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Goal: To document shifts in rural hospital service line offerings between 2010 and 2021 and to assess the resulting impacts on hospital profitability. Methods: We used annual Medicare cost report data for all rural hospitals that did not change payment classifications between 2010 and 2021. We documented changes in the percentages of hospitals offering each of the 37 inpatient or ancillary service lines included in the data. We then used panel event studies to assess effects on hospital operating margin for specific service lines that changed most prominently during this period. Principal Findings: Twelve service lines changed by more than 5% during our period of analysis. These are highlighted by hospitals adding rural health clinics (+32%) and CT scans (+20%) and removing delivery rooms (-21%) and skilled nursing facilities (-19%). Panel event studies demonstrated that the addition or subtraction of most services did not have statistically significant impacts on future hospital operating margins. Notable exceptions were the addition of rural health clinics and the removal of delivery services, both of which positively affected future operating margins. The addition of occupational therapy services had a positive effect on operating margin in the near term, but adding MRI services had a negative effect. Practical Applications: The finding that only a select few service line changes resulted in meaningful impacts to hospital operating margins suggests that hospital leaders should be wary of implementing such changes as a means of improving financial viability. [ABSTRACT FROM AUTHOR]

Purpose: To determine whether community sociodemographic factors are associated with the survival or closure of rural hospitals at risk of financial distress between 2010 and 2019. Methods: We use a national sample of 985 rural hospitals at risk of financial distress to analyze the relationship between community sociodemographic characteristics and hospital survival or closure. We control for financial distress using the Financial Distress Index developed by the Sheps Center for Health Services Research. Community characteristics are retrieved from the Census and the Robert Wood Johnson Foundation. We first use Wilcoxon rank‐sum tests to demonstrate annual sociodemographic differences between rural communities with financially distressed hospitals that closed between 2010 and 2019, and those that remained open. Multilevel Weibull proportional hazards regressions then uncover which sociodemographic factors are significantly associated with survival. Findings: Our initial results confirm that closures of rural hospitals at risk of financial distress disproportionately affect communities with certain sociodemographic characteristics. However, most of these characteristics are not associated with higher rates of closure in the multivariate survival analysis. The final results suggest that financially distressed hospitals are more likely to experience closure if their communities have higher rates of unemployment (Hazard Ratio = 1.36, P <.05) or uninsured residents under 65 (Hazard Ratio = 1.13, P <.05). Conclusions: Among financially distressed rural hospitals, specific community‐level sociodemographic characteristics (unemployment and uninsurance rates) are positively associated with the likelihood of closure. Social policies addressing these issues should emphasize their broader relationship with the local health sector. [ABSTRACT FROM AUTHOR]

Purpose: This paper takes an empirical approach to determining the effect that a critical access hospital (CAH) has on local retail activity. Previous research on the relationship between hospitals and economic development has primarily focused on single-case, multiplier-oriented analysis. However, as the efficacy of federal and state-level rural health subsidies come under increasing scrutiny, more comprehensive investigations can provide support for continued funding. Methods: Data from 105 rural Oklahoma communities are used to explore whether the presence of a CAH impacts several measures of retail activity. The measures are: total retail sales, total number of retail establishments, and number of micro and small retail establishments. Ordinary least squares regression is used to evaluate the impact of a CAH after controlling for a host of other factors influencing retail activity such as local demographics, unemployment rates, and the presence of a Wal-Mart. Findings: The presence of a CAH has a positive and significant influence on each measure of retail activity. The parameter estimates suggest that a CAH has a similar influence on rural retail sales as a Wal-Mart, increasing total retail sales by approximately 28% over towns without a CAH. Other model results indicate that a CAH presence significantly increases the number of total retail establishments and the number of micro and small business establishments. Conclusions: The positive results provide additional evidence on the far-reaching economic development impacts of CAHs. The results also emphasize the importance of continued support for these rural institutions, including federal and state subsidies. (Contains 1 figure and 3 tables.)

Obesity has become an increasingly severe problem in the United States. From 2008 to 2018, the adult obesity rate rose from 33.8% to 42.4%, with rates that are notably higher in rural areas when compared to their urban counterparts. Meanwhile, rural regions have experienced relatively slower employment growth and higher poverty rates during the recovery from the Great Recession. Social scientists are interested in determinants of -- and potential solutions to -- this rise in obesity rates. The existing literature has focused on the relationship between obesity and social/economic factors, such as the number of fastfood restaurants, limited physical activity, and unemployment rates. However, one unexplored question is whether the level of economic growth experienced by a rural area plays a role in the obesity problem. This paper assesses the impact of economic growth (measured by county-level GDP per capita) on obesity rates (measured by the county-level percentage of adults with BMI higher than 30) in rural America. Nationwide, data is collected on a host of demographic and economic characteristics for all non-metropolitan counties from 2012 to 2016, resulting in a county-level panel data set (n=1,948, t=5). Control variables include age, race and ethnicity, unemployment rates, rates of physical inactivity, food assistance program participation, and an index measuring healthy food availability. Two different econometric approaches were applied: (1) a fixed-effects panel regression model and (2) a difference-in-difference model using propensity score matching (PSM). The results of both econometric models suggest there is no relationship between economic growth and future obesity rates. This suggests that programs focused on rural economic growth may not affect other quality-of-life metrics. The conclusion discusses these competing interests and how regional scientists can play a role in future research in this area. [ABSTRACT FROM AUTHOR]

A consistent gap exists between home Internet use in metropolitan areas and in non-metropolitan areas in the U.S. This digital divide may stem from technology differences in home Internet connectivity. Alternatively, differences in education, income, and other household attributes may explain differences in metropolitan and non-metropolitan area home Internet access. Effective programs to reduce the metropolitan-non-metropolitan digital divide must be based on' an understanding of the relative roles that technology and household characteristics play in determining differential Internet usage. The household Internet adoption decision is modeled using a logit estimation approach with data from the 2001 U.S. Current Population Survey Internet and Computer Use Supplement. A decomposition of separate metropolitan and non-metropolitan area estimates shows that differences in household attributes, particularly education and income, account for 63 percent of the current metropolitan-non-metropolitan digital divide. The result raises significant doubts that policies which focus solely on infrastructure and technology access will mitigate the current metropolitan-non-metropolitan digital divide.

This paper examines the effects of four significant tornadoes on housing prices in Moore, Oklahoma. We use a hedonic difference-in-difference approach by considering transactions made preceding and following major tornadic events in Moore (occurring in 1999, 2003, 2010, and 2013). Our dataset spans nearly 30,000 housing transactions between 1990 and 2020. The length of tornado impacts is evaluated using a set of time indicators for the years leading up to (and after) the tornadoes. We find a 2-5% decrease in housing prices during the first year after a tornado for houses in the destructive path. However, no such impacts exist in years 2-7. We also employ three different specifications (OLS, spatial lag, and spatial error) to find the most appropriate model for considering the potential spatial processes at work. The results are largely similar across specifications. [ABSTRACT FROM AUTHOR]

With increased numbers of veterinarians in the market, it is critical to understand how this increased competition affects income potential at multiple levels. This study presents an empirical approach that incorporates local and nonlocalised spatial competition of firms into one model. By analysing the market for veterinarians using a spatial weight matrix approach, we are able to quantify localized and nonlocalised competition which assists in defining relevant market areas for veterinarians. Specifically, increased density within their county and surrounding counties decreases veterinarian income. Thus, the potential market area for veterinarians is larger than the local/county market in which they practice. This is important for veterinarians when choosing a location to practice, as they must consider the competition and demand in local and non-local areas. [ABSTRACT FROM AUTHOR]