Programs and Communities

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.

The human papillomavirus (HPV) is a sexually transmitted infection (STI) that is associated with several types of cancer and genital warts. No cure exists for those currently infected with HPV, but a vaccine is available that can prevent the virus and development of cancers associated with HPV. Military servicemembers are at a high risk for contracting HPV; it is one of the most common STIs among active duty service members. The health consequences of HPV can impact a servicemember’s military readiness. The HPV vaccine is not required for military servicemembers, but it is offered free of charge. HPV vaccination rates among military service members remain relatively low.

The purpose of this evidence-based project was to increase the level of knowledge about HPV, improve health beliefs regarding HPV, increase HPV vaccine intention, recommendation, and uptake. Using the Health Belief Model as an organizing framework, a population targeted eight-minute education video on HPV and HPV vaccination was developed. It was implemented at an outpatient military treatment facility located in the southwest United States over a 6-week period, to newly reported service members. Participants included 116 military service members aged 18 to 45. A pretest and posttest questionnaire were used to assess the impact of the intervention. HPV level of knowledge increased significantly from pretest to posttest mean scores were 3.00 to 4.39 respectively (p < .001). HPV vaccine intention increased from 62% to 66% (p = .739). HPV vaccine recommendation increased from 62% to 85% (p < .001).

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.