This study examined the relationships among gender, perceived financial barriers to health care, and selected health status indicators in a randomly selected rural Appalachian sample. The data were gathered through the Johnson County Health Survey. The survey was conducted through personal interviews with 207 females and 178 males representing 197 households. The Duke Health Profile was used to measure the perceived health of the respondents. Analysis of variance, t tests, and descriptive statistics were used to analyze the data. Analysis of the data revealed that women perceive financial barriers to health care significantly more than men (P < 0.01), even when living in the same household; women had significantly poorer health than men (P < 0.01); and both women and men with perceived financial barriers experienced poorer health (P < 0.01) than those who did not perceive such barriers. Conclusions from the study suggest that in this rural sample women were the most compromised by both gender and health status, and that they perceived that their health care needs were not being adequately met.
The duration and cost of intensive care for premature infants are important concerns for parents and health providers. We developed a mathematical model to predict length of stay and hospital charges from perinatal information. Length of stay was found to decrease exponentially with gestational age. The equation predicted the length of stay within 10 days in 86% of the cases and had an R2 = .765. Gestational age, the presence of respiratory distress syndrome, and pneumonia were the strongest predictors of hospital charges (R2 = .811). The gestational age threshold below which length and cost of hospitalization were significantly higher was 34 weeks.
The purpose of this research project was to compare inpatient mortality rates for rural hospitals with mortality rates of urban hospitals of given sizes and ranges of service. Statistical adjustments for risk were made in the probability of death during hospitalization for 43,000 patients across 166 hospitals by age, gender, principal diagnosis, principal surgical procedure, characteristics of the secondary diagnoses, and whether or not cancer was a secondary diagnosis. Eighty-three small hospitals that had a relatively unspecialized range of services constituted the study group. Patient characteristics of this study group were moderately representative of the national population. A standardized score was calculated for each hospital using a formula based on the actual hospital death rate and the death rate expected for a given hospital with patients of the same demographic and medical characteristics. Patients admitted to hospitals in nonmetropolitan areas had a mortality rate of 0.41 percent compared with a mortality rate of 0.66 percent in peer hospitals in metropolitan areas. After mortality rates were risk-adjusted and converted to z scores, nonmetropolitan areas had an average z of +0.16, and metropolitan areas had an average z of -0.25, where positive z scores reflect a lower-than-average adjusted mortality rate. The metropolitan-nonmetropolitan (urban-rural) difference was not statistically significant, but it is meaningful in that rural hospitals tended to have a lower adjusted mortality rate than urban hospitals of the same size and type, indicating that rural hospitals had the same or lower adjusted mortality rates. The possibility of urban hospitals having riskier patients was minimized but could not be definitively ruled out. Taken together with other studies, the data are consistent with the view that small rural hospitals generally make appropriate transfer decisions for severely ill patients and provide quality care for retained patients.
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