4 resultados para Joint research projects

em DigitalCommons@The Texas Medical Center


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Study objective. This was a secondary data analysis of a study designed and executed in two phases in order to investigate several questions: Why aren't more investigators conducting successful cross-border research on human health issues? What are the barriers to conducting this research? What interventions might facilitate cross-border research? ^ Methods. Key informant interviews and focus groups were used in Phase One, and structured questionnaires in Phase Two. A multi-question survey was created based on the findings of focus groups and distributed to a wider circle of researchers and academics for completion. The data was entered and analyzed using SPSS software. ^ Setting. El Paso, TX located on the U.S-Mexico Border. ^ Participants. Individuals from local academic institutions and the State Department of Health. ^ Results. From the transcribed data of the focus groups, eight major themes emerged: Political Barriers, Language/Cultural Barriers, Differing Goals, Geographic Issues, Legal Barriers, Technology/Material Issues, Financial Barriers, and Trust Issues. Using these themes, the questionnaire was created. ^ The response rate for the questionnaires was 47%. The largest obstacles revealed by this study were identifying a funding source for the project (47% agreeing or strongly agreeing), difficulties paying a foreign counterpart (33% agreeing or strongly agreeing) and administrative changes in Mexico (31% agreeing or strongly agreeing). ^ Conclusions. Many U.S. investigators interested in cross-border research have been discouraged in their efforts by varying barriers. The majority of respondents in the survey felt financial issues and changes in Mexican governments were the most significant obstacles. While some of these barriers can be overcome simply by collaboration among motivated groups, other barriers may be more difficult to remove. Although more evaluation of this research question is warranted, the information obtained through this study is sufficient to support creation of a Cross-Border Research Resource Manual to be used by individuals interested in conducting research with Mexico. ^

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Retinitis pigmentosa (RP) is a name given to a group of inherited retinal dystrophies that lead to progressive photoreceptor degeneration, and thus, visual impairment. It is evident at both the clinical and the molecular level that these are heterogeneous disorders, with wide variation in severity, mode of inheritance, and phenotype. The genetics of RP are not simple; the disease can be inherited in dominant, recessive, X-linked, and digenic modes. Autosomal dominant RP (adRP) results from mutations in at least ten mapped loci, but there may be dozens of genetic loci where mutations can cause RP. To date, there are over a hundred genes known to cause retinal degenerative diseases, and less than half of these have been cloned (RetNet). Among the dozens of retinitis pigmentosa loci known to exist, only a few have been identified and the remainders are inferred from linkage studies. Today, the genes for seven of the twelve-adRP loci have been identified, and these are rhodopsin, peripherin/RDS, NRL, ROM1, CRX, RP13 and RP1. My research projects involved a combination of the continued search for genes involved in retinal dystrophies, as well the investigation into the role of peripherin/RDS and RP1 in the disease etiology of autosomal dominant RP. ^ Most of the mutations leading to inherited retinal disorders have been identified in predominately retina expressed genes like rhodopsin, peripherin/RDS, and RP1. Expressed sequence tags (ESTs) that were retina-specific were culled from sequence databases and, together with laboratory analysis, were analyzed as potential candidate genes for retinal dystrophies. Thirteen of the fifty-five identified retina-specific ESTs mapped to within candidate regions for inherited retinopathies. One of these is RP1L1, a homologue of RP1 and a potential cause of adRP. ^ Once a disease-associated gene has been identified, elucidating the role of that gene in the visual process is essential for understanding what happens when the process is defective as it is in adRP. My next projects involved investigating the role of a novel 5′ donor +3 splice site mutation on the mRNA of peripherin/RDS in adRP affected individuals, and comparative sequencing in RP1 to define conserved regions of the protein. Comparative sequencing is a powerful way to delineate critical regions of a sequence because different regions of a gene have different functions, and each region is subject to different levels of functional or structural constraints. Establishing a framework of conserved domains is beneficial not only for structural or functional studies, but can also aid in determining the potential effects of mutations. With the completion of sequencing of human genome, and other organisms such as Saccharomyces cerevisiae, Caenorhabditis elegans , and Drosophila, the facility of comparative sequencing will only increase in the future. Comparative sequencing has already become an established procedure for pinpointing conserved regions of a protein, and is an efficient way to target regions of a protein for experimental and/or evolutionary analysis. ^

