Oral Antihyperglycemic Medication Nonadherence and Subsequent Hospitalization Among Individuals With Type 2 Diabetes

College of Pharmacy, University of Michigan, Ann Arbor, Michigan, United States
Diabetes Care (Impact Factor: 8.42). 10/2004; 27(9):2149-53. DOI: 10.2337/diacare.27.9.2149
Source: PubMed


This study examines the association between oral antihyperglycemic medication nonadherence and subsequent hospitalization among individuals with type 2 diabetes.
Using administrative claims data (2000-2001) from a managed care organization in the Midwestern U.S., this study analyzed 900 enrollees, aged 18 years and over, with type 2 diabetes who were taking oral antihyperglycemic agents both years but who did not use insulin. Nonadherence was defined as a medication possession ratio (MPR) <80%. Multivariate logistic regression analyses were performed where hospitalization in 2001 was regressed on nonadherence to the oral antihyperglycemic drug regimen in 2000, while controlling for nonadherence to drugs for hypertension and dyslipidemia and for hospitalization in 2000, age, sex, intensity of the diabetes drug regimen, and comorbidities.
The proportion of enrollees who were nonadherent to the antihyperglycemic drug regimen in 2001 was 28.9%, whereas 18.8 and 26.9% were nonadherent to antihypertensive and lipid-modifying drugs, respectively. The increase in the hospitalization rate for 2001 was most apparent where the antihyperglycemic MPR for 2000 dropped to <80%. Enrollees who were nonadherent to oral diabetes medications in 2000 were at higher risk of hospitalization in 2001 (odds ratio 2.53; 95% CI 1.38-4.64), whereas nonadherence to drugs for hypertension and dyslipidemia were not significantly associated with hospitalization.
Patients with type 2 diabetes who do not obtain at least 80% of their oral antihyperglycemic medications across 1 year are at a higher risk of hospitalization in the following year.

