Montori, Victor M

OBJECTIVE—To determine the efficacy of telecare (modem transmission of glucometer data and clinician feedback) to support intensive insulin therapy in patients with type 1 diabetes and inadequate glycemic control. RESEARCH DESIGN AND METHODS—Thirty-one patients with type 1 diabetes on intensive insulin therapy and with HbA1c >7.8% were randomized to telecare (glucometer transmission with feedback) or control (glucometer transmission without feedback) for 6 months. The primary end point was 6-month HbA1c. To place our findings in context, we pooled HbA1c change from baseline reported in randomized trials of telecare identified in a systematic review of the literature. RESULTS—Compared with the control group, telecare patients had a significantly lower 6-month HbA1c (8.2 vs. 7.8%, P = 0.03, after accounting for HbA1c at baseline) and a nonsignificant fourfold greater chance of achieving 6-month HbA1c ≤7% (29 vs. 7%; risk difference 21.9%, 95% CI −4.7 to 50.5). Nurses spent 50 more min/patient giving feedback on the phone with telecare patients than with control patients. Meta-analysis of seven randomized trials of adult patients with type 1 diabetes found a 0.4% difference (95% CI 0–0.8) in HbA1c mean change from baseline between the telecare and control groups. CONCLUSIONS—Telecare is associated with small effects on glycemic control in patients with type 1 diabetes on intensive insulin therapy but with inadequate glycemic control.

OBJECTIVE—The aim of this study was to determine personal characteristics and preferences that affect decision making (decisional attributes) in patients with diabetes. In particular, we were interested in relating these attributes to the choice of using aspirin to reduce cardiovascular risk. RESEARCH DESIGN AND METHODS—We conducted a cross-sectional survey (70% response rate) of 206 diabetic patients (median age, 63 years; 42% women; 91% completed high school; median HbA1c, 8%) attending a tertiary care diabetes clinic. Patients answered a 42-question survey exploring decisional attributes. Medical records provided the source of clinical information. We evaluated sociodemographic, clinical, and decisional predictors of aspirin use. We also conducted a multivariable analysis with aspirin use as a dependent variable. RESULTS—Sixty-seven percent of patients surveyed used aspirin. Patients using aspirin were at higher risk of cardiovascular disease (odds ratio 1.4, 95% CI 1.0–2.1), knew more about the benefits of aspirin (1.9, 1.4–2.6) and less about the risks of aspirin (1.4, 1.2–1.8), and were more certain about using aspirin (0.5, 0.3–0.8) than patients not using aspirin. Patients using aspirin placed a higher value on preventing cardiovascular events than on avoiding the side effects of aspirin. Patients perceived that their diabetes provider and the American Diabetes Association had greater influence on their decision to use aspirin than family members or other patients with diabetes. CONCLUSIONS—The decisional attributes of patients with diabetes are associated with aspirin use. Decisional attributes may be the target of research and interventions to reduce underutilization to levels consistent with patient preferences.

OBJECTIVE—The Mayo Health System Diabetes Translation Project sought to assess models of community-based diabetes care and use of a diabetes electronic management system (DEMS). Planned care is a redesigned model of chronic disease care that involves guideline implementation, support of self-management, and use of clinical information systems. RESEARCH DESIGN AND METHODS—We studied adult diabetic patients attending three primary care practice sites in Wisconsin and Minnesota. We implemented planned care at all sites and DEMS in the practice of 16 primary care providers. We assessed quality of diabetes care using standard indicators for 200 patients randomly selected from each site at baseline and at 24 months of implementation. We used multivariable analyses to estimate the association between planned care and DEMS and each quality indicator. RESULTS—Planned care was associated with improvements in measurement of HbA1c (odds ratio 7.0 [95% CI 4.2–11.6]), HDL cholesterol (5.6 [4.1–7.5]), and microalbuminuria (5.3 [3.5–8.0]), as well as the provision of tobacco advice (6.9 [4.7–10.1]), among other performance measures. DEMS use was associated with improvements in all indicators, including microalbuminuria (3.2 [1.9–5.2]), retinal examination (2.4 [1.5–3.9]), foot examinations (2.3 [1.2–4.4]), and self-management support (2.6 [1.7–3.8]). Although planned care was associated with improvements in metabolic control, we observed no additional metabolic benefit when providers used DEMS. CONCLUSIONS—Planned care was associated with improved performance and metabolic outcomes in primary care. DEMS use augmented the impact of planned care on performance outcomes but not on metabolic outcomes. Optimal identification of the best translation of evidence to diabetes practice will require longer follow-up or new care-delivery models.

OBJECTIVE—We sought to systematically ascertain the quality of randomized controlled trials (RCTs) in diabetes. RESEARCH DESIGN AND METHODS—We identified the 10 most recently published trials as of 31 October 2003 in each of six general medical, five diabetes, and five metabolism and nutrition journals and further enriched our sample with 10 additional RCTs from each of five journals that published the most eligible RCTs in a year. We explored the association between trial characteristics and reporting quality using univariate analyses and a preplanned multivariate regression model. RESULTS—After excluding redundant reports of included trials and one trial that measured outcomes on the health system and not on patients, we included 199 RCTs: 119 assessed physiological and other laboratory outcomes, 42 assessed patient-important outcomes (e.g., morbidity and mortality, quality of life), and 38 assessed surrogate outcomes (e.g., disease progression or regression, HbA1c, cholesterol). Fifty-three percent were of low methodological quality, as were one-third (36–40%) of trials reporting patient-important or surrogate outcomes and two-thirds (64%) of laboratory investigations. Independent predictors of low quality were nonprofit funding source (odds ratio 3.1 [95% CI 1.5–6.2]), measure of physiological and laboratory outcomes (2.3 [1.2–4.4]), and cross-over design (2.3 [1.1–4.8]), all characteristics of laboratory clinical investigations. CONCLUSIONS—There is ample room for improving the quality of diabetes trials. To enhance the practice of evidence-based diabetes care, trialists need to pay closer attention to the rigorous implementation and reporting of important methodological safeguards against bias in randomized trials.