Triage ability of emergency medical services providers and patient disposition: a prospective study

Prehosp Disaster Med. 1999 Jul-Sep;14(3):174-9.

Abstract

Study objective: To determine the ability of emergency medical services (EMS) providers to subjectively triage patients with respect to hospital admission and to determine patient characteristics associated with increased likelihood of admission.

Methods: A prospective, cross-sectional study of a consecutive sample of patients arriving by ambulance during the month of February 1997 at an urban, university hospital, Emergency Department. Emergency medical services providers completed a questionnaire asking them to predict admission to the hospital and requested patient demographic information. Predictions were compared to actual patient disposition.

Results: A total of 887 patients were included in the study, and 315 were admitted to the hospital (36%). With respect to admission, EMS providers had an accuracy rate of 79%, with a sensitivity of 72% and specificity of 83% (kappa = 0.56). Blunt traumatic injury and altered mental status were the most common medical reasons for admission. Variables significantly associated with high admission rates were patients with age > 50 years, chest pain or cardiac complaints, shortness of breath or respiratory complaints, Medicare insurance, and Hispanic ethnicity. The EMS providers most accurately predicted admission for patients presenting with labor (kappa = 1.0), shortness of breath/respiratory complaints (kappa = 0.84), and chest pain (kappa = 0.77).

Conclusion: Emergency medical services providers can predict final patient disposition with reasonable accuracy, especially for patients presenting with labor, shortness of breath, or chest pain. Certain patient characteristics are associated with a higher rate of actual admission.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Aged
  • California
  • Cross-Sectional Studies
  • Emergency Service, Hospital / statistics & numerical data
  • Female
  • Forecasting
  • Hospitals, University / statistics & numerical data
  • Humans
  • Male
  • Middle Aged
  • Patient Admission* / statistics & numerical data
  • Professional Competence*
  • Prospective Studies
  • Socioeconomic Factors
  • Triage* / statistics & numerical data
  • Workforce