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High levels of uncompensated care impact hospital profitability and may create challenges for rural hospitals at financial risk of closure. We explore 2019 hospital uncompensated care as a percentage of operating expenses and draw comparisons at a state level by Medicaid expansion status and rural classification. We further compare uncompensated care in 2019 to 2014 in rural hospitals by Medicaid expansion implementation timing. We found that, overall, rural hospitals had more uncompensated care than urban hospitals in 2019 (3.81% vs. 3.12%), but there was a larger difference by expansion status (expansion states: 2.55% vs. non-expansion states: 6.28%). In all but seven states, rural hospitals reported higher uncompensated care than urban, and the 14 states with the highest uncompensated care had not expanded Medicaid. We observed that rural hospital uncompensated care in non-expansion states increased between 2014 and 2019, while the most dramatic decrease occurred in late-expansion states. [ABSTRACT FROM AUTHOR]

ObjectiveTo determine whether, following implementation of California's minimum nurse staffing legislation, changes in acuity-adjusted nurse staffing and quality of care in California hospitals outpaced similar changes in hospitals in comparison states without such regulations.Data sources/study settingData from the American Hospital Association Annual Survey of Hospitals, the California Office of Statewide Health Planning and Development, the Hospital Cost Report Information System, and the Agency for Healthcare Research and Quality's Health Care Cost and Utilization Project's State Inpatient Databases from 2000 to 2006.Study designWe grouped hospitals into quartiles based on their preregulation staffing levels and used a difference-in-difference approach to compare changes in staffing and in quality of care in California hospitals to changes over the same time period in hospitals in 12 comparison states without minimum staffing legislation.Data collection/extraction methodsWe merged data from the above data sources to obtain measures of nurse staffing and quality of care. We used Agency for Healthcare Research and Quality's Patient Safety Indicators to measure quality.Principal findingsWith few exceptions, California hospitals increased nurse staffing levels over time significantly more than did comparison state hospitals. Failure to rescue decreased significantly more in some California hospitals, and infections due to medical care increased significantly more in some California hospitals than in comparison state hospitals. There were no statistically significant changes in either respiratory failure or postoperative sepsis.ConclusionsFollowing implementation of California's minimum nurse staffing legislation, nurse staffing in California increased significantly more than it did in comparison states' hospitals, but the extent of the increases depended upon preregulation staffing levels; there were mixed effects on quality.

This study assessed whether permanent supportive housing (PSH) participation is associated with health service use among a population of adults with disabilities, including people transitioning into PSH from community and institutional settings. Our primary data sources were 2014 to 2018 secondary data from a PSH program in North Carolina linked to Medicaid claims. We used propensity score weighting to estimate the average treatment effect on the treated of PSH participation. All models were stratified by whether individuals were in institutional or community settings prior to PSH. In weighted analyses, among individuals who were institutionalized prior to PSH, PSH participation was associated with greater hospitalizations and emergency department (ED) visits and fewer primary care visits during the follow-up period, compared with similar individuals who largely remained institutionalized. Individuals who entered PSH from community settings did not have significantly different health service use from similar comparison group members during the 12-month follow-up period. [ABSTRACT FROM AUTHOR]

Purpose: To ascertain the use and perceived success of strategies to improve the financial performance of Critical Access Hospitals (CAHs). Methods: Information about the use and perceived effectiveness of 44 specific strategies to improve financial performance was collected from an online survey of 291 CAH Chief Executive Officers and Chief Financial Officers. Responses were merged with financial and operational characteristics of the respondents' hospitals obtained from Medicare cost reports. Use rates and perceived success and failure were calculated for each strategy. A cluster analysis was applied to classify strategies based on their use and success. Finally, CAH characteristics were examined to predict the use of individual strategies. Findings: Financial improvement strategies are pervasive among CAHs. The administrators who responded to the survey in this study reported using an average of 17.0 of the maximum 44 strategies listed in the survey questionnaire. Revenue/cost, human resource, and capital strategies were more frequently used than service expansion and reduction strategies. Overall, CAH characteristics did not explain the use or perceived success of specific strategies, but they did partially predict the number of strategies attempted. Conclusions: CAH administrators have used multiple strategies to improve financial performance with a wide variety of reported success. More research into the effectiveness of specific interventions is needed to help administrators select evidence-based strategies.

Context: Among the large number of hospitals with critical access hospital (CAH) designation, there is substantial variation in facility revenue as well as the number and types of services provided. If these variations have material effects on financial indicators, then performance comparisons among all CAHs are problematic. Purpose: To investigate whether indicators of financial performance and condition systematically vary among peer groups of CAHs. Methods: Suggestions from CAH administrators, a literature review, expert panel advice, and statistical analysis were used to create peer groups based on whether a CAH: (1) had less than $5 million, $5-10 million, or over $10 million in net patient revenue; (2) was owned by a government entity; (3) provided long-term care; and (4) operated a provider-based Rural Health Clinic. Findings: Significant differences in financial performance and condition exist among CAH peer groups. Conclusions: CAHs should ensure that they use appropriate peer comparators when assessing their financial performance and condition. If quality, outcome, safety and access are affected by financial performance and condition, it may also be important for research in these areas to control for peer group differences among CAHs.

