Comparison of Disaster Preparedness Between Urban and Rural Community Hospitals in New York State.

OBJECTIVE: The intent of this study was to determine whether there are differences in disaster preparedness between urban and rural community hospitals across New York State. METHODS: Descriptive and analytical cross-sectional survey study of 207 community hospitals; thirty-five questions evaluated 6 disaster preparedness elements: disaster plan development, on-site surge capacity, available materials and resources, disaster education and training, disaster preparedness funding levels, and perception of disaster preparedness. RESULTS: Completed surveys were received from 48 urban hospitals and 32 rural hospitals.There were differences in disaster preparedness between urban and rural hospitals with respect to disaster plan development, on-site surge capacity, available materials and resources, disaster education and training, and perception of disaster preparedness. No difference was identified between these hospitals with respect to disaster preparedness funding levels. CONCLUSIONS: The results of this study provide an assessment of the current state of disaster preparedness in urban and rural community hospitals in New York. Differences in preparedness between the two settings may reflect differing priorities with respect to perceived threats, as well as opportunities for improvement that may require additional advocacy and legislation. (Disaster Med Public Health Preparedness. 2019;13:424-428).

Assessment of community hospital disaster preparedness in New York State.

OBJECTIVE: The intent of this study was to assess disaster preparedness in community hospitals across New York. DESIGN: Descriptive and analytical cross-sectional survey study. The survey instrument consisted of 35 questions that examined six elements of disaster preparedness: disaster plan development, onsite surge capacity, available materials and resources, disaster education and training, disaster preparedness funding levels, and perception of disaster preparedness. SETTING: Community hospitals in New York. SUBJECTS: Contact information was obtained for 207 of 208 community hospitals. Email invitations to participate in the survey were sent to hospital CEOs and disaster preparedness coordinators. Completed surveys were received from 80 hospitals. MAIN OUTCOME MEASURES: Hospital responses to questions related to the six elements of disaster preparedness. RESULTS: Most (87.5 percent) hospitals had experienced a disaster event during the past 5 years (2012-2016). Eighty percent had disaster plans that addressed all of six major types of disasters. Only 17.5 percent believed their disaster plans were "very sufficient" and did not require any revisions. Nearly three-quarters (73.3 percent) of hospitals could continue operations for less than a week without external resources. Less than half (49.4 percent) reported being satisfied or very satisfied with the level of funding that they received from the Hospital Preparedness Program. Most (88.8 percent) respondents felt that barriers to disaster preparedness exist for their organizations. CONCLUSIONS: The results demonstrate the current level of disaster preparedness among New York hospitals. The study's approach is discussed as a model that will enable hospitals to identify focus areas for improvement and opportunities for legislation and advocacy.

Comparison of disaster preparedness between Upstate and Downstate community hospitals in New York.

OBJECTIVE: This study sought to determine whether differences exist in disaster preparedness between Upstate and Downstate community hospitals in New York. DESIGN: A descriptive and analytical cross-sectional survey study was conducted using a 35-element questionnaire. These questions examined six disaster preparedness components: disaster plan development, onsite surge capacity, available materials and resources, disaster education and training, disaster preparedness funding levels, and perception of disaster preparedness. SETTING: The population surveyed included community hospitals across New York. SUBJECTS: Invitations to participate in the survey were emailed to the CEOs and disaster preparedness coordinators at 207 of the 208 community hospitals in New York. Eighty hospitals completed surveys, including 41 Upstate hospitals and 39 Downstate facilities. MAIN OUTCOME MEASURES: Responses to questions pertaining to the six disaster preparedness elements. RESULTS: There were differences in disaster preparedness between Upstate and Downstate hospitals with respect to disaster plan development, available materials and resources, and disaster education and training. No differences were identified in onsite surge capacity, disaster preparedness funding levels, or perception of disaster preparedness. CONCLUSIONS: The results demonstrate the current condition of disaster preparedness in Upstate and Downstate community hospitals in New York. Differences in preparedness between hospitals in the two locations may reflect factors such as availability of resources and differing priorities with regard to threat levels. They also suggest opportunities for improvement in disaster preparedness, which may require additional government resources and advocacy organization efforts.

Financial performance monitoring of the technical efficiency of critical access hospitals: a data envelopment analysis and logistic regression modeling approach.

From 1980 to 1999, rural designated hospitals closed at a disproportionally high rate. In response to this emergent threat to healthcare access in rural settings, the Balanced Budget Act of 1997 made provisions for the creation of a new rural hospital--the critical access hospital (CAH). The conversion to CAH and the associated cost-based reimbursement scheme significantly slowed the closure rate of rural hospitals. This work investigates which methods can ensure the long-term viability of small hospitals. This article uses a two-step design to focus on a hypothesized relationship between technical efficiency of CAHs and a recently developed set of financial monitors for these entities. The goal is to identify the financial performance measures associated with efficiency. The first step uses data envelopment analysis (DEA) to differentiate efficient from inefficient facilities within a data set of 183 CAHs. Determining DEA efficiency is an a priori categorization of hospitals in the data set as efficient or inefficient. In the second step, DEA efficiency is the categorical dependent variable (efficient = 0, inefficient = 1) in the subsequent binary logistic regression (LR) model. A set of six financial monitors selected from the array of 20 measures were the LR independent variables. We use a binary LR to test the null hypothesis that recently developed CAH financial indicators had no predictive value for categorizing a CAH as efficient or inefficient, (i.e., there is no relationship between DEA efficiency and fiscal performance).