An ecologic comparison study of the impact of economic disadvantage on Texas Assessment of Knowledge and Skills performance, graduation rates, and readiness for higher education for students attending public and charter schools in Texas from 2004 to 2006

Purpose. No Child Left Behind aimed to "improve the academic achievement of the disadvantaged." The primary research question considered how academic achievement of those from economic disadvantage compared to those not from disadvantage? ^ Economically disadvantaged students can potentially have added academic disadvantage. Research shows low academic achievement can potentially result in drug abuse, youth violence, and teen pregnancy. ^ Methods. To compare the student populations, measures included TAKS results and academic indicator data collected by the Texas Education Agency. ^ Results. T-test analyses showed a significant difference between the economically and non-economically disadvantaged student populations in meeting the TAKS passing standard, graduation, and preparation for higher education.^ Conclusions. The achievement gap between students remained as indicated by the Texas testing program. More research and time are needed to observe if the desired impact on those from economic disadvantage will be reflected by academic achievement data.^

Evaluating the impact of vertical integration on health system peformance

Vertical integration is grounded in economic theory as a corporate strategy for reducing cost and enhancing efficiency. There were three purposes for this dissertation. The first was to describe and understand vertical integration theory. The review of the economic theory established vertical integration as a corporate cost reduction strategy in response to environmental, structural and performance dimensions of the market. The second purpose was to examine vertical integration in the context of the health care industry, which has greater complexity, higher instability, and more unstable demand than other industries, although many of the same dimensions of the market supported a vertical integration strategy. Evidence on the performance of health systems after integration revealed mixed results. Because the market continues to be turbulent, hybrid non-owned integration in the form of alliances have increased to over 40% of urban hospitals. The third purpose of the study was to examine the application of vertical integration in health care and evaluate the effects. The case studied was an alliance formed between a community hospital and a tertiary medical center to facilitate vertical integration of oncology services while maintaining effectiveness and preserving access. The economic benefits for 1934 patients were evaluated in the delivery system before and after integration with a more detailed economic analysis of breast, lung, colon/rectal, and non-malignant cases. A regression analysis confirmed the relationship between the independent variables of age, sex, location of services, race, stage of disease, and diagnosis, and the dependent variable, cost. The results of the basic regression model, as well as the regression with first-order interaction terms, were statistically significant. The study shows that vertical integration at an intermediate health care system level has economic benefits. If the pre-integration oncology group had been treated in the post-integration model, the expected cost savings from integration would be 31.5%. Quality indicators used were access to health care services and research treatment protocols, and access was preserved in the integrated model. Using survival as a direct quality outcome measure, the survival of lung cancer patients was statistically the same before and after integration. ^

Clinical and economic outcomes of serious postoperative infections following resection of common respiratory and gastrointestinal solid tumors

Unlike infections occurring during periods of chemotherapy-induced neutropenia, postoperative infections in patients with solid malignancy remain largely understudied. The purpose of this population-based study was to evaluate the clinical and economic burden, as well as the relationship of hospital surgical volume and outcomes associated with serious postoperative infection (SPI) – i.e., bacteremia/sepsis, pneumonia, and wound infection – following resection of common solid tumors.^ From the Texas Discharge Data Research File, we identified all Texas residents who underwent resection of cancer of the lung, esophagus, stomach, pancreas, colon, or rectum between 2002 and 2006. From their billing records, we identified ICD-9 codes indicating SPI and also subsequent SPI-related readmissions occurring within 30 days of surgery. Random-effects logistic regression was used to calculate the impact of SPI on mortality, as well as the association between surgical volume and SPI, adjusting for case-mix, hospital characteristics, and clustering of multiple surgical admissions within the same patient and patients within the same hospital. Excess bed days and costs were calculated by subtracting values for patients without infections from those with infections computed using multilevel mixed-effects generalized linear model by fitting a gamma distribution to the data using log link.^ Serious postoperative infection occurred following 9.4% of the 37,582 eligible tumor resections and was independently associated with an 11-fold increase in the odds of in-hospital mortality (95% Confidence Interval [95% CI], 6.7-18.5, P < 0.001). Patients with SPI required 6.3 additional hospital days (95% CI, 6.1 - 6.5) at an incremental cost of $16,396 (95% CI, $15,927–$16,875). There was a significant trend toward lower overall rates of SPI with higher surgical volume (P=0.037). ^ Due to the substantial morbidity, mortality, and excess costs associated with SPI following solid tumor resections and given that, under current reimbursement practices, most of this heavy burden is borne by acute care providers, it is imperative for hospitals to identify more effective prophylactic measures, so that these potentially preventable infections and their associated expenditures can be averted. Additional volume-outcomes research is also needed to identify infection prevention processes that can be transferred from higher- to lower-volume providers.^

Resource Review: Child Food Insecurity: The Economic Impact on Our Nation

A review of Child Food Insecurity: The Economic Impact on our Nation. A Report on Research on the Impact of Food Insecurity and Hunger on Child Health, Growth and Development Commissioned by Feeding America and the ConAgra Foods Foundation by John Cook and Karen Jeng.

ECONOMIC ANALYSIS OF THE DEMAND FOR PRESCRIPTION MEDICINE IN THE UNITED STATES

The purpose of this study was to understand the role of principle economic, sociodemographic and health status factors in determining the likelihood and volume of prescription drug use. Econometric demand regression models were developed for this purpose. Ten explanatory variables were examined: family income, coinsurance rate, age, sex, race, household head education level, size of family, health status, number of medical visits, and type of provider seen during medical visits. The economic factors (family income and coinsurance) were given special emphasis in this study.^ The National Medical Care Utilization and Expenditure Survey (NMCUES) was the data source. The sample represented the civilian, noninstitutionalized residents of the United States in 1980. The sample method used in the survey was a stratified four-stage, area probability design. The sample was comprised of 6,600 households (17,123 individuals). The weighted sample provided the population estimates used in the analysis. Five repeated interviews were conducted with each household. The household survey provided detailed information on the United States health status, pattern of health care utilization, charges for services received, and methods of payments for 1980.^ The study provided evidence that economic factors influenced the use of prescription drugs, but the use was not highly responsive to family income and coinsurance for the levels examined. The elasticities for family income ranged from -.0002 to -.013 and coinsurance ranged from -.174 to -.108. Income has a greater influence on the likelihood of prescription drug use, and coinsurance rates had an impact on the amount spent on prescription drugs. The coinsurance effect was not examined for the likelihood of drug use due to limitations in the measurement of coinsurance. Health status appeared to overwhelm any effects which may be attributed to family income or coinsurance. The likelihood of prescription drug use was highly dependent on visits to medical providers. The volume of prescription drug use was highly dependent on the health status, age, and whether or not the individual saw a general practitioner. ^