Diabetes Self-Management Models to Reduce Health Disparities (P20-P2)

Primary Outcome Measures:

• HbA1c [ Time Frame: 12 months ]
  Measures of HbA1c were collected from electronic health records dating back six months prior to orientation to the last day of study participation (45 days after the 12-month follow-up period). If a participant did not have any HbA1c value within the electronic health record for any particular follow-up visit, a lab test was scheduled to obtain a measure. Of the HbA1c collected six months prior to orientation, the value measured closest to the orientation date was considered as the baseline HbA1c value. HbA1c values that were measured on dates preceding the baseline HbA1c were not included; i.e., HbA1c values included in the analysis were those collected since the baseline HbA1c and until the last day of study participation.
  
  

Secondary Outcome Measures:

• BMI [ Time Frame: 12 months ]
  Body mass index
  
  
• Patient Self-reported Perceived Health Status [ Time Frame: 12 months ]
  
• Diabetes-related Behaviors [ Time Frame: 12 months ]
  Participants were asked the number of days in the past 7 which they participated in various diabetes self-care activities on diet, exercise, home blood glucose monitoring, and foot care.
  
  
• Quality of Life (QOL) [ Time Frame: 12 months ]
  Participants where asked the number of days in the past 30 days in which their physical (phys) and/or mental was not good, and whether their usual activity was affected by their physical/mental health.
  
  

Despite concerted federal and state attempts to reduce health disparities over the past decades substantial disparities in reported rates of chronic disease for minorities still exist. In particular, African Americans and Hispanics experience higher rates of Type 2 diabetes (T2DM), and cardiovascular disease (CVD) than do other segments of the U.S. population. The objectives of this proposed research project are to test two different diabetes self-management (DSM) programs in a large multi-site health care organization in Central Texas that serves large populations of minority and rural residents, comparing outcomes in order to evaluate their efficacy for reducing health disparities. Our specific aims are to: 1) document the nature and magnitude of extant health disparities in diabetes treatment processes and outcomes; 2) evaluate different DSM intervention approaches on behavioral and clinical outcomes, with attention to differential effects by patient and environmental characteristics; 3) examine the cost-effectiveness of these different approaches to DSM education in minority and rural populations; and 4) explore the reach of our intervention efforts and the broader organizational impacts of DSM education, including feedback loops to clinicians and organizational receptivity to self-management approaches. Our study will employ four different activities: 1) an initial electronic chart review of 1300 records of adults; 2) a 2 by 2 open 24 month randomized clinical trial of behaviorally and technologically based DSM interventions with 400 adults age 21 and older who have type 2 diabetes (T2DM); 3) a cost-effectiveness analysis of the different treatment approaches; and 4) surveys of primary care providers and health care administrators. While our primary outcome will be reductions in hemoglobin A1c (HbA1c), our conceptual model includes clinical, behavioral, economic and organizational outcomes. We will also assess the extent to which our interventions reduce health disparities by examining differential treatment success. This study is innovative in its comparison of both behavioral and technological intervention approaches, its attention to the public health impact and cost-effectiveness of different intervention approaches, and its concern with organizational responses to intervention sustainability. A noteworthy significance will be the strengthening of the linkages between clinical and community treatment approaches and the identification of successful treatment strategies in different settings and populations.