Context: There is a growing recognition of the need to measure and report hospital financial performance. However, there exists little comparative financial indicator data specifically for critical access hospitals (CAHs). CAHs differ from other hospitals on a number of dimensions that might affect appropriate indicators of performance, including differences in Medicare reimbursement, limits on bed size and average length of stay, and relaxed staffing rules. Purpose: To develop comparative financial indicators specifically designed for CAHs using Medicare cost report data. Methods: A technical advisory group of individuals with extensive experience in rural hospital finance and operations provided advice to a research team from the University of North Carolina at Chapel Hill. Twenty indicators deemed appropriate for assessment of CAH financial condition were chosen and formulas determined. Issues 1 and 2 of the CAH Financial Indicators Report were mailed to the chief executive officers of 853 CAHs in the summer of 2004 and 1,092 CAHs in the summer of 2005, respectively. Each report included indicator values specifically for their CAH, indicator medians for peer groups, and an evaluation form. Findings: Chief executive officers found the indicators to be useful and the underlying formulas to be appropriate. The multiple years of data provide snapshots of the industry as a whole, rather than trend data for a constant set of hospitals. Conclusions: The CAH Financial Indicators Report is a useful first step toward comparative financial indicators for CAHs.

Purpose: To investigate (1) all‐payer inpatient volume changes at rural hospitals and (2) whether trends in inpatient volume differ by organizational and geographic characteristics of the hospital and characteristics of the patient population. Methods: We used a retrospective, longitudinal study design. Our study sample consisted of rural hospitals between 2011 and 2017. Inpatient volume was measured as inpatient average daily census (ADC). Additional measured hospital characteristics included census region, Medicare payment type, ownership type, number of beds, local competition, total margin, and whether the hospital was located in a Medicaid expansion state. Measured characteristics of the local patient population included total population size, percent of population aged 65 years or older, and percent of population in poverty. To identify predictors of inpatient volume trends, we fit a linear multiple regression model using generalized estimating equations. Findings: Rural hospitals experienced an average change in ADC of −13% between 2011 and 2017. We found that hospital characteristics (eg, census region, Medicare payment type, ownership type, total margin, whether the hospital was located in a Medicaid expansion state) and patient population characteristics (eg, percent of population in poverty) were significant predictors of inpatient volume trends. Conclusions: Trends in inpatient volume differ by organizational and geographic characteristics of the hospital and characteristics of the patient population. Researchers and policy makers should continue to explore the causal mechanisms of inpatient volume decline and its role in the financial viability of rural hospitals. [ABSTRACT FROM AUTHOR]

Purpose: To determine whether inpatient and outpatient charges changed at rural hospitals after a merger. Methods: Hospital mergers were derived from proprietary Irving Levin Associates data through manual review and validation. Hospital‐level characteristics were derived from HCRIS, CMS Impact File Hospital Inpatient Prospective Payment System, Hospital MSA file, AHRF, and US Census data. A difference‐in‐differences approach was used to determine whether inpatient and outpatient charges changed at rural hospitals after a merger. The comparison group, rural hospitals that did not merge at any point during the sample period, was weighted using inverse probability of treatment weights. Key outcome measures were total inpatient and total outpatient charges (logged). Findings: Hospitals that merged billed 17.73% more inpatient charges and 12.66% more outpatient charges at baseline compared to hospitals that did not merge. Our results indicate that merging was associated with a 3.04% decrease in inpatient charges (P <.001) and a 1.07% increase in outpatient charges (P =.082). Merging was also associated with a 4.38% decrease in total revenue, a 3.58% decrease in net patient revenue, and no change in total inpatient discharges or average daily census. Conclusions & Implications: Merging was strongly associated with a decrease in inpatient charges and somewhat associated with an increase in outpatient charges for rural hospitals. Future work could build upon this work to determine whether acquirers reduce or eliminate certain services at rural hospitals after a merger, and ultimately how changes in service delivery could impact patients in those rural communities. [ABSTRACT FROM AUTHOR]

Purpose: Skilled nursing care (SNC) provides Medicare beneficiaries short‐term rehabilitation from an acute event. The purpose of this study is to assess beneficiary, market, and hospital factors associated with beneficiaries receiving care near home. Methods: The population includes Medicare beneficiaries who live in a rural area and received acute care from an urban facility in 2013. "Near home" was defined 3 different ways based on distances from the beneficiary's home to the nearest source of SNC. Results include unadjusted means and odds ratios from logistic regression. Findings: About 69% of rural beneficiaries receiving acute care in an urban location returned near home for SNC. Beneficiaries returning home were white (odds ratio [OR] black: 0.69; other race: 0.79); male (OR: 1.07); older (OR age 85+ [vs 65‐69]: 1.14); farther from SNC (OR: 1.01 per mile); closer to acute care (OR: 0.28, logged miles); and received acute care from hospitals that did not own a skilled nursing facility (owned OR: 0.77) and hospitals with: no swing bed (swing bed OR: 0.47), high case mix (OR: 3.04), and nonprofit status (for‐profit OR: 0.85). Results varied somewhat across definitions of "near home." Conclusions: Rural Medicare beneficiaries who received acute care far from home were more likely to receive SNC far from home. Because Medicare beneficiaries have the choice of where to receive SNC, policy makers may consider ensuring that new payment models do not incentivize provision of SNC away from home. [ABSTRACT FROM AUTHOR]