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.

Phoenix is the sixth most populated city in the United States and the 12th largest metropolitan area by population, with about 4.4 million people. As the region continues to grow, the demand for housing and jobs within the metropolitan area is projected to rise under uncertain climate conditions.

Undergraduate and graduate students from Engineering, Sustainability, and Urban Planning in ASU’s Urban Infrastructure Anatomy and Sustainable Development course evaluated the water, energy, and infrastructure changes that result from smart growth in Phoenix, Arizona. The Maricopa Association of Government's Sustainable Transportation and Land Use Integration Study identified a market for 485,000 residential dwelling units in the urban core. Household water and energy use changes, changes in infrastructure needs, and financial and economic savings are assessed along with associated energy use and greenhouse gas emissions.

The course project has produced data on sustainable development in Phoenix and the findings will be made available through ASU’s Urban Sustainability Lab.

Hybrid system models - those devised from two or more disparate sub-system models - provide a number of benefits in terms of conceptualization, development, and assessment of dynamical systems. The decomposition approach helps to formulate complex interactions that are otherwise difficult or impractical to express. However, hybrid model development and usage can introduce complexity that emerges from the composition itself.

To improve assurance of model correctness, sub-systems using disparate modeling formalisms must be integrated above and beyond just the data and control level; their composition must have model specification and simulation execution aspects as well. Poly-formalism composition is one approach to composing models in this manner.

This dissertation describes a poly-formalism composition between a Discrete EVent System specification (DEVS) model and a Cellular Automata (CA) model types. These model specifications have been chosen for their broad applicability in important and emerging domains. An agent-environment domain exemplifies the composition approach. The inherent spatial relations within a CA make it well-suited for environmental representations. Similarly, the component-based nature of agents fits well within the hierarchical component structure of DEVS.

This composition employs the use of a third model, called an interaction model, that includes methods for integrating the two model types at a formalism level, at a systems architecture level, and at a model execution level. A prototype framework using DEVS for the agent model and GRASS for the environment has been developed and is described. Furthermore, this dissertation explains how the concepts of this composition approach are being applied to a real-world research project.

This dissertation expands the tool set modelers in computer science and other disciplines have in order to build hybrid system models, and provides an interaction model for an on-going research project. The concepts and models presented in this dissertation demonstrate the feasibility of composition between discrete-event agents and discrete-time cellular automata. Furthermore, it provides concepts and models that may be applied directly, or used by a modeler to devise compositions for other research efforts.