Programs and Communities

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.

Early and effective end-of-life care are associated with increased quality of life for those patients who may be nearing the end-of-life (EOL). However, evidence suggests that most non-palliative healthcare providers lack the skills and confidence to initiate EOL conversations. Consequently, about 70% of Americans would prefer to die at home with their families, yet only 25% die according to their wishes (State of California Department of Justice, n.d). In alignment with the Peaceful End of Life Theory, the purpose of this evidence-based project is to increase primary healthcare providers’ level of skills and confidence in end-of-life discussions.

This project utilized a pre and post study design. A total of 11 participants were recruited using convenience sampling from three primary care clinics in Phoenix, Arizona. Due to the small sample size and assumption of a non-normal distribution of the data, Wilcoxon Signed Ranks test and Pearson correlation coefficient were used for statistical analysis. There were clinical and statistical significant improvements in the EOL knowledge of the participants after the implementation of the two-and-a-half-hour Serious Illness Care Program (Z = -2.950, p = .003) with a large effect size (r = -0.62).

The project evaluation also demonstrated that most participants deemed that the intervention was effective. A brief and systematic education session, such as the SICP can be utilized to improve non-palliative healthcare providers’ skills in having more and effective end-of-life conversations.

Disease burden is higher in the United States than in comparable countries. The Patient Self Determination Act of 1990 requires healthcare facilities to provide Advance Care Planning (ACP) information to all Medicare patients. The healthcare staffs’ (n=7) commitment to 3-days of ACP training increase ACP rates in the primary care setting. The Medicare Incentive Program is the platform for this initiative. This quantitative project used a valid and reliable pre and posttest design that consisted of 27 items on a Likert-scale. A 3.5-month chart audit (n=91) was conducted to assess the completion rate. Descriptive statistics was used to describe the demographic data.

The results of the two-tailed Wilcoxon signed rank test were significant based on an alpha value of 0.05, V = 0.00, z = -2.37, p = .018. There was a significant increase in the post-readiness to change average scores. A Mann Whitney test was used to analyze the statistically significant difference between the averages in two ACP types and electronic health record documentation (EHR). Staff did not always code (Mdn = 0.00) but they documented in the EHR (Mdn =1.00; 512.00, p = 0.003). ACP discussion was performed 63% of the time during Annual Wellness Visits (AWV), and there was a 49% increase in the EHR documentation. Trained staff are key stakeholders in guiding ACP conversations. They understand the barriers, impact, and consequences related to the lack of advance directives.

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.