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The research project is an extension of a series of administrative science and health care research projects evaluating the influence of external context, organizational strategy, and organizational structure upon organizational success or performance. The research will rely on the assumption that there is not one single best approach to the management of organizations (the contingency theory). As organizational effectiveness is dependent on an appropriate mix of factors, organizations may be equally effective based on differing combinations of factors. The external context of the organization is expected to influence internal organizational strategy and structure and in turn the internal measures affect performance (discriminant theory). The research considers the relationship of external context and organization performance.^ The unit of study for the research will be the health maintenance organization (HMO); an organization the accepts in exchange for a fixed, advance capitation payment, contractual responsibility to assure the delivery of a stated range of health sevices to a voluntary enrolled population. With the current Federal resurgence of interest in the Health Maintenance Organization (HMO) as a major component in the health care system, attention must be directed at maximizing development of HMOs from the limited resources available. Increased skills are needed in both Federal and private evaluation of HMO feasibility in order to prevent resource investment and in projects that will fail while concurrently identifying potentially successful projects that will not be considered using current standards.^ The research considers 192 factors measuring contextual milieu (social, educational, economic, legal, demographic, health and technological factors). Through intercorrelation and principle components data reduction techniques this was reduced to 12 variables. Two measures of HMO performance were identified, they are (1) HMO status (operational or defunct), and (2) a principle components factor score considering eight measures of performance. The relationship between HMO context and performance was analysed using correlation and stepwise multiple regression methods. In each case it has been concluded that the external contextual variables are not predictive of success or failure of study Health Maintenance Organizations. This suggests that performance of an HMO may rely on internal organizational factors. These findings have policy implications as contextual measures are used as a major determinant in HMO feasibility analysis, and as a factor in the allocation of limited Federal funds. ^

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The research project is an extension of the economic theory to the health care field and health care research projects evaluating the influence of demand and supply variables upon medical care inflation. The research tests a model linking the demographic and socioeconomic characteristics of the population, its community case mix, and technology, the prices of goods and services other than medical care, the way its medical services are delivered and the health care resources available to its population to different utilization patterns which, consequently, lead to variations in health care prices among metropolitan areas. The research considers the relationship of changes in community characteristics and resources and medical care inflation.^ The rapidly increasing costs of medical care have been of great concern to the general public, medical profession, and political bodies. Research and analysis of the main factors responsible for the rate of increase of medical care prices is necessary in order to devise appropriate solutions to cope with the problem. An understanding of the community characteristics and resources-medical care costs relationships in the metropolitan areas potentially offers guidance in individual plan and national policy development.^ The research considers 145 factors measuring community milieu (demographic, social, educational, economic, illness level, prices of goods and services other than medical care, hospital supply, physicians resources and techological factors). Through bivariate correlation analysis, the number of variables was reduced to a set of 1 to 4 variables for each cost equation. Two approaches were identified to track inflation in the health care industry. One approach measures costs of production which accounts for price and volume increases. The other approach measures price increases. One general and four specific measures were developed to represent each of the major approaches. The general measure considers the increase on medical care prices as a whole and the specific measures deal with hospital costs and physician's fees. The relationships among changes in community characteristics and resources and health care inflation were analyzed using bivariate correlation and regression analysis methods. It has been concluded that changes in community characteristics and resources are predictive of hospital costs and physician's fees inflation, but are not predictive of increases in medical care prices. These findings provide guidance in the formulation of public policy which could alter the trend of medical care inflation and in the allocation of limited Federal funds.^