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.

Children often present to the emergency department (ED) for treatment of abuse-related injuries. ED healthcare providers (HCPs) do not consistently screen children for physical abuse, which may allow abuse to go undetected and increases the risk for re-injury and death. ED HCPs frequently cite lack of knowledge or confidence in screening for and detecting child physical abuse.

The purpose of this evidence-based quality improvement project was to implement a comprehensive screening program that included ED HCP education on child physical abuse, a systematic screening protocol, and use of the validated Escape Instrument. After a 20-minute educational session, there was a significant increase in ED HCP knowledge and confidence scores for child physical abuse screening and recognition (p < .001). There was no difference in diagnostic coding of child physical abuse by ED HCPs when evaluating a 30-day period before and after implementation of the screening protocol.

In a follow-up survey, the Escape Instrument and educational session were the most reported screening facilitators, while transition to a new electronic health system was the most reported barrier. The results of this project support comprehensive ED screening programs as a method of improving HCP knowledge and confidence in screening for and recognizing child physical abuse. Future research should focus on the impact of screening on the diagnosis and treatment of child physical abuse. Efforts should also be made to standardize child abuse screening programs throughout all EDs, with the potential for spread to other settings.