Predicting Use of Lights and Siren for Patient Illnesses

Abstract

Lights and siren are frequently used by Emergency Medical Service (EMS) groups to reduce response times and increase a patient’s chance for survival. However, the use of lights and siren in EMS patient transport has been associated with occasional inappropriate use, higher crash rates involving the ambulance, and a potential “wake effect” increasing crash rates in ambient traffic. This study examines types of patient illnesses and their involvement with either emergency (lights and siren engaged) or non-emergency transport. Patient care records were analyzed from a five-year period from a private medical transportation company. A binary logistic regression model was built to predict the transportation mode (lights and siren or non-emergency-mode) most likely to accompany each unique primary patient illness. Patient illnesses were identified that showed a higher probability of transport using lights and siren. Fifteen illness descriptions were identified from the records as being more likely to result in emergency mode travel, including airway obstruction, altered level of consciousness, breathing problems, cardiac arrest, cardiac symptoms, chest pain, congestive heart failure/pulmonary embolism, heart/cardiac, obstetrics, respiratory arrest, respiratory distress, stroke/cerebrovascular accident, trauma, unconscious, and patients where data was not entered. The patient illnesses associated with lights and siren were not limited to cardiac conditions and symptoms, which suggest that response-time goals based solely on cardiac arrest patients may need to be expanded to include other illnesses such as respiratory conditions. Expanded studies could assess whether or not lights and sirens result in a clinically significant time savings across the spectrum of illnesses that are currently being transported using lights and siren. The list of illnesses identified here as more commonly utilizing lights and siren could be useful to untrained EMS or dispatch workers to assist in minimizing unnecessary emergency mode travel, thereby increasing safety for EMS workers, patients, and the general public.

Share and Cite:

J. Mueller and L. Stanley, "Predicting Use of Lights and Siren for Patient Illnesses," Open Journal of Safety Science and Technology, Vol. 3 No. 3, 2013, pp. 63-68. doi: 10.4236/ojsst.2013.33008.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] National Association of Emergency Medical Services Physicians [NAEMSP], “Use of Warning Lights and Siren in Emergency Medical Vehicle Response and Patient Transport,” Prehospital and Disaster Medicine, Vol. 9, No. 2, 1994, pp. 133-135.
[2] J. Clawson, R. Martin, G. Cady and R. Maio, “The Wake Effect: Emergency Vehicle-Related Collisions,” Prehospital and Disaster Medicine, Vol. 12, No. 4, 1997, pp. 274- 277.
[3] Pre-Hospital Trauma Life Support Committee of the National Association of Emergency Technicians in Cooperation with the Committee on Trauma of the American College of Surgery, “PHTLSC—Basic and Advanced Pre-Hospital Trauma Life Support,” 3rd Edition, Mosby, New York, 1998.
[4] J. P. Pell, J. M. Sirel, A. K. Marsden, I. Ford and S. M. Cobbe, “Effect of Reducing Ambulance Response Times on Deaths from out of Hospital Cardiac Arrest: Cohort Study,” British Medical Journal, Vol. 322, No. 7299, 2001, pp. 1385-1322. doi:10.1136/bmj.322.7299.1385
[5] P. T. Pons and V. J. Markovchick, “Eight Minutes or Less: Does the Ambulance Response Time Guideline Impact Trauma Patient Outcome?” The Journal of Emergency Medicine, Vol. 23, No. 1, 2002, pp. 43-48. doi:10.1016/S0736-4679(02)00460-2
[6] M. E. Lacher and J. C. Bausher, “Lights and Sirens in Pediatric 911 Ambulance Transports: Are They Being Misused?” Annals of Emergency Medicine, Vol. 29, No. 2, 1996, pp. 223-227. doi:10.1016/S0196-0644(97)70272-5
[7] T. L. Sanddal, N. D. Sanddal, N. Ward and L. Stanley, “Ambulance Crash Characteristics in the US Defined by the Popular Press: Aretrospective Analysis,” Emergency Medicine International, Vol. 2010, No. 2010, 2010, pp. 1-7. doi:10.1155/2010/525979
[8] L. R. Becker, E. Zaloshnja, N. Levick, G. Li and T. R. Miller, “Relative Risk of Injury and Death in Ambulances and Other Emergency Vehicles,” Accident Analysis & Prevention, Vol. 35, No. 6, 2003, pp. 941-948. doi:10.1016/S0001-4575(02)00102-1
[9] C. Kahn, R. Pirrallo and E. Kuhn, “Characteristics of Fatal Ambulance Crashes in the United States: An 11-Year Retrospective Analysis,” Prehospital Emergency Care, Vol. 5, No. 3, 2001, pp. 261-269. doi:10.1080/10903120190939751
[10] A. Agresti, “An Introduction to Categorical Data Analysis,” 2nd Edition, John Wiley and Sons, Inc., Hoboken, 2007. doi:10.1002/0470114754
[11] K. W. Neely, J. A. Eldurkar and M. E. R. Drake, “Do Emergency Medical Services Dispatch Nature and Severity Codes Agree with Paramedic Field Findings?” Academic Emergency Medicine, Vol. 7, No. 2, 1999, pp. 174-180. doi:10.1111/j.1553-2712.2000.tb00523.x
[12] R. F. Maio, H. G. Garrison, D. W. Spaite, J. S. Desmond, M. A. Gregor, C. G. Cayten and I. G. Stiell, “Emergency Medical Services Outcomes Project I (EMSOP I): Prioritizing Conditions for Outcomes Research,” Annals of Emergency Medicine, Vol. 33, No. 4, 1999, pp. 423-432. doi:10.1016/S0196-0644(99)70307-0
[13] R. Hunt, L. Brown, E. Cabinum, T. Whitley, N. Prasad, C. Owens and C. Mayo, “Is Ambulance Transport Time with Lights and Sirens Faster than That Without?” Annals of Emergency Medicine, Vol. 24, No. 4, 1994, pp. 507-511.
[14] A. Marques-Baptista, P. Ohman-Strickland, K. Baldino, M. Prasto and M. Merlin, “Utilization of Warning Lights and Siren Based on Hospital Time-Critical Interventions,” Prehospital and Disaster Medicine, Vol. 25, No. 4, 2010, pp. 335-339.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.