Abstract
OBJECTIVESThe risk of cross infection in a busy emergency department (ED) is a serious public health concern, especially in times of pandemic threats. We simulated cross infections due to respiratory diseases spread by large droplets using empirical data on contacts (ie, close-proximity interactions of ≤1m) in an ED to quantify risks due to contact and to examine factors with differential risks associated with them.DESIGNProspective study.PARTICIPANTSHealth workers (HCWs) and patients.SETTINGA busy ED.METHODSData on contacts between participants were collected over 6 months by observing two 12-hour shifts per week using a radiofrequency identification proximity detection system. We simulated cross infection due to a novel agent across these contacts to determine risks associated with HCW role, chief complaint category, arrival mode, and ED disposition status.RESULTSCross-infection risk between HCWs was substantially greater than between patients or between patients and HCWs. Providers had the least risk, followed by nurses, and nonpatient care staff had the most risk. There were no differences by patient chief complaint category. We detected differential risk patterns by arrival mode and by HCW role. Although no differential risk was associated with ED disposition status, 0.1 infections were expected per shift among patients admitted to hospital.CONCLUSIONThese simulations demonstrate that, on average, 11 patients who were infected in the ED will be admitted to the hospital over the course of an 8-week local influenza outbreak. These patients are a source of further cross-infection risk once in the hospital.Infect Control Hosp Epidemiol 2018;39:688-693.
Highlights
Understanding the dynamics of cross infection in the emergency department (ED) will facilitate the development of improved mitigation efforts
The presentation of a patient infectious with Ebola virus disease to an ED in Dallas, Texas, resulted in a need to monitor more than 180 individuals, many of them hospital personnel, who were in close contact with this patient or with 2 nurses who became infected after exposure to this patient.[2]
Having found that healthcare workers (HCWs) played a large role in cross transmission, we evaluated the influence of staff role
Summary
Data on contacts that occurred ≤1 m distance between patients and staff in the busy ED of a large urban hospital were collected using an RFID system described elsewhere.[13]. The data we collected about the contacts were the study IDs of the 2 individuals involved and length of contact. We had planned to observe contacts among patients and staff during two 12-hour shifts per week for 1 year. We observed 293,181 contacts of 4,732 patient and 85 staff participants during 81 shifts during the study year (July 1, 2009, to June 30, 2010). We restricted our analysis to data from the first 6 months of the study (35 shifts). We restricted analysis to this subset of shifts because examination of participation by patients and staff across the year showed a significant decline. We restricted analyses to shifts in the first 6 months of our observation period because the decline in staff participation started at the beginning of the second half of the year. The observations included here should not be biased by the presence of missing data
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