Clinical Inertia in a Randomized Trial of Telemedicine-Based Chronic Disease Management: Lessons Learned.

BACKGROUND: Treatment nonadherence and clinical inertia perpetuate poor cardiovascular disease (CVD) risk factor control. Telemedicine interventions may counter both treatment nonadherence and clinical inertia. INTRODUCTION: We explored why a telemedicine intervention designed to reduce treatment nonadherence and clinical inertia did not improve CVD risk factor control, despite enhancing treatment adherence versus usual care. METHODS: In this analysis of a randomized trial, we studied recipients of the 12-month telemedicine intervention. This intervention comprised two nurse-administered components: (1) monthly self-management education targeting improved treatment adherence; and (2) quarterly medication management facilitation designed to support treatment intensification by primary care (thereby reducing clinical inertia). For each medication management facilitation encounter, we ascertained whether patients met treatment goals, and if not, whether primary care recommended treatment intensification following the encounter. We assessed disease control associated with encounters, where intensification was/was not recommended. RESULTS: We examined 455 encounters across 182 intervention recipients (100% African Americans with type 2 diabetes). Even after accounting for valid reasons for deferring intensification (e.g., treatment nonadherence), intensification was not recommended in 67.5% of encounters in which hemoglobin A1c was above goal, 72.5% in which systolic blood pressure was above goal, and 73.9% in which low-density lipoprotein cholesterol was above goal. In each disease state, treatment intensification was more likely with poorer control. CONCLUSIONS: Despite enhancing treatment adherence, this intervention was unsuccessful in countering clinical inertia, likely explaining its lack of effect on CVD risk factors. We identify several lessons learned that may benefit investigators and healthcare systems.

Jump starting shared medical appointments for diabetes with weight management: Rationale and design of a randomized controlled trial.

BACKGROUND: Rates of glycemic control remain suboptimal nationwide. Medication intensification for diabetes can have undesirable side effects (weight gain, hypoglycemia), which offset the benefits of glycemic control. A Shared Medical Appointment (SMA) intervention for diabetes that emphasizes weight management could improve glycemic outcomes and reduce weight while simultaneously lowering diabetes medication needs, resulting in less hypoglycemia and better quality of life. We describe the rationale and design for a study evaluating a novel SMA intervention for diabetes that primarily emphasizes low-carbohydrate diet-focused weight management. METHODS: Jump Starting Shared Medical Appointments for Diabetes with Weight Management (Jump Start) is a randomized, controlled trial that is allocating overweight Veterans (body mass index≥27kg/m2) with type 2 diabetes into two arms: 1) a traditional SMA group focusing on medication management and self-management counseling; or 2) an SMA group that combines low-carbohydrate diet-focused weight management (WM/SMA) with medication management. Hemoglobin A1c reduction at 48weeks is the primary outcome. Secondary outcomes include hypoglycemic events, diabetes medication use, weight, medication adherence, diabetes-related quality of life, and cost-effectiveness. We hypothesize that WM/SMA will be non-inferior to standard SMA for glycemic control, and will reduce hypoglycemia, diabetes medication use, and weight relative to standard SMA, while also improving quality of life and costs. CONCLUSIONS: Jump Start targets two common problems that are closely related but infrequently managed together: diabetes and obesity. By focusing on diet and weight loss as the primary means to control diabetes, this intervention may improve several meaningful patient-centered outcomes related to diabetes.

Assessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus.

OBJECTIVE: We assessed the sensitivity and specificity of 8 electronic health record (EHR)-based phenotypes for diabetes mellitus against gold-standard American Diabetes Association (ADA) diagnostic criteria via chart review by clinical experts. MATERIALS AND METHODS: We identified EHR-based diabetes phenotype definitions that were developed for various purposes by a variety of users, including academic medical centers, Medicare, the New York City Health Department, and pharmacy benefit managers. We applied these definitions to a sample of 173 503 patients with records in the Duke Health System Enterprise Data Warehouse and at least 1 visit over a 5-year period (2007-2011). Of these patients, 22 679 (13%) met the criteria of 1 or more of the selected diabetes phenotype definitions. A statistically balanced sample of these patients was selected for chart review by clinical experts to determine the presence or absence of type 2 diabetes in the sample. RESULTS: The sensitivity (62-94%) and specificity (95-99%) of EHR-based type 2 diabetes phenotypes (compared with the gold standard ADA criteria via chart review) varied depending on the component criteria and timing of observations and measurements. DISCUSSION AND CONCLUSIONS: Researchers using EHR-based phenotype definitions should clearly specify the characteristics that comprise the definition, variations of ADA criteria, and how different phenotype definitions and components impact the patient populations retrieved and the intended application. Careful attention to phenotype definitions is critical if the promise of leveraging EHR data to improve individual and population health is to be fulfilled.

Managing hyperglycemia and diabetes in patients receiving enteral feedings: A health system approach.

Evidence of poor outcomes in hospitalized patients with hyperglycemia has led to new and revised guidelines for inpatient management of diabetes. As providers become more aware of the need for better blood glucose control, they are finding limited guidance in the management of patients receiving enteral nutrition. To address the lack of guidelines in this population, Duke University Health System has developed a consistent practice for managing such patients. Here, we present our practice strategies for insulin use in patients receiving enteral nutrition. Essential factors include assessing the patients' history of diabetes, hyperglycemia, or hypoglycemia and timing and type of feedings. Insulin practices are then designed to address these issues keeping in mind patient safety in the event of abrupt cessation of nutrition. The outcome of the process is a consistent and safe method for glucose control with enteral nutrition.