Care Patterns and Outcomes for Hospitalized Patients with Diabetes in Nevada

This study demonstrates substantial differences between Nevada and the national average in patterns of hospital based care in patients with type 2 diabetes. Diabetic patients in Nevada are more likely to be hospitalized through the emergency department, and more likely to be admitted for a condition related to diabetes. Moreover, in Nevada, Medicaid and uninsured patients with diabetes are more likely to experience adverse outcomes then their privately insured counterparts. These differences may be primarily reflective of variances in access to ambulatory care, care seeking behavior, and availability of health services and facilities. Policies promoting expansion of health care benefits to include coverage for people at risk for type 2 diabetes and strengthening the ambulatory care services network, and system in the state, is necessary to reduce discrepancies in patterns of hospitalization and improve outcomes

Compositional Model Repositories via Dynamic Constraint Satisfaction with Order-of-Magnitude Preferences

The predominant knowledge-based approach to automated model construction, compositional modelling, employs a set of models of particular functional components. Its inference mechanism takes a scenario describing the constituent interacting components of a system and translates it into a useful mathematical model. This paper presents a novel compositional modelling approach aimed at building model repositories. It furthers the field in two respects. Firstly, it expands the application domain of compositional modelling to systems that can not be easily described in terms of interacting functional components, such as ecological systems. Secondly, it enables the incorporation of user preferences into the model selection process. These features are achieved by casting the compositional modelling problem as an activity-based dynamic preference constraint satisfaction problem, where the dynamic constraints describe the restrictions imposed over the composition of partial models and the preferences correspond to those of the user of the automated modeller. In addition, the preference levels are represented through the use of symbolic values that differ in orders of magnitude