Programs and Communities

Diabetes, a common chronic condition, effects many individuals causing poor quality of life, expensive medical bills, and devastating medical complications. While health care providers try to manage diabetes during short office visits, many patients still struggle to control their diabetes at home. Lack of diabetes self-management (DSM) is a potential barrier for people with diabetes having to maintain healthy hemoglobin A1cs (HgA1c).

In hopes of addressing this concern, an evidenced-based intervention; diabetic education and phone calls, using the chronic care model as its framework was implemented. The intervention targeted people with type II diabetes at a transitional care setting. Measured variables included HgA1c and DSM. Statistically significant improvements were seen in reported physical activity. Average improvements were seen in HgA1c and DSM after three months of diabetes self-management education (DSME). Attrition, cultural sensitivity, and increasing DSME hours should be further evaluated for future projects.

Background and Purpose: Over 30 million people in the United States (U.S.) have diabetes mellitus, which comprises about 9% of the population, and about 90% of individuals with diabetes have type 2 diabetes (Centers for Disease Control and Prevention [CDC], 2017). Adults with type 2 diabetes at a local internal medicine clinic were consistently having high glycated hemoglobin (HbA1C) levels, demonstrated by data collected from the electronic health record (EHR), and there was no ordering process for referring patients to diabetes management education and support (DSMES) services. The purpose of this project was to improve glycemic control, demonstrated by lower HbA1C levels, and reach a diabetes education attendance rate of 62.5% at an internal medicine clinic in Chandler, Arizona.

Methods: An electronic health record (EHR) template was created and brief staff training was completed to connect patients with diabetes in the community to a local formal diabetes education program. HbA1C levels were measured before and three months after adults with education program. HbA1C levels were measured before and three months after adults with type 2 diabetes mellitus (T2DM) received physicians’ orders for a DSMES program, and rates of attendance to the program were calculated. Data was collected through the EHR and through feedback from the DSMES program. Descriptive statistics were used in data analysis.

Outcomes: The participants’ results did not demonstrate significant differences in pre-referral and post-referral HbA1C results after they were ordered DSMES services (p = .506). The proportion of education attendance (30%) was lower than the project goal of 62.5%, but increased from the clinic baseline.

Conclusions: EHR template implementation for referral to DSMES may increase rates of formal diabetes education and improve glycemic control. Larger sample sizes, longer project periods, alternative methods of communication, and increased follow-up of participants may be required to produce significant results.

Background: The global prevalence of all types of diabetes increased from 108 million in 1980 to 422 million in 2014 (Nazir et al., 2018). The Centers for Disease Control and Prevention (2017) ranks diabetes as the 7th leading cause of death in the United States with an estimated annual expense of $327 billion. Within the rural setting, patients typically have less resources available for the treatment and self-management of their diseases. It is important to explore self-management techniques that can be utilized by patients with type 2 diabetes living in rural areas. Research demonstrating the importance of education, exercise, diet, glucose monitoring, medications, and supportive measures is prominent throughout the literature.

Objective: The purpose of this Doctor of Nursing Practice (DNP) applied project is to investigate the effects of delivering biweekly text messages containing diabetes self-management education (DSME) materials to patients in an effort to support successful self-care.

Methods: During an 8 week period, DSME was provided via text messaging, bi-weekly (Sunday and Wednesday), to 23 rural participants with type 2 diabetes, in a family clinic in Payson, Arizona. Participants were asked to complete the Skills, Confidence, and Preparedness Index both pre- and post-intervention to evaluate their knowledge of diabetes self-management.

Results: Twenty-three adults aged 52 to 78 years (M = 64.91) participated in the project. Of the participants, 57% (13/23) were female. The majority of participants had T2DM diagnosis less than 10 years (M=13.8 years). There was a statistical difference between the pre- and post-Skills, Confidence and Preparedness Index questionnaire (p < .001) indicating an improvement in self-efficacy scores post- intervention.

Conclusion: DSME delivered via text message is a cost-effective way to increase patients' self-efficacy and potentially improve their ability to successfully self-manage their disease.

The New Jersey Childhood Obesity Study was designed to provide vital information for planning, implementing, and evaluating interventions aimed at preventing childhood obesity in five New Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. These five communities are being supported by the Robert Wood Johnson Foundation’s New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity. Effective interventions for addressing childhood obesity require community-specific information on

who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community. Based on comprehensive research, a series of reports are being prepared for each community to assist in planning effective interventions.

