Literature DB >> 12385603

Can paramedics accurately identify patients who do not require emergency department care?

Salvatore Silvestri1, Steven G Rothrock, Dan Kennedy, Jay Ladde, Marsha Bryant, Joseph Pagane.   

Abstract

OBJECTIVE: To determine whether paramedics can identify patients contacting 9-1-1 who do not require emergency department (ED) care.
METHODS: The setting was an urban county with a two-tiered, dual response to 9-1-1 calls comprising eight local fire departments with advanced life support capabilities and a private advanced life support 9-1-1 agency with primary transport responsibilities (approximately 39,000 of the 78,000 total system patient transports in this county per year). The study population consisted of consecutive patients transported by a private transporting paramedic agency. After patient contact and stabilization, paramedics completed a survey detailing the necessity for transport to an ED for each patient. Prior to data analysis, it was determined that patients would be designated as requiring ED care if they 1) were admitted, 2) required surgical, surgical subspecialty, obstetric, or gynecologic consult, or 3) required advanced radiologic procedures (excluding plain films). Sensitivity, specificity, and predictive values for paramedic assessment of necessity for ED care were calculated with 95% confidence intervals (95% CIs).
RESULTS: Over the study period, 313 patients were enrolled. Paramedic assessment was 81% sensitive (72-88%, 95% CI) and 34% specific (28-41%, 95% CI) in predicting requirement for ED care. In 85 cases where paramedics felt ED transport was unnecessary, 27 (32%) met criteria for ED treatment, including 15 (18%) who were admitted and five (6%) who were admitted to an intensive care unit.
CONCLUSION: In this urban system, paramedics cannot reliably predict which patients do and do not require ED care.

Entities:  

Mesh:

Year:  2002        PMID: 12385603     DOI: 10.1080/10903120290937987

Source DB:  PubMed          Journal:  Prehosp Emerg Care        ISSN: 1090-3127            Impact factor:   3.077


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