered adherent.15,16 Although this percentage is somewhat arbitrary, it has been accepted as the cutoff in most investigations on adherence and in observational and randomized controlled clinical trials.15

The number of total medications and different classes of AHMs on hand were determined as of December 31, 2007. In addition, we evaluated the following variables during year 1 that were identified as potential mediators of adherence: generic dispensing rates, the number of prescriptions filled for generically available AHMs divided by the total number of prescriptions for AHMs, the percentage of AHMs filled through mail order, the number of prescriptions filled by mail order divided by the total number of prescriptions filled after adjusting for the increased days supply by mail order, and the monthly patient copayment for AHMs from pharmacy claims, which is the total amount paid by the patient, including copayment, deductible, and coinsurance per month covered by prescriptions.

To control for possible comorbidities, we used pharmacy claims from 2007 to calculate a chronic disease score (CDS).16 The CDS is a comorbidity severity indicator derived from pharmacy-based claims data during a given period. For each patient, we used medical claims to evaluate the number of hospitalizations and ED visits in year 1 and year 2 and the following specific comorbidities identified by ICD-9-CM codes: coronary artery disease (codes 410.x-414.x and 996.03), dyslipidemia (code 272.x), stroke (codes 430.x-438.x and 997.02), heart failure (codes 402.x1, 404.x1, 404.x3, and 428.x), diabetes mellitus (code 250.x), end-stage renal disease (ESRD) (codes 403.x1, 404.x1, 585.5, and 585.6), and depression (codes 296.2x, 296.3x, 298.0, 300.4, 309.1, 309.28, and 311).

The primary outcome was total healthcare costs during year 2 (January 1, 2008, through December 31, 2008) for the groups having low-to-moderate adherence compared with the group having high adherence. In a secondary analysis, adjusted healthcare costs were also calculated for 5 quintiles of adherence. Total healthcare costs were determined by summing the costs of all pharmacy and medical claims (including outpatient services, hospitalizations, and ED visits) in 2008. Costs were based on total cost to the plan sponsor and excluded atient copayments and deductibles. Nursing home and home healthcare costs were not included in our cost analysis. Secondary outcomes were CV-related hospitalizations and ED visits, evaluated as the risk of having 1 or more medical claims indicating a hospitalization or an ED visit in 2008.

Statistical Analysis

We compared the baseline demographic factors, comorbidities, and medication factors between adherent and nonadherent patients using χ2 test for binary variables and Wilcox on signed rank test for continuous variables. Regression analyses were performed to assess the relationship between outcome variables and covariates. When the outcome variable had continuous values, we used general linear model (GLM) least squares regression analysis; when the outcome variable had binary values, we used logistic regression analysis. To reveal the determinants of adherence to AHMs, we created an outcome variable of high adherence versus low-to-moderate adherence. The predictors included demographics alone and together with comorbidities, CDS, class of AHMs, out-of-pocket cost for medication, and use of mail order. To explore possible differential effects of sex in critical subgroups of patients, we performed a secondary analysis of determinants of adherence that included interaction terms for sex-×age, sex-×–coronary artery disease, sex-×–diabetes mellitus, sex-×–heart failure, sex-×-stroke, sex-×-hyperlipidemia, sex- depression, and sex-×-ESRD. We used logistic regressionanalysis to evaluate the association of level of adherence with clinical outcomes of CV disease–related hospitalizations and ED visits after adjusting for important baseline differences. To determine the mean costs in year 2 for each level of adherence, we used GLMs and adjusted for baseline differences in age, sex, year 1 CDS, and year 1 total costs. Least squares means of costs were generated and compared among groups with the 3 levels of adherence. Version 9.1 of SAS (SAS Institute, Cary, NC) was used for all statistical analyses, and 2-sided P <.05 was considered statistically significant.

RESULTS

After applying the inclusion and exclusion criteria, we identified 625,620 patients for the analysis (Figure 2). On average, patients were 52.6 years old and 48.9% female and had an MPR of 86.3% and a CDS of 22.0 (Table 1). The most common comorbidities in the population included dyslipidemia (58.5%), diabetes mellitus (24.2%), coronary artery disease (11.0%), and depression (7.6%). At the end of year 1, patients averaged 3.7 medications on hand, representing 1.3 different classes of AHMs. Generic medications were used in 63.2% of AHMs, and 46.7% of patients received 1 or more of their AHMs by mail order. Angiotensin-converting enzyme inhibitors (43.9%) and diuretics (48.3% [84.5% of these were thiazides]) were the most common classes of AHMs used. The mean copayment for the AHMs was $10.10 per month.

 
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