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Impact of Interventions for Patients Refusing Emergency Medical Services Transport
Author(s) -
Alicandro Jeanne,
Hollander Judd E.,
Henry Mark C.,
Sciammarella Joseph,
Stapleton Edward,
Gentile David
Publication year - 1995
Publication title -
academic emergency medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.221
H-Index - 124
eISSN - 1553-2712
pISSN - 1069-6563
DOI - 10.1111/j.1553-2712.1995.tb03244.x
Subject(s) - medicine , checklist , psychological intervention , documentation , medical record , intervention (counseling) , emergency medical services , emergency medicine , medical emergency , emergency department , surgery , nursing , computer science , cognitive psychology , programming language , psychology
ABSTRACT Objective: To evaluate the effect of a documentation checklist and on–line medical control contact on ambulance transport of out–of–hospital patients refusing medical assistance. Methods: Consecutive patients served by four suburban ambulance services who initially refused emergency medical services (EMS) transport to the hospital were prospectively enrolled. In phase 1 (control phase), all patients who initially refused medical attention or transport had an identifying data card completed. In phase 2 (documentation phase), out–of–hospital providers completed a similar data card that contained a checklist of high–risk criteria for a poor outcome if not transported. In phase 3 (intervention phase), a data card similar to that used in phase 2 was completed, and on–line medical control was contacted for all patients with high–risk criteria who refused transport. The primary endpoint was the percentage of patients transported to the hospital. Results: A total of 361 patients were enrolled. Transport rate varied by phase: control, 17 of 144 (12%); documentation, 11 of 150 (7%); and intervention, 12 of 67 (18%) (chi–square, p = 0. 023). Transport of high–risk patients improved with each intervention: control, two of 60 (3%); documentation, seven of 70 (10%); and intervention, 12 of 34 (35%) (chi–square, p = 0. 00003). Transport of patients without high–risk criteria decreased with each intervention: control, 15 of 84 (18%); documentation, four of 80 (5%); and intervention, 0 of 33 (0%) (p = 0. 0025). Of the 28 patients for whom medical control was contacted, 12 (43%) were transported to the hospital, and only three of these 12 patients (25%) were released from the ED. Conclusion: Contact with on–line medical control increased the likelihood of transport of high–risk patients who initially refused medical assistance. The appropriateness of the decreased transport rate of patients not meeting high–risk criteria needs further evaluation.

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