Cost-related medication non-adherence among U.S. adults with diabetes

https://doi.org/10.1016/j.diabres.2018.06.016Get rights and content

Abstract

Aims

To examine factors that affect cost-related medication non-adherence (CRN), defined as taking medication less than as prescribed because of cost, among adults with diabetes and to determine their relative contribution in explaining CRN.

Methods

Behavioral Risk Factor Surveillance System data for 2013–2014 were used to identify individuals with diabetes and their CRN. We modeled CRN as a function of financial factors, regimen complexity, and other contextual factors including diabetes care, lifestyle, and health factors. Dominance analysis was performed to rank these factors by relative importance.

Results

CRN among U.S. adults with diabetes was 16.5%. Respondents with annual income <$50,000 and without health insurance were more likely to report CRN, compared to those with income ≥$50,000 and those with insurance, respectively. Insulin users had 1.24 times higher risk of CRN compared to those not on insulin. Contextual factors that significantly affected CRN included diabetes care factors, lifestyle factors, and comorbid depression, arthritis, and COPD/asthma. Dominance analysis showed health insurance was the most important factor for respondents <65 and depression was the most important factor for respondents ≥65.

Conclusions

In addition to traditional risk factors of CRN, compliance with annual recommendations for diabetes and healthy lifestyle were associated with lower CRN. Policies and social supports that address these contextual factors may help improve CRN.

Introduction

Approximately 30.3 million people in the U.S. have diabetes [1]. Poor medication adherence is a common phenomenon among patients with diabetes [2]. The American Diabetes Association (ADA) estimated that patients with diabetes spent 27% ($3,734 per patient in 2012) of direct medical costs for outpatient medications and supplies [3]. The high cost of diabetes care is associated with medication non-adherence [4], [5], [6], which results in poor clinical outcomes [7], [8]. Patients with diabetes often have comorbidities that require medications in addition to oral and injectable diabetes medications. The complex polypharmacy regimens increase cost burden in acquiring prescribed medications, which can play a role in reducing medication adherence [9], [10], [11].

Cost-related medication non-adherence (CRN), defined as taking medication less than as prescribed because of cost, has been found to be between 16% and 19% among patients with diabetes [12], [13]. For low-income individuals with diabetes, CRN may become a serious issue in managing their blood glucose and comorbid conditions that can potentially lead to further economic disparities in diabetic complications and mortality. Studying factors that affect CRN may help identify policies that could improve adherence to medication. In previous research, numerous factors have been examined and found to affect CRN [13], [14], [15], [16], [17]. However, it is still not clear whether medication non-adherence can truly be reduced if financial burden is lifted through insurance coverage or other fiscal policies or if there are other factors that may need to be addressed before any fiscal policies may take effect. A study on the relative importance of these factors may help in prioritizing policies for reducing CRN.

The primary objective of this study is to examine both financial and non-financial factors that affect CRN among patients with diabetes. Our secondary objective is to determine the relative contribution of factors in explaining CRN. Our hypothesis is that contextual factors (e.g., diabetes care, lifestyle, comorbidities) are significant predictors of CRN, independent of financial factors and regimen complexity.

Section snippets

Research design and study population

Our study population consisted of all persons with diabetes who used prescription medications in the U.S. in 2013–2014. We derived our study sample from the Behavioral Risk Factor Surveillance System (BRFSS), an annual telephone survey of U.S. adults about their health, chronic conditions, and preventive care utilization. The study sample included all persons with self-reported diabetes who took at least one prescription medication and resided in states that implemented the “Diabetes Module” in

Results

In 2013 and 2014, 956,437 persons responded to the BRFSS surveys, of whom 12.9% reported as having diabetes. After survey weights were applied, diabetes prevalence in these two years was 10.4% of the US adult population. After exclusions, there were 44,925 respondents from 25 states and the D.C. in the final sample.

Table 1 shows weighted percentages of respondents with CRN by individual characteristics. Overall, about 16.5% of respondents with diabetes who took prescription medications answered

Discussion

Our results show that household income and health insurance were the most important factors in explaining CRN for younger adults <65 years of age, while depression dominated all other factors for the elderly with over 21% of CRN explained by this single factor followed by household income. Depression ranked fifth for the younger adults. When both age groups were combined, age had the largest contribution to CRN of all predictors with individuals <55 years of age having four times higher

Conclusion

CRN prevalence among U.S. adults with diabetes was 16.5% in 2013–2014. Depression and household income for respondents aged ≥65 years and health insurance and household income for those <65 years were the most important determinants of CRN. In addition to traditional risk factors of CRN, we showed that contextual factors such as compliance with ADA recommendations and healthy lifestyle were also associated with lower CRN. Policies and social supports that address the significant contextual

Acknowledgments

The authors gratefully acknowledge the financial support from the Agency for Healthcare Research and Quality (R01HS018542) and the National Institute of Diabetes, Digestive, and Kidney Diseases (R01DK113295). The paper presents the findings and conclusions of the authors; it does not necessarily represent the Agency for Healthcare Research and Quality or the National Institutes of Health.

Conflict of Interest

The authors have no conflicts of interest to report.

Funding source

Agency for Healthcare Research and Quality (1R01HS018542) and NIH/NIDDK (1R01DK113295)

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