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1.
Acad Emerg Med ; 17(12): 1337-45, 2010 Dec.
Article in English | MEDLINE | ID: mdl-21122016

ABSTRACT

This article summarizes the discussions of the emergency medical services (EMS) breakout session at the June 2010 Academic Emergency Medicine consensus conference "Beyond Regionalization: Integrated Networks of Emergency Care." The group focused on prehospital issues such as the identification of patients by EMS personnel, protocol-driven destination selection, bypassing closer nondesignated centers to transport patients directly to more distant designated specialty centers, and the modes of transport to be used as they relate to the regionalization of emergency care. It is our hope that the proposed research agenda will be advanced in a way that begins to rigorously approach the unanswered research questions and that these answers, in turn, will lead to an evidence-based, cohesive, comprehensive, and more uniform set of guidelines that govern the delivery and practice of prehospital emergency care.


Subject(s)
Catchment Area, Health , Community Health Services/organization & administration , Emergency Medical Services/methods , Emergency Medical Services/organization & administration , Community Health Services/methods , Decision Making, Organizational , Health Services Research , Humans , Needs Assessment/organization & administration , Triage/organization & administration , United States
2.
Acad Emerg Med ; 16(6): 519-25, 2009 Jun.
Article in English | MEDLINE | ID: mdl-19438413

ABSTRACT

OBJECTIVES: The objective was to validate a previously derived prediction rule for hospital admission using routinely collected out-of-hospital information. METHODS: The authors performed a multicenter retrospective cohort study of 1,500 randomly selected, adult patients transported to six separate emergency departments (EDs; three community and three academic hospitals in three separate health systems) by a city-run emergency medical services (EMS) system over a 1-year period. Patients younger than 18 years or who bypassed the ED to be evaluated by trauma, obstetric, or psychiatric teams were excluded. The score consisted of six weighted elements that generated a total score (0-14): age >or= 60 years (3 points); chest pain (3); shortness of breath (3); dizzy, weakness, or syncope (2); history of cancer (2); and history of diabetes (1). Receiver operator characteristic (ROC) curves for the decision rule and admission rates were calculated among individual hospitals and for the entire cohort. RESULTS: A total of 1,102 patients met inclusion criteria. The admission rate for the entire cohort was 40%, and individual hospital admission rates ranged from 28% to 57%. Overall, 34% had a score of >or=4, and 29% had a score of >or=5. Area under the ROC curve (AUC) for the combined cohort was 0.83 for all admissions and 0.72 for intensive care unit (ICU) admissions; AUCs at individual hospitals ranged from 0.72 to 0.85. The admission rate for a score of >or=4 was 77%; for a score of >or=5 the admission rate was 80%. CONCLUSIONS: The ability of this EMS rule to predict the likelihood of hospital admission appears valid in this multicenter cohort. Further studies are needed to measure the impact and feasibility of using this rule to guide decision-making.


Subject(s)
Emergency Medical Services/statistics & numerical data , Patient Admission/statistics & numerical data , Patient Discharge/statistics & numerical data , Academic Medical Centers , Cohort Studies , Databases, Factual , Emergency Service, Hospital/statistics & numerical data , Female , Hospitals, Community , Humans , Intensive Care Units , Logistic Models , Male , Middle Aged , Philadelphia , ROC Curve , Reproducibility of Results , Retrospective Studies , Transportation of Patients
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