We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Rapid transport from scene to closest trauma center requires optimal use of public safety first responder (FR), basic life support (BLS), advanced life support (ALS), and transport resources (ground or air). In some parts of this regional emergency medical services (EMS) system, on-scene ALS requires contact with on-line medical command (OLMC) to obtain authorization for air medical helicopter (AMH) dispatch, because some EMS medical directors believe that this may decrease overutilization of AMH services.
Hypothesis:
The hypothesis of this study was that requiring prior OLMC for AMH dispatch prolongs mean time to a trauma center versus either FR or BLS request for AMH.
Methods:
Computer mapping programs were used to model the most rapid driving time to the closest trauma center from 167 actual AMH responses to the scene of a motor vehicle accident. In an OLMC-ALS model, only OLMC-ALS can request an AMH. In a BLS model, BLS units arrive on the scene and the crew requests simultaneous dispatch of an ALS response and an AMH. In the FR model, on arrival at the scene, a FR requests simultaneous dispatch of a BLS unit, an ALS unit, and an AMH.
Results:
The OLMC-ALS model resulted in a longer mean value for time to trauma center by an AMH than did the computer model for all ground transport settings. The FR model yielded a shorter mean time for AMH compared with the mean values for time to trauma center for all settings. Differences in mean values for time in urban settings were small (ground: 42 minutes, air: 36 minutes), whereas those for the suburban (ground: 52 minutes, air: 41 minutes), and those for rural (ground: 69 minutes, air: 47 minutes) were significant clinically. For the BLS model, these differences persisted, but were significant clinically only in the rural setting (ground: 68 minutes, air: 53 minutes).
Conclusions:
Optimal use of AMH requires balancing the need for early helicopter dispatch to fully exploit its speed advantage with the disadvantage of expensive overutilization. This computer model indicates that the best person to request AMH varies by venue: in urban settings, the OLMC physician should request AMH dispatch; in suburban venues, BLS should request AMH dispatch; and in rural venues, FRs should request AMH dispatch.
There is a growing interest in cases in which emergency medical services (EMS) providers evaluate a patient, but do not transport the patient to a hospital. A subset of these cases, the patient-initiated refusal (PIR) in which the patient refused care and transport, was studied and evaluated. The objectives of the study were to examine the adequacy of ambulance call report documentation in PIR, to examine the clinical outcome of these patients in one hospital-based, suburban EMS system, and to assess the potential impact of on-line medical command (OLMC) on cases of PIR.
Methods:
The system studied is a hospital-based, transport-capable, advanced life support service in a suburban EMS system, with an annual call volume of 4,200 runs. During the 6-month study period, all ambulance call reports completed by the paramedics and medical command control forms completed by medical command physicians were examined, and cases of PIR collected. Each ambulance call report was examined for adequacy of documentation. Patient outcome was determined from emergency department records and telephone follow-up.
Results:
Eighty-five PIRs were documented during the study period. Four cases were excluded because of a missing ambulance call reports and/or medical command control forms, leaving 81 PIRs for analysis. Despite policy requiring OLMC in cases of PIR, OLMC was established in only 23 PIRs (28%). Of these, two (9%) had inadequate ambulance call report documentation. Of the 58 PIR in which OLMC was not established, 25 (43%) had inadequate ambulance call report documentation (p <0.001, Fisher's exact test). Follow-up was obtained for 54 (67%) PIR. Of these, 37 (68%) did not subsequently see a physician, and all needed no further medical care. Seven (13%) saw their own physicians within a few days of the initial refusal of prehospital care, and had no further problems. Ten patients were seen in an emergency department within a few days. Three (6%) were discharged, and did well. Seven (13%) were admitted to the hospital, with four (7%) admitted to monitored beds, and three (6%) to unmonitored beds. There were no deaths.
Conclusions:
Ambulance call report documentation is better with OLMC than without. Patients who initially refuse care may be ill, and some ultimately will be hospitalized. Further research may elucidate a role for OLMC in preventing refusals by incompetent patients, convincing patients who are competent but appear ill to accept transport, and assisting paramedics with other difficult or unusual circumstances.
The aim of this study was to compare the patient care measures provided by paramedics according to standing orders versus measures ordered by direct [on-line] medical command in order to determine the types and frequency of medical command orders.
Design:
Prospective identification of patient care measures done as part of a prehospital quality assurance program.
Setting:
An urban paramedic service in the northeast United States with direct medical command from three local hospitals.
Participants:
One thousand eight paramedic reports from October 1992 through March 1993.
Interventions:
All patient care interventions recorded as done by standing orders or by direct medical command orders. Errors in patient care were determined by the same criteria as in the prior two studies of the same system.
Results:
Direct medical command gave orders in 143/1,008 (14.2%) cases. Paramedics performed 2,453/2,624 (93.5%) of the total patient care interventions using standing orders. In 61 cases (6.1 %), medical command ordered a potentially beneficial intervention not specified by standing orders or not done by the paramedic. 21/171 (12.3%) command orders were for additional doses of epinephrine or atropine in cardiac arrest cases (where the initial doses had been given under standing orders), and 59/171 (34.5%) were for interventions already mandated or permitted by standing orders. The paramedic error rate was 0.6%, and the medical command error rate was 1.8% (unchanged form the prior study of the same standing-orders system).
Conclusion:
Direct medical command gave orders in 14% of cases in this standing-orders system, but 35% of command orders only reiterated the standing orders. More selective and reduced uses of on-line command could be done in this system with no change in the types or numbers of patient care interventions performed.
Recommend this
Email your librarian or administrator to recommend adding this to your organisation's collection.