Hospital Surge Capacity: A Web-Based Simulation Tool for Emergency Planners.

The National Center for the Study of Preparedness and Catastrophic Event Response (PACER) has created a publicly available simulation tool called Surge (accessible at http://www.pacerapps.org) to estimate surge capacity for user-defined hospitals. Based on user input, a Monte Carlo simulation algorithm forecasts available hospital bed capacity over a 7-day period and iteratively assesses the ability to accommodate disaster patients. Currently, the tool can simulate bed capacity for acute mass casualty events (such as explosions) only and does not specifically simulate staff and supply inventory. Strategies to expand hospital capacity, such as (1) opening unlicensed beds, (2) canceling elective admissions, and (3) implementing reverse triage, can be interactively evaluated. In the present application of the tool, various response strategies were systematically investigated for 3 nationally representative hospital settings (large urban, midsize community, small rural). The simulation experiments estimated baseline surge capacity between 7% (large hospitals) and 22% (small hospitals) of staffed beds. Combining all response strategies simulated surge capacity between 30% and 40% of staffed beds. Response strategies were more impactful in the large urban hospital simulation owing to higher baseline occupancy and greater proportion of elective admissions. The publicly available Surge tool enables proactive assessment of hospital surge capacity to support improved decision-making for disaster response. (Disaster Med Public Health Preparedness. 2018;12:513-522).

The Effect of Medicaid Expansion on Utilization in Maryland Emergency Departments.

STUDY OBJECTIVE: A proposed benefit of expanding Medicaid eligibility under the Patient Protection and Affordable Care Act (ACA) was a reduction in emergency department (ED) utilization for primary care needs. Pre-ACA studies found that new Medicaid enrollees increased their ED utilization rates, but the effect on system-level ED visits was less clear. Our objective was to estimate the effect of Medicaid expansion on aggregate and individual-based ED utilization patterns within Maryland. METHODS: We performed a retrospective cross-sectional study of ED utilization patterns across Maryland, using data from Maryland's Health Services Cost Review Commission. We also analyzed utilization differences between pre-ACA (July 2012 to December 2013) uninsured patients who returned post-ACA (July 2014 to December 2015). RESULTS: The total number of ED visits in Maryland decreased by 36,531 (-1.2%) between the 6 quarters pre-ACA and the 6 quarters post-ACA. Medicaid-covered ED visits increased from 23.3% to 28.9% (159,004 additional visits), whereas uninsured patient visits decreased from 16.3% to 10.4% (181,607 fewer visits). Coverage by other insurance types remained largely stable between periods. We found no significant relationship between Medicaid expansion and changes in ED volume by hospital. For patients uninsured pre-ACA who returned post-ACA, the adjusted visits per person during 6 quarters was 2.38 (95% confidence interval 2.35 to 2.40) for those newly enrolled in Medicaid post-ACA compared with 1.66 (95% confidence interval 1.64 to 1.68) for those remaining uninsured. CONCLUSION: There was a substantial increase in patients covered by Medicaid in the post-ACA period, but this did not significantly affect total ED volume. Returning patients newly enrolled in Medicaid visited the ED more than their uninsured counterparts; however, this cohort accounted for only a small percentage of total ED visits in Maryland.