96KB Sizes 0 Downloads 8 Views

Abstracts PCV101 THE IMPACT OF MULTIPLE CARDIOVASCULAR DIEASES ON ANTIDIABETIC MEDICATION ADHERENCE IN A CALIFORNIA MEDICAID POPULATION WITH COMORBID TYPE II DIABETES AND CARDIOVASCULAR DISEASE Wu J1, Nichol MB1, An JJ1, Knight TK1, Priest J2, Cantrell C2 1 University of Southern California, Los Angeles, CA, USA, 2GlaxoSmithKline, RTP, NC, USA OBJECTIVES: To investigate the impact of comorbid cardiovascular disease (CVD) on antidiabetic medication adherence. METHODS: Eligibility and claims data (2002– 2004) were used to identify patients ≥40 years of age with a diagnosis of type 2 diabetes concurrent with hypertension (HYPT), coronary artery disease (CAD), and/ or heart failure (HF), and at least two prescription fills for an antidiabetic medication. Medication adherence was assessed using proportion of days covered ≥0.8. Multivariable logistic regressions were used to assess CVD and other risk factors associated with nonadherence with antidiabetic medication using 2004 data. RESULTS: A total of 16,922 patients were identified. Patients with two comorbid CVD were more likely to use or be adherent with combination cardiovascular and antidiabetic medications [HYPT + CAD (79%/28%, represented as proportion of use/adherent rate), HF + CAD (88%/31%)] than those with a single comorbid CVD [HYPT (68%/21%), CAD (65%/21%), and HF (72%/21%), respectively, p < 0.0001]. The adherence rate for use of both antidiabetic and cardiovascular medications was only 24%. The major significant predictors of diabetic medication nonadherence included no fill of (OR:2.62, 95% CI:2.28–3.01) or nonadherent with (OR:3.43, CI:3.13–3.75) cardiovascular medication; MediCal-only eligibility (OR:1.76, CI:1.62–1.91 vs. MediCalMedicare eligibility); nonompliance with diabetes care guidelines (no eye examination, no LDL test, and less than two HbA1c tests during 2004) (OR:1.48, CI:1.37–1.59); a greater number of inpatient (OR:1.17, CI:1.10–1.24) or diabetes-related inpatient visits (OR:1.41, CI:1.06–1.87); Black race (OR = 1.47, CI: 1.29–1.66 vs. White); type of comorbid CVD vs. HF + CAD [HYPT (OR:0.73, CI:0.65–0.81), CAD (OR:0.73, CI:0.67–0.86), HYPT + CAD (OR:0.76, CI:0.67–0.86)]; two or more cardiovascular medication fills (OR:1.35, CI:1.18–1.55). CONCLUSIONS: CVD comorbidity and nonadherence with cardiovascular medications and diabetes care guidelines were major significant factors associated with nonadherence to antidiabetic medications in a California Medicaid sample. Patient nonadherence behaviors should be considered when providing care for diabetes patients with comorbid CVD. PCV102 HEALTH BELIEFS AND THEIR IMPACT ON MEDICATION ADHERENCE IN PATIENTS WITH COEXISTING DIABETES, DYSLIPIDEMIA AND HYPERTENSION Willey VJ1, Peterson A1, Ajmera M1, Manke A1, Plummer R2, Cascade E2, McGhan W1 1 University of the Sciences in Philadelphia, Philadelphia, PA, USA, 2iGuard, Inc, Princeton, NJ, USA OBJECTIVES: As individual treatment guidelines for diabetes, dyslipidemia and hypertension have evolved with more aggressive treatment targets, there may be an unintended consequence of poor medication adherence in patients having all three conditions. The study objective was to investigate how patient health beliefs affect medication adherence in patients with coexisting diabetes, dyslipidemia and hypertension. METHODS: An online survey was administered in December 2008 to iGuard. org members. Patients taking at least 1 medication for diabetes, dyslipidemia and hypertension were invited to participate in the nationwide survey (n = 2150). Survey items included demographics, the Medication Adherence Report Scale (MARS)— (score = 5–25), potential adherence barriers and adherence trade-off scenarios. Patients were assigned a dominant health belief among the three disease states based on responses to the trade-off scenarios. Medication adherence rates between diabetes and hypertension health belief groups (dyslipidemia group excluded due to small sample size) and trade-off scenario selections were compared using z-tests. RESULTS: A total of 325 patients completed the survey, 218 patients demonstrated a dominate health belief for diabetes, 81 for hypertension, 13 for dyslipidemia and 13 with no dominate health belief. In trade-off scenarios, patients consistently stated they would choose taking diabetes medications over hypertension and dyslipidemia medications. (p < 0.01) Complete adherence (MARS score = 25) with diabetes medications was higher in the diabetes health belief group (39.4%) compared to hypertension health belief group (22.2%) (p = 0.008); however there was no difference between the groups with complete adherence to hypertension (p = 0.811) or dyslipidemia (p = 0.278) medications. CONCLUSIONS: Diabetes therapy was considered the most important therapy to the majority of patients with coexisting diabetes, dyslipidemia and hypertension. However, in patients who considered hypertension therapy most important, there was significantly less adherence to diabetes medications while exhibiting similar adherence to hypertension and dyslipidemia medications. These insights could be considered by clinicians when assessing adherence in these complex patients. PCV103 A METHODOLOGY FOR USING CLAIMS DATA FROM ELECTRONIC PRESCRIBERS TO ASSESS FIRST FILL FAILURE RATE OF ANTIHYPERTENSIVE PRESCRIPTIONS Belletti DA1, Lee HY2, Xing S3, Cooke CE4 1 Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA, 2CareFirst BlueCross BlueShield, Baltimore, MD, USA, 3University of Maryland School of Pharmacy, Baltimore, MD, USA, 4PosiHealth, Inc., Ellicott City, MD, USA OBJECTIVES: Despite numerous studies on medication adherence, there is little research on the first prescription fill rate. Our study used claims data from electronic

A169 prescribers to calculate first fill failure rate for antihypertensive prescriptions. METHODS: This retrospective study combined administrative, medical and pharmacy claims data from a health plan to find the percentage of unclaimed, first fill antihypertensive prescriptions, the primary outcome. Adult members with new antihypertensive prescriptions prescribed by an electronically prescribing physician were eligible for inclusion. We allowed only prescriptions written by physicians who were electronically prescribing in order to capture antihypertensive prescriptions that would likely be adjudicated with a claim captured. Each antihypertensive prescription was assigned one outcome: paid claim (patient obtained prescription) and denied claim (unclaimed prescription). RESULTS: The cohort consisted of 14,693 new antihypertensive prescriptions prescribed by 164 electronically prescribing physicians. First fill failure rate was 15.6% for prescriptions which affected 24.3% of patients. We examined the accuracy of this new methodology by verifying the prescription rate through medical record abstraction. Chart review occurred for 183 of the 200 charts. There were 254 antihypertensives prescribed, of which 247 (97.2%) had a matching pharmacy claim. Our methodology identified 97.2% of the prescribed antihypertensives and implies that 2.8% of prescriptions would not have been identified. CONCLUSIONS: Using electronic prescribers to proxy electronic prescribing is a new method for assessing first fill rates. The intent was to identify most of the prescribed antihypertensives so that matching pharmacy claims would determine whether the prescription was obtained. With a potential error rate of 2.8% of prescriptions, this methodology appears sensitive and accurate to determine adherence to first fill prescriptions. Future research should examine the correlation between the use of electronic prescriber data and electronic prescriptions. PCV104 AN ASSESSMENT OF ADHERENCE TO SINGLE-PILL VERSUS MULTI-PILL COMBINATION LIPID-MODIFYING THERAPIES AMONG PATIENTS WITH MIXED DYSLIPIDEMIA IN A MANAGED CARE POPULATION Chang CL1, Bullano MF2, Kamat SA1, Gandhi SK2, Cziraky MJ1 1 HealthCore, Inc., Wilmington, DE, USA, 2AstraZeneca LP, Wilmington, DE, USA OBJECTIVES: To compare medication adherence among patients initiating single-pill combination (SPC) versus multi-pill combination (MPC) lipid-modifying therapies. METHODS: Administrative claims data from the nationally representative HealthCore Integrated Research Database (HIRD®), representing 32.1 million fully insured US members, was used to identify patients who newly initiated SPC therapy (simvastatin/ezetimibe SPC, simvastatin/niacin SPC, or lovastatin/niacin SPC) or equivalent medications dispensed as MPC therapy from January 2005 through November 2008. Adherence to therapy was compared between SPC and MPC groups and measured using the National Quality Forum-endorsed proportion of days of medication coverage (PDC) metric. Multivariate regression models were used to control for baseline differences between groups such as demographic