Rural Hospital Closures: A Scoping Review of Studies Published Between 1990 and 2020.

Between 1990 and 2020, 334 rural hospitals closed in the United States, and since 2011 hospital closures have outnumbered new hospital openings. This scoping review evaluates peer-reviewed studies published since 1990 with a focus on rural hospital closures, synthesizing studies across six themes: 1) health care policy environment, 2) precursors to rural hospital closures, 3) economic impacts, 4) effects of rural hospital closures on access to care, 5) health and community impacts, and 6) definitions of rural hospitals and communities. In the 1990s, rural hospitals that closed were smaller, while rural hospitals that closed in the 2010s tended to have more beds. Many studies of the health impacts of rural hospital closures yielded null findings. However, these studies differed in their definitions of "rural hospital closure." Given the accelerated rate of hospital closures, more attention should be paid to hospitals that serve rural communities of color and low-income communities.

Impact of rural hospital closures on hospitalizations and associated outcomes for ambulatory and emergency care sensitive conditions.

PURPOSE: The purpose of this paper is to examine the impact of rural hospital closures on age-adjusted hospitalization rates for ambulatory care sensitive condition (ACSC) and emergency care sensitive condition (ECSC) and associated outcomes, such as length of stay and in-hospital mortality in hospital service areas (HSAs) that utilized the closed hospital. METHODS: We used the State Inpatient Data from the Healthcare Cost and Utilization Project for 9 states from 2010 to 2017 and classified admissions as ACSC or ECSC. We compared age-adjusted admission rates and length of stay (LOS) for ACSC and ECSC rates and age adjusted in-hospital mortality rate for ECSC among rural ZIP codes in HSAs with a closure to rural ZIP codes in HSAs without closures. We used propensity score-weighted regression analysis and event study design. FINDINGS: Findings suggest that ACSC admission rates started to increase right before the closure. However, this increase levels off 2 years after closure. LOS for ACSC significantly decreased almost a year after closure. ECSC admissions showed a significant decrease for a few quarters 1 year before the closure. CONCLUSIONS: Rural hospital closures were associated with increase in ACSC admissions right before closure and for nearly 2 years post closure as well as decrease in ECSC admissions before closure. As rural hospitals continue to close, efforts to ensure communities affected by these closures maintain access to primary health care may help eliminate increases in costly preventable hospital admissions for ACSC while ensuring access for emergency care services.

COVID-19 Data Utilization in North Carolina: Qualitative Analysis of Stakeholder Experiences.

BACKGROUND: As the world faced the pandemic caused by the novel coronavirus disease 2019 (COVID-19), medical professionals, technologists, community leaders, and policy makers sought to understand how best to leverage data for public health surveillance and community education. With this complex public health problem, North Carolinians relied on data from state, federal, and global health organizations to increase their understanding of the pandemic and guide decision-making. OBJECTIVE: We aimed to describe the role that stakeholders involved in COVID-19-related data played in managing the pandemic in North Carolina. The study investigated the processes used by organizations throughout the state in using, collecting, and reporting COVID-19 data. METHODS: We used an exploratory qualitative study design to investigate North Carolina's COVID-19 data collection efforts. To better understand these processes, key informant interviews were conducted with employees from organizations that collected COVID-19 data across the state. We developed an interview guide, and open-ended semistructured interviews were conducted during the period from June through November 2020. Interviews lasted between 30 and 45 minutes and were conducted by data scientists by videoconference. Data were subsequently analyzed using qualitative data analysis software. RESULTS: Results indicated that electronic health records were primary sources of COVID-19 data. Often, data were also used to create dashboards to inform the public or other health professionals, to aid in decision-making, or for reporting purposes. Cross-sector collaboration was cited as a major success. Consistency among metrics and data definitions, data collection processes, and contact tracing were cited as challenges. CONCLUSIONS: Findings suggest that, during future outbreaks, organizations across regions could benefit from data centralization and data governance. Data should be publicly accessible and in a user-friendly format. Additionally, established cross-sector collaboration networks are demonstrably beneficial for public health professionals across the state as these established relationships facilitate a rapid response to evolving public health challenges.

To What Extent do Community Characteristics Explain Differences in Closure among Financially Distressed Rural Hospitals?

From January 2005 through December 2015, 105 rural hospitals closed. This study examined associations between community characteristics and rural hospital closure. Compared with other rural hospitals that were at high risk of financial distress but remained open over the same time period, closed rural hospitals had a smaller market share (p < .0001) despite being in areas with higher population density (p < .05), were located nearer to another hospital (p < .0001), and were located in markets that had a higher rate of unemployment (p < .05) and a higher percentage of Black (p < .05) and Hispanic (p < .01) residents. These results have three implications for rural health policy: rural hospital closures may disproportionately affect racial and ethnic minorities, community characteristics in combination with other factors make it likely that rural hospital closures will continue, and rural hospital closures illuminate the need for new models of reimbursement and health care delivery to meet the needs of rural communities.

The Rising Rate of Rural Hospital Closures.

PURPOSE: Since 2010, the rate of rural hospital closures has increased significantly. This study is a preliminary look at recent closures and a formative step in research to understand the causes and the impact on rural communities. METHODS: The 2009 financial performance and market characteristics of rural hospitals that closed from 2010 through 2014 were compared to rural hospitals that remained open during the same period, stratified by critical access hospitals (CAHs) and other rural hospitals (ORHs). Differences were tested using Pearson's chi-square (categorical variables) and Wilcoxon rank test of medians. The relationships between negative operating margin and (1) market factors and (2) utilization/staffing factors were explored using logistic regression. FINDINGS: In 2009, CAHs that subsequently closed from 2010 through 2014 had, in general, lower levels of profitability, liquidity, equity, patient volume, and staffing. In addition, ORHs that closed had smaller market shares and operated in markets with smaller populations compared to ORHs that remained open. Odds of unprofitability were associated with both market and utilization factors. Although half of the closed hospitals ceased providing health services altogether, the remainder have since converted to an alternative health care delivery model. CONCLUSIONS: Financial and market characteristics appear to be associated with closure of rural hospitals from 2010 through 2014, suggesting that it is possible to identify hospitals at risk of closure. As closure rates show no sign of abating, it is important to study the drivers of distress in rural hospitals, as well as the potential for alternative health care delivery models.