Patient throughput times and inflow patterns in Swedish emergency departments. A basis for ANSWER, A National SWedish Emergency Registry

We compared patient inflow patterns, total lengths of patient stay (LOS) and times to first physician at six Swedish university hospital EDs in 2009. Study data were retrieved from the hospitals' computerized information systems during single on-site visits to each participating hospital.All EDs provided throughput times and patient presentation data without significant problems. In all EDs, Monday was the busiest day and the fewest patients presented on Saturday. All EDs had a large increase in patient inflow before noon with a slow decline over the rest of the 24 h, and this peak and decline was especially pronounced in elderly patients. The average LOS was 4 h of which 2 h was spent waiting for the first physician. These throughput times showed a considerable diurnal variation in all EDs, with the longest times occurring 6-7 am and in the late afternoon.These results demonstrate the feasibility of collecting benchmarking data on quality of care targets within Swedish EM, and form the basis for ANSWER, A National SWedish Emergency Registry.Large resources are used in local and regional initiatives to improve the quality of emergency care. If such initiatives are to be successful, they need to be based on reliable data on the quality of care at the single emergency care center and, for benchmarking, at similar other centers. However, since benchmarking data are often lacking [1], quality improvements are commonly suboptimal and may not represent the best use of the available resources.Limited benchmarking data relating to emergency care may be obtained from existing multicenter patient databases or registries. However, almost all such registries focus on single disease groups [2-6] or specific medical interventions [3,7,8]. Very few registries focus on the emergency care process and none were primarily formed to reflect the quality of care. For instance, the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT [9-11]) is an emergency p