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    • "However , lack of standard measurements and use of different definitions make comparison challenging. It is important for health care providers to consider low medication adherence as a factor contributing to poor glycemic control (Lau and Nau 2004). Thus, designing strategies to improve medication adherence might improve glycemic control and there-by decrease the rate of chronic complications related to diabetes. "
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    ABSTRACT: Low adherence to prescribed diabetes medications is one of the major reasons to poor glycemic control in developing countries. Therefore, this study attempted to assess the magnitude of medication adherence and factors associated with it among adult persons with diabetes in northwest Ethiopia. This study utilized a cross sectional study design with internal comparison. The study population was adult persons with diabetes attending the Diabetes Referral Clinic of Gondar University Hospital. Adherence was assessed using the eight-item Morisky Medication Adherence Scale (MMAS-8). In addition laboratory tests and chart reviews were carried out to collect relevant data. Ordinary logistic regression was used to identify factors associated with adherence. A total of 391 patients were studied. Based on the MMAS-8 scale, the self-reported adherence to diabetic medication was low for 25.4% [95% CI: 21, 29] of the patients, medium for 28.7% [95% CI: 24, 33], and high for 45.9% [95% CI: 41, 50] of the patients. The Mean (±SD) of glycosylated hemoglobin for the low adherence group was 8.2% (±2.1). It was 8.1% (±2.0), for the medium, and 7.4% (±1.6) for the high adherence group. In the multivariate analysis poor wealth status (AOR = 1.99; 1.15, 3.43), using traditional treatment (AOR = 2.90; 1.03, 8.15), and service dissatisfaction (AOR = 2.23; 1.04, 4.80) were significantly associated with low adherence to prescribed diabetic medications. Over half of the persons with diabetes did not adhere to medications. Adherence was poor among users of traditional treatment and those dissatisfied with services. Developing a more intensive communication strategies and improving the quality of services could improve the level of adherence.
    SpringerPlus 04/2014; 3(1):195. DOI:10.1186/2193-1801-3-195
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    • "Adherence to long-term therapy for chronic illnesses in developed countries is estimated to average 50% by the World Health Organization (WHO) [4]. Studies have shown that poor adherence is associated with worsening of the patients' clinical status/ health [5] [6], higher risk of hospitalization [7], risk of preventable drugs-related hospital admissions [8], and higher mortality risk [9]. Losing adherence has been shown to be associated with higher outcome of hospitalizations and emergency department visits [10]. "
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    ABSTRACT: Objectives To develop a multistate model and an algorithm for calculating long-term adherence to medication among patients with a chronic disease. Methods We propose definitions of the different states of waiting, persistence, with sufficient supply to implement the prescribed dosing regimen, gaps, nonpersistence, and nonacceptance and an algorithm for transitions between states to describe long-term adherence to medication treatment. The model and algorithm are operationalized for use in a case with a retrospective cohort of patients with type 2 diabetes mellitus, with access to records of prescribed drugs from a Danish diabetes research hospital and records of filled prescriptions at Danish pharmacies from the Danish Health and Medicines Authority. Results Calculations of long-term adherence to medication are shown for patients with type 2 diabetes mellitus on metformin and/or simvastatin. The study shows how the prevalence of patients waiting to initiate treatment, patients with supply to implement the prescribed dosing regimen, patients not accepting treatment, and patients discontinuing treatment varies over time. Conclusions The proposed multistate model and algorithm can easily be translated and used for the calculation of adherence to medication in any chronic disease. The model and algorithm take time into account, and thus, changes in incidence rates and prevalence of the different states over time can be estimated on several time scales (calendar time, age of the patient, and time since indication for medication).
    Value in Health 03/2014; 17(2):266–274. DOI:10.1016/j.jval.2013.11.014 · 3.28 Impact Factor
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    • "Many adults with type 2 diabetes mellitus (T2DM) do not take their medications as prescribed [1] [2]; and suboptimal medication adherence has been associated with poor glycemic control [3] [4] [5] [6], an increased risk of hospitalization [5,7–9], early mortality [5] [9], and higher healthcare costs [8]. Improvements in diabetes medication adherence could improve the health outcomes of patients with diabetes [7] [10] and save $661 million to $1.16 billion annually [11]. While identifying nonadherence is a logical first step to intervention [12], more scientifically valuable and clinically feasible measures of diabetes medication adherence are needed for this purpose [13] [14]. "
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    ABSTRACT: The Adherence to Refills and Medications Scale (ARMS) has been associated with objective measures of adherence and may address limitations of existing self-report measures of diabetes medication adherence. We modified the ARMS to specify adherence to diabetes medicines (ARMS-D), examined its psychometric properties, and compared its predictive validity with HbA1C against the most widely used self-report measure of diabetes medication adherence, the Summary of Diabetes Self-Care Activities medications subscale (SDSCA-MS). We also examined measurement differences by age (<65 vs. ≥65 years) and insulin status. We administered self-report measures to 314 adult outpatients prescribed medications for type 2 diabetes and collected point-of-care HbA1C. One of the 12-item ARMS-D items was identified as less relevant to adherence to diabetes medications and removed. The 11-item ARMS-D had good internal consistency reliability (α=0.86), maintained its factor structure, and had convergent validity with the SDSCA-MS (rho=-0.52, p<0.001). Both the ARMS-D (β=0.16, p<0.01) and the SDSCA-MS (β=-0.12, p<0.05) independently predicted HbA1C after adjusting for covariates, but this association did not hold among participants ≥65 years in subgroup analyses. There were no differences in ARMS-D or SDSCA-MS scores by insulin status, but participants on insulin reported more problems with adherence on two ARMS-D items (i.e., feeling sick and medicine costs). The ARMS-D is a reliable and valid measure of diabetes medication adherence, and is more predictive of HbA1C than the SDSCA-MS, but takes more time to administer. The ARMS-D also identifies barriers to adherence, which may be useful in research and clinical practice.
    Diabetes research and clinical practice 09/2013; 102(2). DOI:10.1016/j.diabres.2013.09.010 · 2.54 Impact Factor
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