Hostname: page-component-745bb68f8f-grxwn Total loading time: 0 Render date: 2025-01-11T08:41:51.413Z Has data issue: false hasContentIssue false
  • English
  • Français

Does Emergency Medical Dispatch Priority Predict Delphi Process-Derived Levels of Prehospital Intervention?

Published online by Cambridge University Press:  28 June 2012

Karl A. Sporer ,
Alan M. Craig ,
Nicholas J. Johnson  and
Clement C. Yeh
Karl A. Sporer*
Affiliation:
University of California, San Francisco, Department of Medicine, San Francisco, California, USA Department of Emergency Services, San Francisco General Hospital, San Francisco, California, USA
Alan M. Craig
Affiliation:
Toronto Emergency Medical Services, Toronto, Ontario Canada
Nicholas J. Johnson
Affiliation:
University of California, San Francisco, School of Medicine, San Francisco, California, USA
Clement C. Yeh
Affiliation:
University of California, San Francisco, Department of Medicine, San Francisco, California, USA Department of Emergency Services, San Francisco General Hospital, San Francisco, California, USA
*
Emergency Services, Room 1E21, San Francisco General Hospital, 1001 Potrero Avenue, San Francisco, California 94110, USA E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective:

The Medical Priority Dispatch System (MPDS) is an emergency medical dispatch system widely used to prioritize 9-1-1 calls and optimize resource allocation. This study evaluates whether the assigned priority predicts a Delphi process-derived level of prehospital intervention in each emergency medical dispatch category.

Methods:

All patients given a MPDS priority in a suburban California county from 2004–2006 were included. A Delphi process of emergency medical services (EMS) professionals in another system developed the following categories of prehospital treatment representing increasing acuity, which were adapted for this study: advanced life support (ALS) intervention, ALS–Stat, and ALS–Critical. The sensitivities and specificities of MPDS priority for level of prehospital intervention were determined for each MPDS category.

Results:

A total of 65,268 patients met inclusion criteria, representing 61% of EMS calls during the study period. The overall sensitivities of high-priority dispatch codes for ALS, ALS-Stat, and ALS-Critical interventions were 83% (95% confidence interval 83–84%), 83% (82–84%), and 94% (92–96%). Overall specificities were: ALS, 32% (31–32%); ALS-Stat, 31% (30–31%); and ALS-Critical 28% (28–29%). Compared to calls assigned to a low priority, calls with high-priority dispatch codes were more likely to receive ALS interventions by 22%, ALS-Stat by 20%, and ALS-Critical by 32%. A low priority dispatch code decreased the likelihood of ALS interventions by 48%, ALS-Stat by 45%, and ALS-Critical by 80%. Among high-priority dispatch codes, the rates of interventions were: ALS 26%, ALS-Stat 22%, and ALS-Critical 1.5%, all of which were significantly greater than low-priority calls (p <0.05) [ALS 13%, ALS-Stat 11%, and ALS-Critical 0.2%]. Major MPDS were categories with high sensitivities (>95%) for ALS interventions included breathing problems, cardiac or respiratory arrest/death, chest pain, stroke, and unconscious/fainting; these categories had an average specificity of 3%. Medical Priority Dispatch System categories such as back pain, unknown problem, and traumatic injury had sensitivities for ALS interventions <15%.

Conclusions:

The MPDS is moderately sensitive for the Delphi process derived ALS, ALS-Stat, and ALS-Critical intervention levels, but non-specific. A low MPDS priority is predictive of no prehospital intervention. A high priority, however, is of little predictive value for ALS, ALS-Stat, or ALSCritical interventions.