The main components of the study were:

• A household telephone survey of 1700 families with 3–18 year old children,

• De-identified heights and weights measured at public schools,

• Assessment of the food and physical activity environments using objective data.

This report presents the results from the household survey. Reports based on school body mass index (BMI) data and food and physical activity environment data are available at www.cshp.rutgers.edu/childhoodobesity.htm.

The maps in this chartbook describe the food environment in ewark in terms of access to supermarkets, smaller grocery stores, convenience stores, and limited service restaurants. Research shows that when residents have access to healthy food outlets, they tend to eat healthy.

• Food environment maps were created using geo-coded commercially available data of food outlets (InfoUSA, 2008 and Trade Dimensions, 2008) in Newark and in a 1 mile buffer area around Newark.

•Using the commercial data and additional investigation, food outlets were classified into different categories based on their likelihood of carrying healthy choices: supermarkets carry most healthy choices; smaller grocery stores carry fewer healthy choices; convenience stores and limited service restaurants are likely to carry mostly unhealthy choices.

• Access to different types of food outlets was computed at the census block group level based on concentration of stores / restaurants per unit area and is reported as food outlet densities.

• Food outlet density maps are compared with Census 2000 data to visualize accessibility of healthy foods in neighborhoods with different characteristics.

Data Sources: Info USA food outlet 2008 data

Trade Dimensions food outlet 2008 data

Census 2000 data

New Jersey Department of Education 2008-2009 data

The maps in this chartbook describe the food environment in Trenton in terms of access to supermarkets, smaller grocery stores, convenience stores, and limited service restaurants. Research shows that when residents have access to healthy food outlets, they tend to eat healthy.

•Food environment maps were created using geo-coded commercially available data of food outlets (InfoUSA, 2008 and Trade Dimensions, 2008) in Trenton and in a 1 mile buffer area around Trenton.

•Using the commercial data and additional investigation, food outlets were classified into different categories based on their likelihood of carrying healthy choices: supermarkets carry most healthy choices; smaller grocery stores carry fewer healthy choices; convenience stores and limited service restaurants are likely to carry mostly unhealthy choices.

• Access to different types of food outlets was computed at the census block group level based on concentration of stores / restaurants per unit area and is reported as food outlet densities.

•Food outlet density maps are compared with Census 2000 data to visualize accessibility of healthy foods in neighborhoods with different characteristics.

Data Sources: Info USA food outlet 2008 data

Trade Dimensions food outlet 2008 data

Census 2000 data

New Jersey Department of Education 2008-2009 data

Diabetes is a leading cause of morbidity in the world. About 42 million people worldwide have
diabetes. Poorly managed diabetes leads to long term complications and mortality. Diabetes self-management education (DSME) has been effective in preventing or delaying complications.The purpose of this project is to implement a diabetes self-management education (DSME)
program in primary care and to evaluate its impact on glycemic control and diabetes knowledge in a selected group of adults 18 years or older in a community-based practice.

Interprofessional collaboration (IP) is an approach used by healthcare organizations to improve the quality of care. Studies examining effects of IP with patients with type 2 diabetes mellitus (T2DM) have shown improvement in A1C, blood pressure, lipids, self-efficacy and overall greater knowledge of disease process and management. The purpose of this project was to evaluate the impact of IP with attention to identifying and addressing social needs of patients with T2DM. Participants at least 18 years of age with an A1C >6.5% were identified; Spanish speaking patients were included in this project. The intervention included administration of Health Leads questionnaire to assess social needs. Monthly in person or phone meetings were conducted during a 3-month period.

The patient had the option to meet with the doctor of nursing practice (DNP) student as well as other members of the team including the clinical pharmacist and social work intern. Baseline A1C levels were extracted from chart at 1st monthly meeting. Post A1C levels were drawn at the 3 month follow up with their primary care provider. Study outcomes include the difference in A1C goal attainment, mean A1C and patient satisfaction. Pre A1C levels in participants ranged from 7.1% to 9.8% with a mean of 8.3%. Post A1C levels ranged from 6.9% to 8.6% with a mean of 7.7%. Two cases were excluded as they did not respond to the intervention. A paired-samples t test was calculated to compare the mean pre A1C level to the post A1C level. The mean pre A1C level was 8.24 (sd .879), and the post A1C level was 7.69 (sd .631). A significant decrease from pre to post A1C levels was found (t (6) = 2.82, p<.05).

The prevalence of Type 2 Diabetes is on the rise, as are the costs. This nation’s healthcare system must promote interprofessional collaboration and do a better job of addressing SDOH to more effectively engage patients in the management of their disease.