Determining minimum staffing levels during snowstorms using an integrated simulation, regression, and reliability model

Abstract

Emergency medical services (EMS) provide life-saving care and hospital transport to patients with severe trauma or medical conditions. Severe weather events, such as snow events, may lead to adverse patient outcomes by increasing call volumes and service times. Adequate staffing levels during such weather events are critical for ensuring that patients receive timely care. To determine staffing levels that depend on weather, we propose a model that uses a discrete event simulation of a reliability model to identify minimum staffing levels that provide timely patient care, with regression used to provide the input parameters. The system is said to be reliable if there is a high degree of confidence that ambulances can immediately respond to a given proportion of patients (e.g., 99 %). Four weather scenarios capture varying levels of snow falling and snow on the ground. An innovative feature of our approach is that we evaluate the mitigating effects of different extrinsic response policies and intrinsic system adaptation. The models use data from Hanover County, Virginia to quantify how snow reduces EMS system reliability and necessitates increasing staffing levels. The model and its analysis can assist in EMS preparedness by providing a methodology to adjust staffing levels during weather events. A key observation is that when it is snowing, intrinsic system adaptation has similar effects on system reliability as one additional ambulance.

The linkage among ambulance transports, death and climate parameters in Asahikawa City, Japan

“…In addition, the difference in snowfall, city location and coping with winter weather such as wearing suitable clothes, between Asahikawa City and Takamatsu City may have influenced the findings in this study. Nevertheless, it is reasonable to suggest that dealing with winter weather effects, i.e., innovation in terms of thermal energy metabolism, in cities, for individuals and groups to help them cope with [17] winter weather may be required in the Asahikawa area as well as other areas in Japan (Fig. 1).…”

Weather and Temporal Factors Associated with Use of Emergency Medical Services

“…As the need for prehospital care has increased, EMS agencies have faced substantial challenges regarding reimbursement for EMS response (7)(8)(9)(10), along with staffing and other operational needs to meet the increase in demand (11)(12)(13). To adequately address this increased burden on EMS, better data are needed to predict the timing and frequency of EMS utilization.…”

Isochrones as Indicators of the Influence of Traffic in Public Health: A Visual Simulation Application in Ávila, Spain

“…Many factors may affect this reaction time, all of which are dynamic and probabilistic in nature. Weather conditions may slow travelling times, for example, snow [ 7 ] and fog [ 8 ]. Road conditions and layout, especially on rural areas [ 9 ], or even congestions [ 10 ] may force the drivers to reduce speed, stop or take a different longer route.…”