Does Geographic Location Affect the Quality of Care? The Difference in Readmission Rates Between the Border and Non-Border Hospitals in Texas.

Purpose: Previous literature has limited empirical evidence describing the association between border location and readmission rates among hospitals in the U.S.-Mexico border region. Thus, our study explores this novel connection in Texas border hospitals using a non-experimental longitudinal study design. Materials and Methods: Using longitudinal panel data (2013~2016) drawn from the American Hospital Association Annual Survey Database, Hospital Compare, and Area Health Resource File, a random-effects linear regression analysis was performed to quantify the impact of border location on the readmission rates of the same sample at multiple timed points. Results: We found a positive relationship between border location and 30-day hospital readmission rates for heart failure and pneumonia in Texas. Border hospitals in Texas had approximately a 4.17% higher heart failure readmission rate and a 3.46% higher pneumonia readmission rate than non-border hospitals. We also identified several hospital organizational and market factors associated (eg, registered nurse [RN]-to-patient ratio) with hospital readmission rates. Conclusion: The results suggest that improving RN staffing levels can be the most feasible action to lower the readmission rates among border Texas hospitals. Decreasing readmission rates by increasing RN staffing levels would also help them avoid reimbursement reduction under the Hospital Readmission Reduction Program (HRRP) and enhance overall health in Texas border communities. Further, to improve border health in Texas, decision-makers in state and local governments must consider incentivizing border hospitals to improve RN staffing levels and modulating the market factors affecting hospital readmission rates that are mostly beyond the control of hospitals.

Exploring Health Outcomes for U.S. Veterans Compared to Non-Veterans from 2003 to 2019.

The physical demands on U.S. service members have increased significantly over the past several decades as the number of military operations requiring overseas deployment have expanded in frequency, duration, and intensity. These elevated demands from military operations placed upon a small subset of the population may be resulting in a group of individuals more at-risk for a variety of debilitating health conditions. To better understand how the U.S Veterans health outcomes compared to non-Veterans, this study utilized the U.S. Centers for Disease Control and Prevention (CDC) Behavioral Risk Factor Surveillance System (BRFSS) dataset to examine 10 different self-reported morbidities. Yearly age-adjusted, population estimates from 2003 to 2019 were used for Veteran vs. non-Veteran. Complex weights were used to evaluate the panel series for each morbidity overweight/obesity, heart disease, stroke, skin cancer, cancer, COPD, arthritis, mental health, kidney disease, and diabetes. General linear models (GLM's) were created using 2019 data only to investigate any possible explanatory variables associated with these morbidities. The time series analysis showed that Veterans have disproportionately higher self-reported rates of each morbidity with the exception of mental health issues and heart disease. The GLM showed that when taking into account all the variables, Veterans disproportionately self-reported a higher amount of every morbidity with the exception of mental health. These data present an overall poor state of the health of the average U.S. Veteran. Our study findings suggest that when taken as a whole, these morbidities among Veterans could prompt the U.S. Department of Veteran Affairs (VA) to help develop more effective health interventions aimed at improving the overall health of the Veterans.