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Using Medication Fill Records to Help Predict Nonadherence of Statins in New Users

October 29, 2020

zahraBy: Zahra Majd, PharmD, doctoral student & graduate teaching assistant, Department of Pharmaceutical Health Outcomes and Policy, College of Pharmacy, University of Houston

Statins are one of the highest prescribed classes of drugs in the United States. More than one-fourth of the Americans above 40 years of age are prescribed statins.1,2 Although statins are the mainstay of lipid-lowering therapy with well-established benefits in managing dyslipidemia and reducing cardiovascular risks, adherence to statin therapy is suboptimal.3,4 Nearly 50% of patients discontinue their statin treatment within a year of treatment initiation and this number grows over time.5

Medication adherence is a major public health issue which has been identified as the leading cause of preventable morbidity, mortality, and health care costs.6 Several interventions have been developed to improve adherence. However, given the limited time and resources for developing and implementing adherence intervention programs, it is widely acknowledged that they will be most effective if targeting appropriate patients and prioritizing those who are likely to fail treatment due to poor medication adherence in the future.7,8

Different approaches were implemented by earlier research to predict medication taking behavior for statins and identify predictors associated with it. Although using patients’ demographics and clinical characteristics were successful in predicting adherence, recent studies have suggested that adding measures of past  adherence to chronic medications could enhance predictability of the models.9-13 Therefore, this study aimed to predict patient’s adherence to newly initiated statins by measuring previous adherence to angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin II receptor blockers (ARBs). We hypothesized that patients who are adherent to their past ACEI/ARB use will show better adherence to newly initiated statins over the first 12 months.

In this retrospective cohort study, administrative claims data from patients enrolled in a Texas-based Medicare Advantage Plan between January 2016 and May 2018 were used. We conducted a multivariable logistic regression to investigate the association between adherence to the baseline ACEIs/ARBs and future statin adherence while adjusting for various demographic and clinical characteristics. 

Results showed that among 1,223 patients included in our study, only 41.62% were adherent to statins during the first year of treatment initiation. Majority of the patients were females, younger than 70 years old, and without previous hospitalizations. Hyperlipidemia, hypertension, and type II diabetes were the most frequent comorbidities among patients. Findings from the logistic regression analysis indicated that patients who were adherent to baseline ACEI/ARB use were significantly more likely to be adherent to the future statin use (OR=1.75; 95%CI=1.37-2.25). Additionally, those who had low income subsidy were more likely to be in the statin adherent group compared to patients with no income subsidy (OR=1.280; 95% CI=1.009-1.624). The last significant finding was that patients ≥ 80 years old were less likely to be adherent to statins compared to those below 70 years old (OR=0.62; 95%CI=0.41-0.92).

According to our results, less than 50% of the statin new users are adherent to their statin therapy within the first year of treatment initiation, which is consistent with existing literature. A previous systematic review has found that being a statin new user along with other factors such as age, sex, race, socioeconomic status, side effects, and comorbidities are potential reasons for statin non-adherence.14 Further, we found that previous adherence to ACEIs/ARBs was significantly associated with adherence to newly initiated statins over the first 12-months of treatment. In other words, patients who were nonadherent to ACEI/ARB use in the past had higher likelihood of being nonadherent to statins in the first year of treatment initiation. This finding confirms previous research indicating baseline adherence to chronic medications was a relatively strong predictor of future adherence to newly initiated statins. Another significant predictor for future adherence to statins was receiving low income subsidy meaning that patients having low income subsidy were more likely to be adherent to statins compared to those with no income subsidy. According to a previous study, lower out-of-pocket costs, higher medication fills, and better adherence were observed in low income subsidy beneficiaries from Medicare Part D plan.15 With respect to the association between age and adherence, literature is still controversial. Our findings suggest that medication adherence is adversely affected by age. Patients equal or above 80 years old were less likely to be adherent to statins compared to those below 70 years old. Potential reasons may include development of cognitive impairments, multiple comorbid conditions, and complex treatment regimens.

In conclusion, results from this study highlight the value of using records of past medication fills and adherence to identify statin new users likely to be nonadherent in the first year of treatment initiation. By identifying barriers to statin adherence among potential non-adherent patients and targeting medication adherence interventions at these patients, health care providers will be able to effectively improve patient’s adherence, given that medication adherence is a modifiable health behavior.  

The authors of the study described above were:

Zahra Majd1, Anjana Mohan1, Rutugandha Paranjpe1, Aisha Vadhariya2, Susan M Abughosh1

1 University of Houston College of Pharmacy, Houston, TX; 2 School of Pharmacy, Duquesne University, Pittsburgh, PA


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2. Salami JA, Warraich HJ, Valero‐Elizondo J, et al. National trends in nonstatin use and expenditures among the US adult population from 2002 to 2013: insights from medical expenditure panel survey. Journal of the American Heart Association. 2018;7(2):e007132.

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5. Vadhariya A, Fleming ML, Johnson ML, et al. Group-based trajectory models to identify sociodemographic and clinical predictors of adherence patterns to statin therapy among older adults. American health & drug benefits. 2019;12(4):202.

6. Sabaté E, Sabaté E. Adherence to long-term therapies: evidence for action. World Health Organization; 2003

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9. Mann DM, Woodward M, Muntner P, Falzon L, Kronish I. Predictors of nonadherence to statins: a systematic review and meta-analysis. Ann Pharmacother. 2010;44(9):1410-1421.

10. Choudhry NK, Fischer MA, Avorn J, et al. The implications of therapeutic complexity on adherence to cardiovascular medications. Arch Intern Med. 2011;171(9):814-822.

11. Muntner P, Yun H, Sharma P, et al. Ability of low antihypertensive medication adherence to predict statin discontinuation and low statin adherence in patients initiating treatment after a coronary event. The American journal of cardiology. 2014;114(6):826-831.

12. Kumamaru H, Lee MP, Choudhry NK, et al. Using previous medication adherence to predict future adherence. Journal of managed care & specialty pharmacy. 2018;24(11):1146-1155.

13. Krumme AA, Franklin JM, Isaman DL, et al. Predicting 1-year statin adherence among prevalent users: a retrospective cohort study. Journal of managed care & specialty pharmacy. 2017;23(4):494-502.

14. Ingersgaard MV, Andersen TH, Norgaard O, Grabowski D, Olesen K. Reasons for Nonadherence to Statins–A Systematic Review of Reviews. Patient preference and adherence. 2020;14:675.

15. Yala SM, Duru OK, Ettner SL, Turk N, Mangione CM, Brown AF. Patterns of prescription drug expenditures and medication adherence among medicare part D beneficiaries with and without the low-income supplement. BMC health services research. 2014;14(1):665

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