characteristics, co-morbid conditions, and health resource utilization and to estimate the association between type of treatment group and optimal adherence (PDC ≥ 0.80). RESULTS: A total of 42,460 patients [38,847 SPC, age 56.3 ± 12 (mean ± SD), 55% men; 3,613 MPC, age 54.8 ± 11.6, 62% men] were identified. The mean PDC was 0.76 and 0.70 in the first 3 months of treatment, 0.54 and 0.45 in the second 3 months, and 0.50 and 0.41 for the remaining 30 months of follow-up for the SPC and MPC groups, respectively (p < 0.01 for each time period). This observed trend in sustained higher PDC for the SPC group compared to the MPC group remained even after controlling for baseline patient characteristics. Furthermore, multivariate logistic regression indicated that SPC patients were 31% more likely to be optimally adherent to treatment than MPC patients (OR = 1.31; 95% CI: 1.27–1.35; p < 0.01). CONCLUSIONS: Medication adherence was significantly higher among patients receiving single-pill combination therapies compared to multi-pill combination therapies. The results suggest single-pill therapies may improve health outcomes in patients due to improved medication adherence. Single-pill dyslipidemia therapies, where indicated, may be an important addition to health plan drug formularies because of their improved medication adherence profile. PCV105 UNDERSTANDING BARRIERS TO MEDICATION ADHERENCE FOR THE Nair KV1, Jan S2, Belletti D3, Doyle J4, Allen RR1, Patel J5 1 University of Colorado, Aurora, CO, USA, 2Horizon Blue Cross Blue Shield of New Jersey, Newark, NJ, USA, 3Novartis Pharmaceuticals Corp., Walnutport, PA, USA, 4Novartis, East Hanover, NJ, USA, 5Care Management International, Marlborough, MA, USA OBJECTIVES: Although hypertension is a major risk factor for cardiovascular disease, medication adherence to hypertensive medications is low. Previous research identifying factors influencing adherence have focused primarily on broad, population-based approaches. Identifying specific barriers for an individual is more useful in designing meaningful interventions. Using customized telephonic outreach, we examined the specific barriers influencing hypertensive patients’ non adherence in order to identify targeted interventions. METHODS: Sample represented members from a health plan in 2008 with ≥2 prescriptions for hypertensive medications. Non adherent members had a Medication Possession Ratio (MPR) of <80% for at least one of their hypertensive drugs. Telephone script was based on the “target” drug with the lowest MPR. Study was implemented in fall 2008. RESULTS: Response rate was 28.2% (n = 8692); 22.6% commercial and 49.8% Medicare respondents. Mean age was 63.4, 54.3% were female; mean MPR was 61% for the target drug. Majority of respondents (∼60%) had adherence levels between 60–79%. However, only 58.2% of Medicare and 60.4% of commercial respondents reported “missing a dose of medication”. Primary reason was forgetfulness (61.8% Medicare; 60.8% commercial) followed by

A170 “being too busy (2.5% Medicare; 17.2% commercial and “other reasons” (21.9% Medicare; 8.1% commercial) which included travel, being hospitalized or sick, disruption of daily events and unable to get to the pharmacy. Prescription copay was a barrier for <5% of respondents. Taking medications as part of a daily routine (46.4% Medicare; 52.2% commercial) helped improve adherence. Low non adherence (0–59%) was associated with higher cardiovascular related expenditures ($11,800) compared to moderate (60–79%) non adherence ($8467). CONCLUSIONS: Despite elaborate models explaining non adherence, forgetfulness was the primary reason for self reported non-adherence in this study. Events interfering with daily routine also had significant impact on non-adherence. Novel interventions should address medication taking competency and promote a medication routine. PCV106 PREDICTORS OF CLOPIDOGREL USE AND ADHERENCE FOR PATIENTS WITH ACUTE CORONARY SYNDROMES IN A LARGE EMPLOYER-BASED CLAIMS DATABASE Zhu B, Zhao Z, McCollam P, Anderson J, Bae J, Zettler M, LeNarz L Eli Lilly and Company, Indianapolis, IN, USA OBJECTIVES: Dual-antiplatelet therapy with aspirin and thienopyridines is considered as the cornerstone in the treatment of acute coronary syndromes (ACS) undergoing percutaneous coronary intervention (PCI). Recent ACC/AHA/SCAI guidelines on PCI recommend the use of clopidogrel or prasugrel for the treatment of ACS patients