Comparison of financial trends in small rural and urban hospitals in Texas, 1983--1985

The purpose of this study was to compare the financial performance of small rural hospitals to that of small urban hospitals in Texas. Hospital-specific and environmental factors were studied as control variables.^ Small rural hospitals were found to be financially stronger on measures of liquidity but weaker on measures of profitability. Small urban hospitals performed better on measures of profitability and long-range solvency. When all measures in the five dimensions of financial performance were analyzed, no significant difference was found between the two groups of hospitals. None of the control variables included in the study was significantly associated with financial performance both for rural and urban hospitals. Conclusions were that small rural hospitals in Texas are experiencing a deterioration in financial condition but small, rural hospitals are not doing any worse than small urban hospitals; and that the financial hardship which rural hospitals suffer may be inherent in the nature of the institutions themselves, and not as a result of their smallness nor their rural settings. ^

Charity care and community benefits by hospital type in Texas

Hospital care is the largest component of the health care sector. This industry is made up of for profit hospital (FPH) organizations, not for profit (NFP) hospitals, and government (GOV) run hospital facilities. Objectives of this analysis were: (a) to conduct a literature review on NFP hospital legislation at the state level in Texas and at the federal level in the broader U.S.; and (b) to describe the types of charity care and community benefits currently being provided: by NFP hospitals compared to FPH hospitals and GOV hospitals; by hospitals geographic proximity to the Texas-Mexico border; and by hospital community type (rural, suburban, and urban); and (c) propose specific policy changes that may be needed to improve the current Texas State statute. Methods. In describing the historical and current policy context of NFP hospital legislation in the United States, federal legislation was reviewed from 1913 to the present and Texas State legislation was reviewed from 1980 to the present. In describing the provision of charity care, data from the 2008 Annual Cooperative Hospital Survey were examined by hospital organizational type, size, proximity to the border, and community type using linear regression and chi-squared tests to assess differences in charity care and community benefits. Results. The data included 123 NFP hospitals, 114 GOV hospitals, and 123 FPH. Results. Small sized (p<0.001) and medium sized (p<0.001) NFP hospitals provide a greater percent of total charity care when compared to FPH hospitals and to both GOV and FPH hospitals respectively; however, no significant difference in total charity care was found among large sized NFP hospitals when compared to FPH hospitals alone (p=.345) and both GOV and FPH facilities (p=.214). The amount of charity care provided was not found to be different based on proximity to the border or community type. Community benefit planning and budgeting was found to be similar regardless of community type and proximity to the border. Conclusion. No differences in charity care in Texas were found for large sized NFP hospitals compared to FPH and GOV hospitals. Contrary to widely held beliefs, this study did not find the border region to provide a greater amount of charity care or bad debt. Charity care also did not vary by community type. These findings underscore the need for continued collection of transparent data from all hospitals in order to provide policy makers and consumers with information on utilization trends to ensure benefits are being provided to the community. Policy changes or revoking tax-benefits may occur as charity care utilization declines with the implementation of health reform in the next few years.^

The impact of Medicare, Medicaid and Schip Extension Act of 2007 (MMSEA) on the long term acute care hospitals

The Long Term Acute Care Hospitals (LTACH), which serve medically complex patients, have grown tremendously in recent years, by expanding the number of Medicare patient admissions and thus increasing Medicare expenditures (Stark 2004). In an attempt to mitigate the rapid growth of the LTACHs and reduce related Medicare expenditures, Congress enacted Section 114 of P.L. 110-173 (§114) of the Medicare, Medicaid and SCHIP Extension Act (MMSEA) in December 29, 2007 to regulate the LTCAHs industry. MMSEA increased the medical necessity reviews for Medicare admissions, imposed a moratorium on new LTCAHs, and allowed the Centers for Medicare and Medicaid Services (CMS) to recoup Medicare overpayments for unnecessary admissions. ^ This study examines whether MMSEA impacted LTACH admissions, operating margins and efficiency. These objectives were analyzed by comparing LTACH data for 2008 (post MMSEA) and data for 2006-2007 (pre-MMSEA). Secondary data were utilized from the American Hospital Association (AHA) database and the American Hospital Directory (AHD).^ This is a longitudinal retrospective study with a total sample of 55 LTACHs, selected from 396 LTACHs facilities that were fully operational during the study period of 2006-2008. The results of the research found no statistically significant change in total Medicare admissions; instead there was a small but not statistically significant reduction of 5% in Medicare admissions for 2008 in comparison to those for 2006. A statistically significant decrease in mean operating margins was confirmed between the years 2006 and 2008. The LTACHs' Technical Efficiency (TE), as computed by Data Envelopment Analysis (DEA), showed significant decrease in efficiency over the same period. Thirteen of the 55 LTACHs in the sample (24%) in 2006 were calculated as “efficient” utilizing the DEA analysis. This dropped to 13% (7/55) in 2008. Longitudinally, the decrease in efficiency using the DEA extension technique (Malmquist Index or MI) indicated a deterioration of 10% in efficiency over the same period. Interestingly, however, when the sample was stratified into high efficient versus low efficient subgroups (approximately 25% in each group), a comparison of the MIs suggested a significant improvement in Efficiency Change (EC) for the least efficient (MI 0.92022) and reduction in efficiency for the most efficient LTACHs (MI = 1.38761) over same period. While a reduction in efficiency for the most efficient is unexpected, it is not particularly surprising, since efficiency measure can vary over time. An improvement in efficiency, however, for the least efficient should be expected as those LTACHs begin to manage expenses (and controllable resources) more carefully to offset the payment/reimbursement pressures on their margins from MMSEA.^