To the Editor: Statin drugs are underused in older adults.1 Sex and racial disparities, with poorer low-density lipoprotein cholesterol (LDL-C) control in women and nonwhites, have been described in some but not all studies.2–7 It was hypothesized that telemedicine with case management could improve statin use and LDL-C goal attainment in ethnically diverse older adults. The Informatics for Diabetes Education and Telemedicine (IDEATel) project randomized older, medically underserved Medicare beneficiaries with diabetes mellitus (N=1,665) to receive usual care from their primary care provider (PCP) or a telemedicine intervention.8 Better hemoglobin A1c, blood pressure, and LDL-C levels were previously reported in intervention subjects.9 This report examines the effects of telemedicine on statin therapy and attainment of LDL-C goals and the mediating role of statin use on reduction in LDL-C levels in IDEATel participants over 5 years of follow-up during 2000 to 2007.

The mean age at randomization was 71, and mean duration of diabetes mellitus was 11 years; approximately 49% were white, 35% Hispanic, and 15% African American. Baseline LDL-C levels were 108 mg/dL in the usual care group (n=791) and 107 mg/dL in the telemedicine intervention group (n=819). High-density lipoprotein cholesterol levels at baseline were 47 mg/dL in the control and intervention groups and did not change significantly over time.

Baseline lipid measurement results and practice guidelines were sent to all subjects and their PCPs. Subjects randomized to the telemedicine intervention discussed these results with nurse case managers during home televisits, and treatment recommendations were sent to PCPs.

Analyses were adjusted for clustering caused by randomization within PCP. Variables associated with statin use and LDL-C goal attainment were assessed using the SAS Glimmix macro (SAS Institute, Inc., Cary, NC). A binary distribution was assumed for the outcome variable using the logit link and residual pseudo-likelihood estimation method. A first-order auto-regressive covariance structure was used for statin analyses and a compound symmetry covariance structure for LDL-C goal attainment. SAS PROC Genmod was used to perform sensitivity analyses. Mediating effects of statin use were examined by performing tests of the mediating path coefficients.10

The use of statin drugs increased over time in both groups (P<.001), but the telemedicine group used significantly more statin therapy over time (P=.02). The estimated increase in statin use from baseline to study end was 10% in the control group and 18% in the intervention group. Having heart disease at baseline predicted an increase in statin use (P<.001). Hispanics used significantly less statin therapy than non-Hispanic whites (P=.04). Sensitivity analyses showed similar results.

As expected, participants taking statin drugs had a greater attainment of LDL-C less than 100 mg/dL (P<.001) and less than 130 mg/dL over the 5-year follow-up (P<.001). Statin use was highly related to achievement of LDL-C less than 100 mg/dL. Although attainment of LDL-C less than 100 mg/dL goal was 64% in usual care, versus 73% in telemedicine participants by the fifth follow-up (P=.10 for the overall effect, treating LDL-C as binary), the proportion of participants meeting this goal among those taking statins was similar in each group (69.1% and 71.8%). Women were significantly less likely to attain LDL-C goals of less than 100 mg/dL and less than 130 mg/dL over the 5 years of follow-up than men (P=.002 and P<.001, respectively).

The primary analyses of LDL-C9 showed a significant effect of the telemedicine intervention on lowering LDL-C when it was treated as a continuous variable (P<.001); additional analyses demonstrated that statin use mediated this effect (P=.045, P<.001). Telemedicine increased statin use (Figure 1).

Figure 1.

 Path diagram depicting the direct and indirect effects of the telemedicine intervention, through statin use, on continuous low-density lipoprotein cholesterol (LDL-C). Time was centered to avoid colinearity. Statin use was treated as a time-varying covariate. Mediating effects were estimated using SAS PROC Mixed with nonlinear terms. Baseline data and up to 5 years of follow-up were included. Nonlinear models with exponential (e−time) terms to model nonlinearity with compound symmetry covariance structure were used.

A significant mediating effect of statin use was observed, in that telemedicine operating through increased statin use resulted in significant reductions in LDL-C. In general, the decline in LDL-C was greater in those taking statins, regardless of intervention group status, although those in the telemedicine group who used statins experienced the lowest levels of LDL-C over time (Figure 2).

Figure 2.

 Five-year results for continuous low-density lipoprotein cholesterol (LDL-C) levels (adjusted mean; mg/dL) in usual care and telemedicine intervention groups according to statin use.

In conclusion, the telemedicine intervention increased statin use and lowered LDL-C levels in older underserved adults with diabetes mellitus. The effect of telemedicine on LDL-C was achieved in part through the initiation or intensification of statin treatment. A majority of participants received statin therapy and attained LDL-C goals, but sex and ethnic disparities were observed. Additional approaches are needed to improve LDL-C goal attainment in these underserved groups.


Conflicts of Interest: Dr. Weinstock has received research funding from the National Institute of Diabetes and Digestive and Kidney Diseases, New York State Department of Health, GlaxoSmithKline, Eli Lilly, Pfizer, Novartis, Bristol-Myers Squibb, Biodel, NovoNordisk, Sanofi-Aventis, Merck, and Diamyd.

Dr. Shea has research funding from the National Heart, Lung and Blood Institute, the Health Resources and Services Administration, and the American Cancer Society. This work was supported by Cooperative Agreement with the Center for Medicare and Medicaid Services (CMS) (95-C-90998).

Author Contributions: Ruth S. Weinstock, Walter Palmas, Jeanne A. Teresi, and Steven Shea: study concept and design, acquisition of subjects and data, analysis and interpretation of data, preparation of manuscript. Roberto Izquierdo and Robin Goland: Acquisition of subjects and/or data, interpretation of data, preparation of manuscript. Joseph P. Eimicke: analysis and preparation of manuscript.

Sponsor's Role: The funding agency had the opportunity to comment on the letter before submission but did not participate in the analysis of the data or the writing of the letter. The inferences, conclusions, and opinions expressed in the letter are those of the authors and do not represent the position of CMS.