undergoing PCI with drug eluting or bare metal stents for at least a year. However, little is known about the factors that predict the use and adherence of clopidogrel in ACS-PCI patients. This study examined the predictors of clopidogrel use and adherence in the employer-based MarketScan claims database. METHODS: Patients (N = 10,456), aged 18–65 years, hospitalized with a primary diagnosis of ACS and underwent PCI between January 1, 2005 and December 31, 2006, and had a prior 1-year insurance eligibility and drug information were identified. Adherence was defined as medication possession ratio (MPR) of ≥80%. Multivariate logistic regression analyses were conducted to identify the predictors of clopidogrel use and adherence. RESULTS: Overall, 92.8% of ACS-PCI patients received a prescription of clopidogrel and 66.8% of the clopidogrel users were adherent. Receiving PCI without stenting (OR = 3.3), comorbid hypertension (OR = 1.50), diabetes (OR = 1.49), atrial fibrillation (OR = 1.87), and older age (OR = 1.01) were associated with decreased use of clopidogrel while prior use of clopidogrel (OR = 0.54) or other BASI (Beta-blocker, Antiplatelet agents, Statin, and ACE Inhibitor) (OR = 0.43) were associated with increased use of clopidogrel (all p-values <0.05). Factors significantly associated with non-adherence of clopidogrel were: prior use of clopidogrel (OR = 1.41), prior hospitalization (OR = 1.34), chronic pulmonary disease (OR = 1.33), PCI without stenting (OR = 1.33), and diabetes (OR = 1.18). Older age (OR = 0.98) and prior use of other BASI medications (OR = 0.84) increased the adherence of clopidogrel. CONCLUSIONS: Prior use of clopidogrel and other heart medications, stenting, diabetes and other comorbidities affected the use and adherence of clopidogrel by ACS patients undergoing PCI. These findings may help programs that aim to improve thienopyridines adherence for increased effectiveness. PCV107 PATIENT ADHERENCE TO CHRONIC DISEASE MEDICATIONS IN A MEDICATION THERAPY MANAGEMENT PROGRAM Ramasamy A1, Pinto S2, Holiday-Goodman M2, Black CD2 1 Forest Research Institute, Jersey City, NJ, USA, 2University of Toledo, Toledo, OH, USA OBJECTIVES: 1) To evaluate adherence to chronic disease (Diabetes, Hypertension, and Hyperlipidemia) medications of patients enrolled in an employer sponsored Medication Therapy Management (MTM) program. 2) To determine the effect of adherence on the clinical outcomes of patients with diabetes and hypertension in the MTM program. METHODS: This was a retrospective, longitudinal study. Adherence data was obtained from an independent pharmacy participating in an employer sponsored MTM program in the form of pharmacy refill records for 272 patients. Clinical data was obtained through patient chart reviews. Medication adherence was calculated using Medication Possession Ratio (MPR) and weighted average adherence was calculated for each class of medications. Pearson correlation was used to determine the relationship between medication adherence and desired clinical outcomes-HbA1c for diabetic patients and mean arterial pressure for hypertension patients. Multiple linear regression was used to determine if medication adherence was a predictor of clinical outcomes. Data analysis was performed using SPSS version16.0 and Microsoft Excel. RESULTS: Pearson correlation results indicated that MPR to diabetic medications was significantly correlated with age (r = 0.387, p = 0.000) and gender (r = −0.167, p = 0.021). Further, age was significantly correlated with number of diseases (r = 0.278, p = 0.000) among diabetic patients. However, there were no significant predictors of change in A1c among diabetic patients. Among hypertension patients, change in mean arterial pressure was significantly correlated with gender (r = 0.123 p = 0.037) and MPR (r = −0.146, p = 0.013). MPR was also found to be significantly correlated with gender (r = −0.148, p = 0.012, co-pay (r = 0.142, p = 0.016), and number of diseases (r = 0.142, p = 0.016). Regression model for hypertension patients indicated that MPR (β = −0.136, p = 0.024) was a significant predictor of change in mean arterial pressure. CONCLUSIONS: Patients enrolled in an employer sponsored MTM program showed high weighted average adherence to most of the classes of diabetes, hypertension, and hyperlipidemia medications. This study also identified predictors of clinical outcomes associated with diabetes and hypertension.

