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Association between Patient Unconscious or Not Alert Conditions and Cardiac Arrest or High-Acuity Outcomes within the Medical Priority Dispatch System “Falls” Protocol

  • Jeff Clawson (a1), Christopher Olola (a1) (a2), Greg Scott (a1), Bryon Schultz (a3), Richard Pertgen (a4), Don Robinson (a5), Barry Bagwell (a5) and Brett Patterson (a1)...

Abstract

Introduction:

Falls are one of the most common types of complaints received by 9-1-1 emergency medical dispatch centers. They can be accidental or may be caused by underlying medical problems. Though not alert” falls patients with severe outcomes mostly are “hot” transported to the hospital, some of these cases may be due to other acute medical events (cardiac, respiratory, circulatory, or neurological), which may not always be apparent to the emergency medical dispatcher (EMD) during call processing.

Objectives:

The objective of this study was to characterize the risk of cardiac arrest and “hot-transport” outcomes in patients with “not alert” condition, within the Medical Priority Dispatch System (MPDS®) Falls protocol descriptors.

Methods:

This retrospective study used 129 months of de-identified, aggregate, dispatch datasets from three US emergency communication centers. The communication centers used the Medical Priority Dispatch System version 11.3–OMEGA type (released in 2006) to interrogate Emergency Medical System callers, select dispatch codes assigned to various response configurations, and provide pre-arrival instructions. The distribution of cases and percentages of cardiac arrest and hot-transport outcomes, categorized by MPDS® code, was profiled. Assessment of the association between MPDS® Delta-level 3 (D-3) “not alert” condition and cardiac arrest and hot-transport outcomes then followed.

Results:

Overall, patients within the D-3 and D-2 “long fall” conditions had the highest proportions (compared to the other determinants in the “falls” protocol) of cardiac arrest and hot-transport outcomes, respectively. “Not alert” condition was associated significantly with cardiac arrest and hot-transport outcomes (p < 0.001).

Conclusions:

The “not alert” determinant within the MPDS® “fall” protocol was associated significantly with severe outcomes for short falls (<6 feet; 2 meters) and ground-level falls. As reported to 9-1-1, the complaint of a “fall” may include the presence of underlying conditions that go beyond the obvious traumatic injuries caused by the fall itself.

Copyright

Corresponding author

International Academies of Emergency Dispatch, 139 East South Temple, Suite 200, Salt Lake City, Utah 84111, USA E-mail: jeff.clawson@emergencydispatch.org

References

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1.Davies, AJ, Kenny, RA: Falls presenting to the accident and emergency department: types of presentation and risk factor profile. Age Ageing 1996;25(5):362366.
2.Urgences Sante, Personal communication, 1999.
3.Clawson, J: Manhunt! Improve AED response: helping police enrich “The cardiac arrest quotient”. The National Center for Early Defibrillation from the special educational supplement, “The Life You Save. Community Defibrillation Programs and the Public Safety Responder”, February 2002.
4.International Academies of Emergency Dispatch (IAED): Emergency Medical Dispatch (EMD) v11.3 UKE-Ω Protocol. Advanced Medical Priority Dispatch System®, 2006.
5.Hinchey, P, Myers, B, Zalkin, J, Lewis, R, Garner, D: Low acuity EMS dispatch criteria can reliably identify patients without high-acuity illness or injury. Prehosp Emerg Care 2007;11:4248.
6.Michael, GE, Sporer, KA: Validation of low-acuity Emergency Medical Services Dispatch codes. Prehosp Emerg Care 2005;9(4):429433.
7.Shah, MN, Bishop, P, Lerner, EB, Czapranski, T, Davis, EA: Derivation of emergency medical services dispatch codes associated with low-acuity patients. Prehosp Emerg Care 2003;7(4):434439.
8.Sporer, KA, Youngblood, GM, Rodriguez, RM: The ability of Emergency Medical Dispatch codes of medical complaints to predict ALS prehospital interventions. Prehosp Emerg Car e 2007;11(2):192198.
9.Kupas, DF, Dula, DJ, Pino, BJ: Patient outcome using medical protocol to limit “lights and siren” transport. Prehosp Disaster Med 1994;9(4):226229.
10.Garza, AG, Gratton, MC, McElroy, J, Lindholm, D, Glass, E: The association of dispatch and patient acuity. Prehosp Emerg Care 2008;12:2429.
11.Clawson, J, Olola, C, Heward, A, Patterson, B, Scott, G: 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; 78(3):298306.
12.Clawson, J, Olola, C, Scott, G, Heward, A, Patterson, B: 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;79:257264.
13.Clawson, J, Olola, C, Heward, A, Patterson, B: Cardiac arrest predictability in seizure patients based on emergency medical dispatcher identification of previous seizure or epilepsy history. Resuscitation 2007;75(2):298304.
14.Clawson, J, Olola, CH, Heward, A, Scott, G, Patterson, B: 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):560563.
15.Clawson, J, Olola, C, Heward, A, Patterson, B, Scott, G: Ability of the Medical Priority Dispatch System protocol to predict acuity of “unknown problem” dispatch response levels. Prehosp Emerg Care 2008;12(3):290296.
16.Clawson, J, Olola, C, Heward, A, Patterson, B, Scott, G: The Profile of Emergency Medical Dispatch Calls for breathing problems within the Medical Priority Dispatch System Protocol. Prehosp Disaster Med 2008;23(5):416423.

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Association between Patient Unconscious or Not Alert Conditions and Cardiac Arrest or High-Acuity Outcomes within the Medical Priority Dispatch System “Falls” Protocol

  • Jeff Clawson (a1), Christopher Olola (a1) (a2), Greg Scott (a1), Bryon Schultz (a3), Richard Pertgen (a4), Don Robinson (a5), Barry Bagwell (a5) and Brett Patterson (a1)...

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