Tailored instructional methods for students with diverse levels of computer knowledge and skills

The purpose of this online course is to ensure new nursing graduate students know how to use computer technologies required to complete academic and research activities. Powerful computers, high speed internet, digitalized resources and databases are widely available in educational institutes. New renovation and updates are being released at faster pace than ever. All these developments are necessary for a student to utilize computer programs and synthesize large amount of data in a limited time for any given academic research project. [See PDF for complete abstract]

Corporate decision-making: A case study of decision support systems and financial performance in health care organizations

The purpose of this study was twofold: (1) To describe the relation of the intensity of DSS implementation to financial performance as an empirical exploration of improved performance at the organizational level. (2) To describe the relation of the intensity of DSS implementation to the type of organizational decision culture. A multiple case study design was utilized to compare three groups of paired cases. A pattern matching strategy was applied in this study. Four predictions were specified and compared to the empirical data. A progressively upward trend in the scores was predicted for the following theoretical relationships. (1) The greater the number of DSSs, the higher the sophistication index. (2) The greater the number of DSSs, the higher the financial ratios. (3) The greater the number of DSSs, the higher the culture score. (4) The higher the culture score, the higher the financial ratios. The data did not support any of the predicted trends except the relation between the number of DSSs and the financial ratios. The Income/Revenue ratio indicates the efficiency of a company's operations. One would expect that this ratio would be most affected by the operational and financial decision support systems. The majority of the systems measured in the study supported decisions tangential to the patient service areas. The evidence suggested that the type and number of decision support systems affects the bottom line. ^

A study of the relationship of support systems and adolescent pregnancy outcomes in an adolescent family life project

This study analyzed the relationship of family support systems and adolescent pregnancy outcomes. The population for the study was 390 adolescents who had attended the Marion County Health Department Adolescent Family Life Project in Indianapolis, Indiana during a two-year period.^ The study is unique in that it afforded the opportunity to compare adolescent pregnancy-related characteristics, of white and non-white adolescents in the same study.^ The pregnancy outcomes studied were: Infant birthweight, school attendance, and pregnancy recidivism.^ Significant results were found in the analysis that supported other research in regard to factors that are associated with school attendance when family support, adolescent's age, and ethnicity were controlled. Infant birthweight and repeat pregnancy outcome relationships were not found to have any consistently significant relationship with independent variables anticipated to be associated. However, the comparisons of infant birthweight among the adolescents with, and without, family support, by ethnicity resulted in some interesting findings. Repeat pregnancy proved an enigma, in that there seemed to be almost no variables in this study that were associated with the adolescent having a repeat pregnancy.^ Familial support in this study seemed to be of less importance as a factor in adolescent pregnancy outcomes than was ethnicity. The non-white adolescents in this study had a better record for remaining in school, both those non-white adolescents who lived with parents, and those who did not live with parents. More low birthweight occurred in the non-white adolescent, both those adolescents who lived with parents, and those who did not live with parents. Repeat pregnancy occurred more in the non-white adolescent whether she lived with parents, or did not live with parents. ^

Using small area estimation and geographic information systems technology to target health services for the uninsured

The three articles that comprise this dissertation describe how small area estimation and geographic information systems (GIS) technologies can be integrated to provide useful information about the number of uninsured and where they are located. Comprehensive data about the numbers and characteristics of the uninsured are typically only available from surveys. Utilization and administrative data are poor proxies from which to develop this information. Those who cannot access services are unlikely to be fully captured, either by health care provider utilization data or by state and local administrative data. In the absence of direct measures, a well-developed estimation of the local uninsured count or rate can prove valuable when assessing the unmet health service needs of this population. However, the fact that these are “estimates” increases the chances that results will be rejected or, at best, treated with suspicion. The visual impact and spatial analysis capabilities afforded by geographic information systems (GIS) technology can strengthen the likelihood of acceptance of area estimates by those most likely to benefit from the information, including health planners and policy makers. ^ The first article describes how uninsured estimates are currently being performed in the Houston metropolitan region. It details the synthetic model used to calculate numbers and percentages of uninsured, and how the resulting estimates are integrated into a GIS. The second article compares the estimation method of the first article with one currently used by the Texas State Data Center to estimate numbers of uninsured for all Texas counties. Estimates are developed for census tracts in Harris County, using both models with the same data sets. The results are statistically compared. The third article describes a new, revised synthetic method that is being tested to provide uninsured estimates at sub-county levels for eight counties in the Houston metropolitan area. It is being designed to replicate the same categorical results provided by a current U.S. Census Bureau estimation method. The estimates calculated by this revised model are compared to the most recent U.S. Census Bureau estimates, using the same areas and population categories. ^