Keywords

ambulanceambulance utilizationemergencyclassification of emergenciesEmergency Medical Dispatchemergency medical service communication standardsemergency medical service communication systemsemergency medical servicesemergency medical services standardsemergency medical services utilizationrisk assessmentstandardstriage
Type
Original Research
Information
Prehospital and Disaster Medicine , Volume 25 , Issue 4 , August 2010 , pp. 309 - 317
Copyright
Copyright © World Association for Disaster and Emergency Medicine 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Bailey, ED, O'Connor, RE, Ross, RW: The use of emergency medical dispatch protocols to reduce the number of inappropriate scene responses made by advanced life support personnel. Prehosp Emerg Care 2000;4(2):186–189.CrossRefGoogle ScholarPubMed
2.Flynn, J, Archer, F, Morgans, A: Sensitivity and specificity of the Medical Priority Dispatch System in detecting cardiac arrest emergency calls in Melbourne. Prehosp Disaster Med 2006;21(2):72–76.Google Scholar
3.Shah, MN, Bishop, P, Lerner, EB, et al: Derivation of emergency medical services dispatch codes associated with low-acuity patients. Prehosp Emerg Care 2003;7(4):434–439.CrossRefGoogle ScholarPubMed
4.Myers, JB, Hinchey, P, Zalkin, J, et al: EMS dispatch triage criteria can accurately identify patients without high-acuity illness or injury. Prehospital Emerg Care 2005;9:119.Google Scholar
5.Shah, MN, Bishop, P, Lerner, EB, et al: Validation of EMD dispatch codes associated with low-acuity patients Prehosp Emerg Care 2005;9(1):24–31.CrossRefGoogle Scholar
6.Michael, GE, Sporer, KA: Validation of low-acuity emergency medical services dispatch codes. Prehosp Emerg Care 2005;9(4):429–433.Google Scholar
7.Palumbo, L, Kubincanek, J, Emerman, C, et al: Performance of a system to determine EMS dispatch priorities. Am J Emerg Med 1996;14(4):388–390.Google Scholar
8.Neely, KW, Eldurkar, JA, Drake, ME: Do emergency medical services dispatch nature and severity codes agree with paramedic field findings? Acad Emerg Med 2000;7(2):174–180.CrossRefGoogle ScholarPubMed
9.Feldman, MJ, Verbeek, PR, Lyons, DG, et al: Comparison of the medical priority dispatch system to an out-of-hospital patient acuity score. Acad Emerg Med 2006;13(9):954–960.Google Scholar
10.Craig, A, Schwartz, B, Feldman, M: Development of evidence-based dispatch response plans to optimize ALS paramedic response in an urban EMS system (abstract). Prehosp Emerg Care 2006;10(1):114.Google Scholar
11.Sporer, KA, Youngblood, GM, Rodriguez, RM: The ability of emergency medical dispatch codes of medical complaints to predict ALS prehospital interventions. Prehosp Emerg Care 2007;11(2):192–198.Google Scholar
12.Heward, A, Damiani, M, Hartley-Sharpe C: Does the use of the Advanced Medical Priority Dispatch System affect cardiac arrest detection? Emerg Med J 2004;21(1):115–118.CrossRefGoogle ScholarPubMed
13.Vaillancourt, C, Verma, A, Trickett, J, et al: Evaluating the effectiveness of dispatch-assisted cardiopulmonary resuscitation instructions. Acad Emerg Med 2007;14(10):877–883.Google Scholar
14.Clark, JJ, Culley, L, Eisenberg, M, et al: Accuracy of determining cardiac arrest by emergency medical dispatchers. Ann Emerg Med 1994;23(5):1022–1026.Google Scholar
15.Hallstrom, A, Cobb, L, Johnson, E, et al: Cardiopulmonary resuscitation by chest compression alone or with mouth-to-mouth ventilation. N Engl J Med 2000;342(21):1546–1553.Google Scholar
16.Clawson, J, Olola, C, Heward, A, et al: Cardiac arrest predictability in seizure patients based on emergency medical dispatcher identification of previous seizure or epilepsy history. Resuscitation 2007;75(2):298–304.Google Scholar
17.Clawson, J, Olola, C, Heward, A, et al: Ability of the medical priority dispatch system protocol to predict the acuity of “unknown problem” dispatch response levels. Prehosp Emerg Care 2008;12(3):290–296.Google Scholar
18.Clawson, J, Olola, C, Heward, A, et al: The Medical Priority Dispatch System's ability to predict cardiac arrest outcomes and high acuity pre-hospital alerts in chest pain patients presenting to 9-9-9. Resuscitation 2008.Google Scholar
19.Clawson, J, Olola, C, Scott, G, et al: Effect of a Medical Priority Dispatch System key question addition in the seizure/convulsion/fitting protocol to improve recognition of ineffective (agonal) breathing. Resuscitation 2008.CrossRefGoogle Scholar
20.Clawson, J, Olola, CH, Heward, A, et al: Accuracy of emergency medical dispatchers’ subjective ability to identify when higher dispatch levels are warranted over a Medical Priority Dispatch System automated protocol's recommended coding based on paramedic outcome data. Emerg Med J 2007;24(8):560–563.Google Scholar
21.Ramanujam, P, Guluma, KZ, Castillo, EM, et al: Accuracy of stroke recognition by emergency medical dispatchers and paramedics—San Diego experience. Prehosp Emerg Care 2008;12(3):307–313.Google Scholar
22.Neely, KW, Eldurkar, J, Drake, ME: Can current EMS dispatch protocols identify layperson-reported sentinel conditions? Prehosp Emerg Care 2000;4(3):238–244.Google Scholar
23.Calle, P, Houbrechts, H, Lagaert, L, et al: How to evaluate an emergency medical dispatch system: A Belgian perspective. Eur J Emerg Med 1995;2(3):128–135.Google Scholar
24.Sporer, KA, Johnson, NJ, Yeh, CC, et al: Can emergency medical dispatch codes predict prehospital interventions for common 9-1-1 call types? Prehosp Emerg Care 2008;12(4):470–478.Google Scholar
25.Kuzma, K, Sporer, KA, Michael, GE, et al: Factors influencing prehospital placement and utilization of peripheral intravenous catheters. Journal of Emergency Medicine 2009;36(4):357–362.Google Scholar
26.Kahn, CA, Pirrallo, RG, Kuhn, EM: Characteristics of fatal ambulance crashes in the United States: an 11-year retrospective analysis. Prehosp Emerg Care 2001;5(3):261–269.CrossRefGoogle ScholarPubMed