Comparison of Commercial and Self-Initiated Weight Loss Programs in People With Prediabetes: A Randomized Control Trial.

OBJECTIVES: To determine if a widely available weight-management program (Weight Watchers) could achieve sufficient weight loss in persons with prediabetes compared with a Diabetes Prevention Program-based individual counseling program supported by National Diabetes Education Program materials. METHODS: We conducted an individual, randomized intervention trial in Indianapolis, Indiana, in 2013 to 2014, in 225 persons with prediabetes. We compared the Weight Watchers weight-management program (n = 112) with Your Game Plan to Prevent Type 2 Diabetes, a program developed by the National Diabetes Education Program. Outcomes were weight and metabolic markers measured at baseline, 6 months, and 12 months. RESULTS: Intervention participants lost significantly more weight than controls at 6 months (5.5% vs 0.8%) and 12 months (5.5% vs 0.2%; both P < .001). The intervention group also had significantly greater improvements in hemoglobin A1c and high-density lipoprotein cholesterol level than did controls. CONCLUSIONS: A large weight-management program is effective for achieving lifestyle changes associated with diabetes prevention. Such programs could significantly increase the availability of diabetes prevention programs worldwide making an immediate and significant public health impact.

Integration of Provider, Pharmacy, and Patient-Reported Data to Improve Medication Adherence for Type 2 Diabetes: A Controlled Before-After Pilot Study.

BACKGROUND: Patients with diabetes often have poor adherence to using medications as prescribed. The reasons why, however, are not well understood. Furthermore, most health care delivery processes do not routinely assess medication adherence or the factors that contribute to poor adherence. OBJECTIVE: The objective of the study was to assess the feasibility of an integrated informatics approach to aggregating and displaying clinically relevant data with the potential to identify issues that may interfere with appropriate medication utilization and facilitate patient-provider communication during clinical encounters about strategies to improve medication use. METHODS: We developed a clinical dashboard within an electronic health record (EHR) system that uses data from three sources: the medical record, pharmacy claims, and a patient portal. Next, we implemented the dashboard into three community health centers. Health care providers (n=15) and patients with diabetes (n=96) were enrolled in a before-after pilot to test the system's impact on medication adherence and clinical outcomes. To measure adherence, we calculated the proportion of days covered using pharmacy claims. Demographic, laboratory, and visit data from the EHR were analyzed using pairwise t tests. Perceived barriers to adherence were self-reported by patients. Providers were surveyed about their use and perceptions of the clinical dashboard. RESULTS: Adherence significantly and meaningfully improved (improvements ranged from 6%-20%) consistently across diabetes as well as cardiovascular drug classes. Clinical outcomes, including HbA1c, blood pressure, lipid control, and emergency department utilization remained unchanged. Only a quarter of patients (n=24) logged into the patient portal and completed psychosocial questionnaires about their barriers to taking medications. CONCLUSIONS: Integrated approaches using advanced EHR, clinical decision support, and patient-controlled technologies show promise for improving appropriate medication use and supporting better management of chronic conditions. Future research and development is necessary to design, implement, and integrate the myriad of EHR and clinical decision support systems as well as patient-focused information systems into routine care and patient processes that together support health and well-being.

An informatics approach to medication adherence assessment and improvement using clinical, billing, and patient-entered data.

The aim of this study was to describe an integrated informatics approach to aggregating and displaying clinically relevant data that can identify problems with medication adherence and facilitate patient-provider communication about strategies to improve medication use. We developed a clinical dashboard within an electronic health record (EHR) system that uses data from three sources: the medical record, pharmacy claims, and a personal health record. The data are integrated to inform clinician-patient discussions about medication adherence. Whereas prior research on assessing patterns of medication adherence focused on a single approach using the EHR, pharmacy data, or patient-entered data, we present an approach that integrates multiple electronic data sources increasingly found in practice. Medication adherence is a complex challenge that requires patient and provider team input, necessitating an integrated approach using advanced EHR, clinical decision support, and patient-controlled technologies. Future research should focus on integrated strategies to provide patients and providers with the right combination of informatics tools to help them adequately address the challenge of adherence to complex medication therapies.

Improving medication adherence for chronic disease using integrated e-technologies.

Diabetes mellitus (DM) is a chronic disease affecting more than 285 people worldwide and the fourth leading cause of death. Increasing evidence suggests that many DM patients have poor adherence with prescribed medication therapies, impacting clinical outcomes. Patients' barriers to medication adherence and the extent to which barriers contribute to poor outcomes, however, are not routinely assessed. We designed a dashboard for an electronic health record system to integrate DM disease and medication data, including patient-reported barriers to adherence. Processes to support routine capture of data from patients are also being explored. The dashboard is being evaluated at multiple ambulatory clinics to examine whether integrated electronic tools can support patient-centered decision-making processes involving complex medication regimens for DM and other chronic diseases.