Literature DB >> 16147483

Prehospital provider prediction of emergency department disposition: implications for selective diversion.

Timothy G Price1, Edmond A Hooker, Joshua Neubauer.   

Abstract

OBJECTIVE: To determine whether emergency medical services (EMS) personnel can use selective diversion and accurately predict those patients being transported who are unlikely to need a critical care bed and those patients unlikely to require admission to the hospital.
METHODS: This was a prospective study of patients being transported by the local EMS service. The EMS providers were asked to predict disposition of the patient. Emergency department (ED) personnel were asked to indicate on the study sheet the actual disposition of the patient.
RESULTS: A total of 411 patient transports were entered into the study. The EMS providers predicted that 246 (59.9%) would be discharged to home, 96 (23.3%) would be admitted to a floor bed, and 69 (16.8%) would be admitted to a critical care bed (CCB). The actual dispositions of the patients were: 253 (61.6%) discharged to home, 99 (24.1%) admitted to a floor bed, and 59 (9.9%) admitted to a CCB. The EMS providers performed well at predicting those patients who would not need a CCB: negative predictive value 96.2% (95% confidence interval [CI]) (93.4-97.9). They also correctly identified most patients who were discharged to home: 209 of 253, 85% (95% CI is equal to 79.7-89.1%).
CONCLUSIONS: EMS providers appear to be capable of using selective diversion categories. EMS providers correctly identified most patients who will not require a critical care bed. The EMS providers also correctly identified most patients who will be discharged from the ED after treatment.

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Mesh:

Year:  2005        PMID: 16147483     DOI: 10.1080/10903120590962012

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


  5 in total

1.  Identification of a neurologic scale that optimizes EMS detection of older adult traumatic brain injury patients who require transport to a trauma center.

Authors:  Erin B Wasserman; Manish N Shah; Courtney M C Jones; Jeremy T Cushman; Jeffrey M Caterino; Jeffrey J Bazarian; Suzanne M Gillespie; Julius D Cheng; Ann Dozier
Journal:  Prehosp Emerg Care       Date:  2014-10-07       Impact factor: 3.077

2.  Prediction of critical illness during out-of-hospital emergency care.

Authors:  Christopher W Seymour; Jeremy M Kahn; Colin R Cooke; Timothy R Watkins; Susan R Heckbert; Thomas D Rea
Journal:  JAMA       Date:  2010-08-18       Impact factor: 56.272

3.  [Prediction of further hospital treatment for emergency patients by emergency medical service physicians].

Authors:  M Bernhard; S Trautwein; R Stepan; P Zahn; C-A Greim; A Gries
Journal:  Anaesthesist       Date:  2014-04-03       Impact factor: 1.041

4.  Prediction of patient disposition: comparison of computer and human approaches and a proposed synthesis.

Authors:  Yuval Barak-Corren; Isha Agarwal; Kenneth A Michelson; Todd W Lyons; Mark I Neuman; Susan C Lipsett; Amir A Kimia; Matthew A Eisenberg; Andrew J Capraro; Jason A Levy; Joel D Hudgins; Ben Y Reis; Andrew M Fine
Journal:  J Am Med Inform Assoc       Date:  2021-07-30       Impact factor: 4.497

5.  Unnecessary emergency medical services transport associated with alcohol intoxication.

Authors:  Christine Van Dillen; Sun Hyu Kim
Journal:  J Int Med Res       Date:  2017-06-27       Impact factor: 1.671

  5 in total

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