Ontology driven integration platform for clinical and translational research

Semantic Web technologies offer a promising framework for integration of disparate biomedical data. In this paper we present the semantic information integration platform under development at the Center for Clinical and Translational Sciences (CCTS) at the University of Texas Health Science Center at Houston (UTHSC-H) as part of our Clinical and Translational Science Award (CTSA) program. We utilize the Semantic Web technologies not only for integrating, repurposing and classification of multi-source clinical data, but also to construct a distributed environment for information sharing, and collaboration online. Service Oriented Architecture (SOA) is used to modularize and distribute reusable services in a dynamic and distributed environment. Components of the semantic solution and its overall architecture are described.

Human Trafficking, Sex Tourism, and Child Exploitation on the Southern Border

Human trafficking and various other forms of child sexual exploitation on the United States-Mexico border are described from social science and law enforcement perspectives, including current laws and definitions, case examples, and descriptions of victims and traffickers. The Southern Border Initiative of the AMBER Alert Project is outlined as one effort to combat trafficking through collaboration between law enforcement agencies and programs in the United States and Mexico. Policy recommendations include increasing knowledge and collaboration between law enforcement, social service agencies, and judicial systems across the border region and between the United States and Mexico.

THE APPLICATION OF CIRRHOSIS MORTALITY AND SUICIDE MORTALITY AS INDICATORS FOR ALCOHOLISM PLANNING

This study provides a review of the current alcoholism planning process of the Houston-Galveston planning process of the Houston-Galveston Area Council, an agency carrying out planning for a thirteen county region in surrounding Houston, Texas. The four central groups involved in this planning are identified, and the role that each plays and how it effects the planning outcomes is discussed.^ The most substantive outcome of the Houston-Galveston Area Council's alcoholism planning, the Regional Alcoholism/Alcohol Abuse Plan is examined. Many of the shortcomings in the data provided, and the lack of other data necessary for planning are offered.^ A problem oriented planning model is presented as an alternative to the Houston-Galveston Area Council's current service oriented approach to alcoholism planning. Five primary phases of the model, identification of the problem, statement of objectives, selection of alternative programs, implementation, and evaluation, are presented, and an overview of the tasks involved in the application of this model to alcoholism planning is offered.^ A specific aspect of the model, the use of problem status indicators is explored using cirrhosis and suicide mortality data. A review of the literature suggests that based on five criteria, availability, subgroup identification, validity, reliability, and sensitivity, both suicide and cirrhosis are suitable as indicators of the alcohol problem when combined with other indicators.^ Cirrhosis and suicide mortality data are examined for the thirteen county Houston-Galveston Region for the years 1969 through 1976. Data limitations preclude definite conclusions concerning the alcohol problem in the region. Three hypotheses about the nature of the regional alcohol problem are presented. First, there appears to be no linear trend in the number of alcoholics that are at risk of suicide and cirrhosis mortality. Second, the number of alcoholics in the metropolitan areas seems to be greater than the number of rural areas. Third, the number of male alcoholics at risk of cirrhosis and suicide mortality is greater than the number of female alcoholics.^

PROJECTION OF HEALTH DEMAND IN TERMS OF HOSPITAL ADMISSIONS FOR SELECTED DIAGNOSES IN HEALTH SYSTEMS AGENCY SERVICE AREAS

The National Health Planning and Resources Development Act of 1974 (Public Law 93-641) requires that health systems agencies (HSAs) plan for their health service areas by the use of existing data to the maximum extent practicable. Health planning is based on the identificaton of health needs; however, HSAs are, at present, identifying health needs in their service areas in some approximate terms. This lack of specificity has greatly reduced the effectiveness of health planning. The intent of this study is, therefore, to explore the feasibility of predicting community levels of hospitalized morbidity by diagnosis by the use of existing data so as to allow health planners to plan for the services associated with specific diagnoses.^ The specific objectives of this study are (a) to obtain by means of multiple regression analysis a prediction equation for hospital admission by diagnosis, i.e., select the variables that are related to demand for hospital admissions; (b) to examine how pertinent the variables selected are; and (c) to see if each equation obtained predicts well for health service areas.^ The existing data on hospital admissions by diagnosis are those collected from the National Hospital Discharge Surveys, and are available in a form aggregated to the nine census divisions. When the equations established with such data are applied to local health service areas for prediction, the application is subject to the criticism of the theory of ecological fallacy. Since HSAs have to rely on the availability of existing data, it is imperative to examine whether or not the theory of ecological fallacy holds true in this case.^ The results of the study show that the equations established are highly significant and the independent variables in the equations explain the variation in the demand for hospital admission well. The predictability of these equations is good when they are applied to areas at the same ecological level but become poor, predominantly due to ecological fallacy, when they are applied to health service areas.^ It is concluded that HSAs can not predict hospital admissions by diagnosis without primary data collection as discouraged by Public Law 93-641. ^