The pharmacy sector is a key partner in the National Diabetes Prevention Program (National DPP), as pharmacists frequently care for patients at high risk for type 2 diabetes. The Centers for Disease Control and Prevention aimed to increase pharmacist involvement in the program by leveraging partnerships with national pharmacy stakeholders. Continuous stakeholder engagement helped us to better understand the pharmacy sector and its needs. With stakeholders, we developed a guide and promotional campaign. By following a systematic process and including key stakeholders at every step of development, we successfully engaged these valuable partners in national type 2 diabetes prevention efforts. More pharmacy sites (n = 87) are now offering the National DPP lifestyle change program compared to before release of the guide (n = 27).

The Centers for Disease Control and Prevention (CDC) developed a cooperative agreement with health departments in all 50 states and the District of Columbia to strengthen chronic disease prevention and management efforts through the implementation of evidence-based strategies, such as CDC's National Diabetes Prevention Program. The National Diabetes Prevention Program supports organizations to deliver the year-long lifestyle change program that has been proven to prevent or delay the onset of type 2 diabetes among those at high risk. This article describes activities, barriers, and facilitators reported by funded states during the first 3 years (2013-2015) of a 5-year funding cycle.

PROBLEM/CONDITION: Diabetes self-management education (DSME) is a clinical practice intended to improve preventive practices and behaviors with a focus on decision-making, problem-solving, and self-care. The distribution and correlates of established DSME programs in nonmetropolitan counties across the United States have not been previously described, nor have the characteristics of the nonmetropolitan counties with DSME programs. REPORTING PERIOD: July 2016. DESCRIPTION OF SYSTEMS: DSME programs recognized by the American Diabetes Association or accredited by the American Association of Diabetes Educators (i.e., active programs) as of July 2016 were shared with CDC by both organizations. The U.S. Census Bureau's census geocoder was used to identify the county of each DSME program site using documented addresses. County characteristic data originated from the U.S. Census Bureau, compiled by the U.S. Department of Agriculture's Economic Research Service into the 2013 Atlas of Rural and Small-Town America data set. County levels of diagnosed diabetes prevalence and incidence, as well as the number of persons with diagnosed diabetes, were previously estimated by CDC. This report defined nonmetropolitan counties using the rural-urban continuum code from the 2013 Atlas of Rural and Small-Town America data set. This code included six nonmetropolitan categories of 1,976 urban and rural counties (62% of counties) adjacent to and nonadjacent to metropolitan counties. RESULTS: In 2016, a total of 1,065 DSME programs were located in 38% of the 1,976 nonmetropolitan counties; 62% of nonmetropolitan counties did not have a DSME program. The total number of DSME programs for nonmetropolitan counties with at least one DSME program ranged from 1 to 8, with an average of 1.4 programs. After adjusting for county-level characteristics, the odds of a nonmetropolitan county having at least one DSME program increased as the percentage insured increased (adjusted odds ratio [AOR] = 1.10, 95% confidence interval [CI] = 1.08-1.13), the percentage with a high school education or less decreased (AOR = 1.06, 95% CI = 1.04-1.07), the unemployment rate decreased (AOR = 1.19, 95% CI = 1.11-1.23), and the natural logarithm of the number of persons with diabetes increased (AOR = 3.63, 95% CI = 3.15-4.19). INTERPRETATION: In 2016, there were few DMSE programs in nonmetropolitan, socially disadvantaged counties in the United States. The number of persons with diabetes, percentage insured, percentage with a high school education or less, and the percentage unemployed were significantly associated with whether a DSME program was located in a nonmetropolitan county. PUBLIC HEALTH ACTION: Monitoring the distribution of DSME programs at the county level provides insight needed to strategically address rural disparities in diabetes care and outcomes. These findings provide information needed to assess lack of availability of DSME programs and to explore evidence-based strategies and innovative technologies to deliver DSME programs in underserved rural communities.

Collecting self-reported data on adherence to highly active antiretroviral therapy (HAART) can be complicated by patients' reluctance to report poor adherence. The timeliness with which patients attend visits might be a useful alternative to estimate medication adherence. Among Kenyan and Zambian women receiving twice daily HAART, we examined the relationship between self-reported pill taking and timeliness attending scheduled visits. We analyzed data from 566 Kenyan and Zambian women enrolled in a prospective 48-week HAART-response study. At each scheduled clinic visit, women reported doses missed over the preceding week. Self-reported adherence was calculated by summing the total number of doses reported taken and dividing by the total number of doses asked about at the visit attended. A participant's adherence to scheduled study visits was defined as "on time" if she arrived early or within three days, "moderately late" if she was four-seven days late, and "extremely late/missed" if she was more than eight days late or missed the visit altogether. Self-reported adherence was <95% for 29 (10%) of 288 women who were late for at least one study visit vs. 3 (1%) of 278 who were never late for a study visit (odds ratios [OR] 10.3; 95% confidence intervals [95% CI] 2.9, 42.8). Fifty-one (18%) of 285 women who were ever late for a study visit experienced virologic failure vs. 32 (12%) of 278 women who were never late for a study visit (OR 1.7; 95% CI 1.01, 2.8). A multivariate logistic regression model controlling for self-reported adherence found that being extremely late for a visit was associated with virologic failure (OR 2.0; 95% CI 1.2, 3.4). Timeliness to scheduled visits was associated with self-reported adherence to HAART and with risk for virologic failure. Timeliness to scheduled clinic visits can be used as an objective proxy for self-reported adherence and ultimately for risk of virologic failure.