Literature DB >> 16798145

How well do paramedics predict admission to the hospital? A prospective study.

Saul D Levine1, Christopher B Colwell, Peter T Pons, Craig Gravitz, Jason S Haukoos, Kevin E McVaney.   

Abstract

A study was designed to determine whether paramedics accurately predict which patients will require admission to the hospital, and in those requiring admission, whether they will need a ward bed or intensive care unit (ICU) monitoring. This prospective, cross-sectional study of consecutive Emergency Medical Service (EMS) transport patients was conducted at an urban city hospital. Paramedics were asked to predict if the patient they were transporting would require admission to the hospital, and if so, whether that patient would be admitted to a ward bed or require an ICU bed. Predictions were compared to actual patient disposition. During the study period, 1349 patients were transported to our hospital. Questionnaires were submitted in 985 cases (73%) and complete data were available for 952 (97%) of these patients. Paramedics predicted 202 (22%) patients would be admitted to the hospital, of whom 124 (61%) would go the ward and 78 (39%) would require intensive care. The actual overall admission rate was 21%, although the sensitivity of predicting any admission was 62% with a positive prediction value (PPV) of 59%. Further, the paramedics were able to predict admission to intensive care with a sensitivity of 68% and PPV of 50%. It is concluded that paramedics have very limited ability to predict whether transported patients require admission and the level of required care. In our EMS system, the prehospital diversion policies should not be based solely on paramedic determination.

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Year:  2006        PMID: 16798145     DOI: 10.1016/j.jemermed.2005.08.007

Source DB:  PubMed          Journal:  J Emerg Med        ISSN: 0736-4679            Impact factor:   1.484


  17 in total

1.  How Well Do EMS Providers Predict Intracranial Hemorrhage in Head-Injured Older Adults?

Authors:  Simson Hon; Samuel D Gaona; Mark Faul; James F Holmes; Daniel K Nishijima
Journal:  Prehosp Emerg Care       Date:  2019-04-23       Impact factor: 3.077

2.  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

3.  Motor vehicle crash severity estimations by physicians and prehospital personnel.

Authors:  Nathan Cleveland; Christopher Colwell; Erica Douglass; Emily Hopkins; Jason S Haukoos
Journal:  Prehosp Emerg Care       Date:  2014-03-26       Impact factor: 3.077

4.  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

5.  Prehospital Trauma Triage Decision-making: A Model of What Happens between the 9-1-1 Call and the Hospital.

Authors:  Courtney Marie Cora Jones; Jeremy T Cushman; E Brooke Lerner; Susan G Fisher; Christopher L Seplaki; Peter J Veazie; Erin B Wasserman; Ann Dozier; Manish N Shah
Journal:  Prehosp Emerg Care       Date:  2015-05-27       Impact factor: 3.077

6.  Obstetric emergencies at the United States-Mexico border crossings in El Paso, Texas.

Authors:  Jill A McDonald; Karen Rishel; Miguel A Escobedo; Danielle E Arellano; Timothy J Cunningham
Journal:  Rev Panam Salud Publica       Date:  2015-02

7.  Pre-resuscitation lactate and hospital mortality in prehospital patients.

Authors:  Adam Z Tobias; Francis X Guyette; Christopher W Seymour; Brian P Suffoletto; Christian Martin-Gill; Jorge Quintero; Jeffrey Kristan; Clifton W Callaway; Donald M Yealy
Journal:  Prehosp Emerg Care       Date:  2014-02-18       Impact factor: 3.077

8.  Unnecessary Use of Red Lights and Sirens in Pediatric Transport.

Authors:  Beech Burns; Matthew L Hansen; Stacy Valenzuela; Caitlin Summers; Joshua Van Otterloo; Barbara Skarica; Craig Warden; Jeanne-Marie Guise
Journal:  Prehosp Emerg Care       Date:  2016-01-25       Impact factor: 3.077

9.  [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

10.  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

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