Abstracts PCV108 PATTERNS AND PREDICTORS OF PERSISTENCE OF WARFARIN AND OTHER COMMONLY-UTILIZED CHRONIC MEDICATIONS AMONG PATIENTS WITH ATRIAL FIBRILLATION Song X1, Sander S2, Varker H1, Amin A3 1 Thomson Reuters, Cambridge, MA, USA, 2Boehringer Ingelheim Pharmaceuticals, Inc, Ridgefield, CT, USA, 3University of California, Irvine, Irvine, CA, USA OBJECTIVES: We examined the patterns of persistence among warfarin and other common chronic medications in patients with atrial fibrillation (AF) and identified predictors of warfarin non-persistence. METHODS: We used a national, managed care claims dataset (January 1, 2005-December 31, 2007) to evaluate patterns of persistence in patients with AF. We examined those that filled a prescription for warfarin within 3 months following AF hospitalization discharge and had at least 12-month continuous data prior to and following the first fill. For comparison, we also evaluated patterns of persistence for other selected, chronically-prescribed medications, including branded, generic, once-, twice-, and thrice-daily medications. Nonpersistence was defined as failure to refill the medication within 60 days from the run-out date of the prior prescription. Survival models were used to identify predictors of warfarin non-persistency. RESULTS: A total of 28,384 patients with AF were identified; 16,036 (56.5%) filled a warfarin prescription shortly following hospitalization for AF. A total of 53.5% of warfarin users were persistent on warfarin for at least 1 year. Among non-persistent patients, average time to non-persistence was 122 (SD 83) days from the first warfarin prescription. Persistence with pioglitazone, sitagliptin, amlodipine, and once- and twice-daily carvedilol were similar to warfarin. While persistence with twice-daily carvedilol was similar to once-daily carvedilol phosphase (60.1% vs. 61.3%, p = 0.680), persistence of thrice-daily captopril was significantly worse than that of once-daily amlodipine (27.7% vs. 51.9%, p < 0.001). Factors significantly associated with time to non-persistence with warfarin included age, gender, residence in the south and west region, ischemic stroke, urinary tract infection, and warfarin out-of-pocket expense. CONCLUSIONS: Persistence with warfarin among patients with AF is consistent with other chronic medications. Persistence with thrice-daily, but not twice-daily therapy was worse than once-daily medication. Factors associated with non-persistence can be used to identify patients and target adherence programs. PCV110 DISCRIMINATORY POWER OF THE KCCQ IN ESTIMATING HEALTH UTILITIES IN HEART FAILURE PATIENTS Li Y1, Whellan DJ2, Samsa GP3, Schulman K1, Reed SD1 1 Duke Clinical Research Institute, Durham, NC, USA, 2Jefferson Medical College, Philadelphia, PA, USA, 3Duke Univeristy, Durham, NC, USA OBJECTIVES: Most economic models in heart failure have been structured using New York Heart Association (NYHA) class to define mutually exclusive health states. With this structure, no utility (i.e. effectiveness) gains are measured in patients who experience important changes in health status but remain in the same NYHA class. We sought to evaluate whether the Kansas City Cardiomyopathy Questionnaire (KCCQ) summary score can further discriminate between patients with lower and higher health utilities within a given NYHA class. METHODS: Repeated measures of NYHA class, KCCQ, and EQ-5D utility scores were available from patients enrolled in HFACTION, a randomized trial evaluating the effectiveness and safety of exercise training in addition to usual care compared to usual care alone in patients with chronic heart failure. We used generalized estimating equations to regress utility scores on NYHA class and demographic characteristics and to evaluate the impact of adding the KCCQ summary score in the regression models.RESULTS: A total of 12,649 sets of assessments were available from 2331 patients. The mean age of the study cohort was 59 years at baseline, 72% were male, 61% were white, and 32% were black. When controlling for age, gender and race, estimated utilities were 0.84 (95% CI: 0.81–0.87) for NYHA class I, 0.80 (95% CI: 0.78–0.83) for class II, 0.75 (95% CI: 0.72–0.78) for class III, and 0.65 (95% CI: 0.61–0.69) for class IV. A one-unit increase in the KCCQ summary score was associated with a 0.0044 (95% CI: 0.0042, 0.0045) increase in the utility weight, and its impact did not significantly vary across NYHA classes. CONCLUSIONS: Use of KCCQ summary score in addition to, or instead of, NYHA class may provide more discriminatory power in terms of estimating incremental gains in quality-adjusted life-years afforded by interventions for heart failure. PCV111 ANALYZING THE RELATIONSHIP BETWEEN CHANGES IN PROS AND CLINICAL ENDPOINTS Weinfurt K, Lin L, Flynn K Duke University Medical Center, Durham, NC, USA OBJECTIVES: To demonstrate a simple, powerful, and flexible approach to modeling the relationships between patient-reported outcomes and clinical measures over time. METHODS: Data were from 2,331 patients enrolled in the HF-ACTION (Heart Failure and A Controlled Trial Investigating Outcomes of Exercise TraiNing) trial. The patient-reported endpoint was the Kansas City Cardiomyopathy Questionnaire (KCCQ) overall score and the clinical endpoint was peak VO2. We compared three different ways of measuring the association between changes in the KCCQ and peak VO2. The first method (SIMPLE) computes change-from-baseline scores for each outcome. The second method (BLUP-1) used a linear mixed-effects model for each outcome to derive the best linear unbiased predictions (BLUP) of changes from baseline. The third method (BLUP-2) added 28 baseline covariates and their interactions with time to the mixed model and then obtained BLUPs. For all three methods