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Computer assisted assessment and advice for "non-serious" 999 ambulance service callers : the potential impact on ambulance despatch
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Dale, Jeremy, Higgins, J., Williams, S., Foster, T., Snooks, Helen, Crouch, R., Hartley-Sharpe, C., Glucksman, E., Hooper, R. and George, S. (2003) Computer assisted assessment and advice for "non-serious" 999 ambulance service callers : the potential impact on ambulance despatch. Emergency Medicine Journal, Vol.20 (No.2). pp. 178-183. doi:10.1136/emj.20.2.178 ISSN 1472-0205.
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Official URL: http://dx.doi.org/10.1136/emj.20.2.178
Abstract
Objective: To investigate the potential impact for ambulance services of telephone assessment and
triage for callers who present with non-serious problems (Category C calls) as classified by ambulance
service call takers.
Design: Pragmatic controlled trial. Calls identified using priority dispatch protocols as non-serious
were allocated to intervention and control groups according to time of call. Ambulance dispatch
occurred according to existing procedures. During intervention sessions, nurses or paramedics within
the control room used a computerised decision support system to provide telephone assessment, triage
and, if appropriate, offer advice to permit estimation of the potential impact on ambulance dispatch.
Setting: Ambulance services in London and the West Midlands.
Subjects: Patients for whom emergency calls were made to the ambulance services between April
1998 and May 1999 during four hour sessions sampled across all days of the week between 0700
and 2300.
Main outcome measures: Triage decision, ambulance cancellation, attendance at an emergency
department.
Results: In total, there were 635 intervention calls and 611 controls. Of those in the intervention group,
330 (52.0%) were triaged as not requiring an emergency ambulance, and 119 (36.6%) of these did
not attend an emergency department. This compares with 55 (18.1%) of those triaged by a nurse or
paramedic as requiring an ambulance (odds ratio 2.62; 95% CI 1.78 to 3.85). Patients triaged as not
requiring an emergency ambulance were less likely to be admitted to an inpatient bed (odds ratio
0.55; 95% CI 0.33 to 0.93), but even so 30 (9.2%) were admitted. Nurses were more likely than
paramedics to triage calls into the groups classified as not requiring an ambulance. After controlling
for age, case mix, time of day, day of week, season, and ambulance service, the results of a logistic
regression analysis revealed that this difference was significant with an odds ratio for nurses:paramedics
of 1.28 (95% CI 1.12 to 1.47).
Conclusions: The findings indicate that telephone assessment of Category C calls identifies patients
who are less likely to require emergency department care and that this could have a significant impact
on emergency ambulance dispatch rates. Nurses were more likely than paramedics to assess calls as
requiring an alternative response to emergency ambulance despatch, but the extent to which this relates
to aspects of training and professional perspective is unclear. However, consideration should be given
to the acceptability, reliability, and cost consequences of this intervention before it can be
recommended for full evaluation.
Item Type: | Journal Article | ||||
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Subjects: | R Medicine > RA Public aspects of medicine | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School | ||||
Library of Congress Subject Headings (LCSH): | Telephone in medicine, Triage (Medicine) -- Great Britain, Ambulance service -- Great Britain, Emergency medicine -- Decision making -- Computer programs | ||||
Journal or Publication Title: | Emergency Medicine Journal | ||||
Publisher: | BMJ Group | ||||
ISSN: | 1472-0205 | ||||
Official Date: | 2003 | ||||
Dates: |
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Volume: | Vol.20 | ||||
Number: | No.2 | ||||
Page Range: | pp. 178-183 | ||||
DOI: | 10.1136/emj.20.2.178 | ||||
Status: | Peer Reviewed | ||||
Access rights to Published version: | Open Access (Creative Commons) | ||||
Funder: | NHS Executive. Research and Development Directorate |
Data sourced from Thomson Reuters' Web of Knowledge
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