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ObjectiveOptimal care of adults with severe acute respiratory failure requires specific resources and expertise. We sought to measure geographic access to these centers in the United States.DesignCross-sectional analysis of geographic access to high capability severe acute respiratory failure centers in the United States. We defined high capability centers using two criteria: (1) provision of adult extracorporeal membrane oxygenation (ECMO), based on either 2008–2013 Extracorporeal Life Support Organization reporting or provision of ECMO to 2010 Medicare beneficiaries; or (2) high annual hospital mechanical ventilation volume, based 2010 Medicare claims.SettingNonfederal acute care hospitals in the United States.Measurements and Main ResultsWe defined geographic access as the percentage of the state, region and national population with either direct or hospital-transferred access within one or two hours by air or ground transport. Of 4,822 acute care hospitals, 148 hospitals met our ECMO criteria and 447 hospitals met our mechanical ventilation criteria. Geographic access varied substantially across states and regions in the United States, depending on center criteria. Without interhospital transfer, an estimated 58.5% of the national adult population had geographic access to hospitals performing ECMO and 79.0% had geographic access to hospitals performing a high annual volume of mechanical ventilation. With interhospital transfer and under ideal circumstances, an estimated 96.4% of the national adult population had geographic access to hospitals performing ECMO and 98.6% had geographic access to hospitals performing a high annual volume of mechanical ventilation. However, this degree of geographic access required substantial interhospital transfer of patients, including up to two hours by air.ConclusionsGeographic access to high capability severe acute respiratory failure centers varies widely across states and regions in the United States. Adequate referral center access in the case of disasters and pandemics will depend highly on local and regional care coordination across political boundaries.

A novel and straightforward spatial algorithm generated referral regions that were politically actionable and accountable for time-sensitive medical emergencies.

Objective Estimates of prehospital transport times are an important part of emergency care system research and planning; however the accuracy of these estimates is unknown. We examined the accuracy of three estimation methods against observed transport times in a large cohort of prehospital patient transports. Methods We performed a validation study using prehospital records in King County, Washington and southwestern Pennsylvania from 2002 to 2006 and 2005 to 2011, respectively. We generated transport time estimates using three methods: linear arc distance, Google Maps and ArcGIS Network Analyst. We assessed estimation error, defined as the absolute difference between observed and estimated transport time, and the proportion of estimated times that were within specified error thresholds. Based on the primary results, we then tested whether a regression estimate that incorporated population density, time-of-day and season could improve accuracy. Finally, we compared hospital catchment areas using each method with a fixed drive time. Results We analyzed 29,935 prehospital transports to 44 hospitals. The mean absolute error was 4.8 minutes (± 7.3) using linear arc, 3.5 minutes (± 5.4) using Google Maps and 4.4 minutes (± 5.7) using ArcGIS. All pairwise comparisons were statistically significant (p<0.01). Estimation accuracy was lower for each method among transports more than twenty minutes (mean absolute error was 12.7 minutes (± 11.7) for linear arc, 9.8 minutes (± 10.5) for Google Maps and 11.6 minutes (± 10.9) for ArcGIS). Estimates were within five minutes of observed transport time for 79% of linear arc estimates, 86.6% of Google Maps estimates and 81.3% of ArcGIS estimates. The regression-based approach did not substantially improve estimation. There were large differences in hospital catchment areas estimated by each method. Conclusion We showed that route-based transport time estimates demonstrate moderate accuracy. These methods can be valuable for informing a host of decisions related to the system organization and patient access to emergency medical care; however, they should be employed with sensitivity to their limitations.

Clinic non-arrival is associated with the interaction of longer travel time and lower income.