Skip to main content Accessibility help
×
Home

Population-based analysis of the effect of a comprehensive, systematic change in an emergency medical services resource allocation plan on 24-hour mortality

  • John M. Tallon (a1) (a2), Lu Zheng (a1), Julie Wei (a1), William Dick (a2), George Papadopoulos (a1) and Ognjenka Djurdjev (a3)...

Abstract

Background

Resource allocation planning for emergency medical services (EMS) systems determines appropriate resources including what paramedic qualification and how rapidly to respond to patients for optimal outcomes. The British Columbia Emergency Health Services implemented a revised response plan in 2013.

Methods

A pre- and post-methodology was used to evaluate the effect of the resource allocation plan revision on 24-hour mortality. All adult cases with evaluable outcome data (obtained through linked provincial health administrative data) were analyzed. Multivariable logistic regression was used to adjust for variations in other significant associated factors. Interrupted time series analysis was used to estimate immediate changes in level or trend of outcome after the start of the revised resource allocation plan implementation, while simultaneously controlling for pre-existing trends.

Results

The derived cohort comprised 562,546 cases (April 2012–March 2015). When adjusted for age, sex, urban/metro region, season, day, hour, and dispatch determinant, the probability of dying within 24 hours of an EMS call was 7% lower in the post-resource allocation plan-revision cohort (OR = 0.936; 95% CI: 0.886–0.989; p = 0.018). A subgroup analysis of immediately life-threatening cases demonstrated similar effect (OR = 0.890; 95% CI: 0.808–0.981; p = 0.019). Using time series analysis, the descending changes in overall 24-hour mortality trend and the 24-hour mortality trend in immediately life-threatening cases, were both statistically significant (p < 0.001).

Conclusion

Comprehensive, evidence-informed reconstruction of a provincial EMS resource allocation plan is feasible. Despite change in crew level response and resource allocation, there was significant decrease in 24-hour mortality in this pan-provincial population-based cohort.

Contexte

La planification de l'allocation des ressources aux services médicaux d'urgence (SMU) détermine une attribution appropriée des ressources, notamment en ce qui concerne la qualification du personnel paramédical et le temps de réponse en vue de l'obtention de résultats optimaux. Les British Columbia Emergency Health Services ont donc procédé, en 2013, à la mise en œuvre d'un plan d'intervention révisé.

Méthode

Il s'agit d'une étude de type avant-après, visant à évaluer l'effet de la révision du plan d'allocation des ressources sur la mortalité au bout de 24 heures. Ont été analysés tous les dossiers médicaux d'adultes contenant des données sur des résultats évaluables (obtenus à l'aide de données administratives provinciales liées sur la santé). L'analyse de régression logistique plurifactorielle a permis de tenir compte d’écarts observés dans d'autres facteurs associés importants. Par ailleurs, l’étude de séries temporelles interrompues a permis à la fois d'estimer les changements immédiats de degré ou de tendance concernant les résultats après l'instauration du plan d'allocation des ressources révisé, et de tenir compte des tendances préexistantes.

Résultats

La cohorte à l’étude comptait 562 546 cas (avril 2012 – mars 2015). Après rajustement des données selon l’âge, le sexe, le type de région (urbaine ou métropolitaine), les saisons, le jour, l'heure et les déterminants de la répartition, le risque de mourir dans les 24 heures suivant un appel aux SMU était 7% moins élevé dans la cohorte formée après la mise en œuvre du plan d'allocation des ressources révisé (risque relatif approché [RRA] = 0,936; IC à 95% : 0,886–0,989; p = 0,018) que dans celle formée avant. De plus, un effet comparable (RRA = 0,890; IC à 95% : 0,808–0,981; p = 0,019) a été démontré dans une analyse par sous-groupe des cas de danger de mort immédiate. D'après l'analyse des séries temporelles, la tendance à la diminution de la mortalité générale au bout de 24 heures et cette même tendance de la mortalité au bout de 24 heures dans les cas de mort immédiate étaient toutes deux statistiquement significatives (p < 0,001).

Conclusion

Il est possible de procéder à une révision globale, fondée sur des données probantes, du plan provincial d'allocation des ressources aux SMU. Malgré les changements apportés au temps de réponse des équipes d'urgence et à l'allocation des ressources, une diminution significative de la mortalité au bout de 24 heures a été enregistrée dans cette étude de cohortes panprovinciale, fondée sur la population.

Copyright

Corresponding author

Correspondence to: Dr. John M. Tallon, Vice-President, Chief Medical Officer, BC Emergency Health Services, 150-2955 Virtual Way, Vancouver, BC V5M 4X6; Email: john.tallon@bcehs.ca

References

Hide All
1.Bandara, D, Mayorga, ME, McLay, LA. Optimal dispatching strategies for emergency vehicles to increase patient survivability. Int J Operational Res 2012;15(2):195214.
2.Ball, SJ, Williams, TA, Smith, K, et al. Association between ambulance dispatch priority and patient condition. Emerg Med Australas 2016;28(6):716–24.
3.Hinchey, P, Myers, B, Zalkin, J, Lewis, R, Garner, D Jr. Low acuity EMS dispatch criteria can reliably identify patients without high-acuity illness or injury. Prehosp Emerg Care 2007;11(1):42–8.
4.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):186–9.
5.Hettinger, AZ, Cushman, JT, Shah, MN, Noyes, K. Emergency medical dispatch codes association with emergency department outcomes. Prehosp Emerg Care 2013;17(1):2937.
6.British Columbia Emergency Health Services. Available at: http://www.bcehs.ca/ (accessed September 9, 2018).
7.Craig, AM, Verbeek, PR, Schwartz, B. Evidence-based optimization of urban firefighter first response to emergency medical services 9-1-1 incidents. Prehosp Emerg Care 2010;14(1):109–17.
8.Craig, A. External review of the British Columbia emergency health services resource allocation plan. Vancouver (BC): British Columbia Emergency Health Services; 2014. Available at: http://www.bcehs.ca/about-site/Documents/201404-external-review-of-bcehs-rap%20(1).pdf (accessed September 9, 2018).
9.Clawson, JJ. Emergency medical dispatch and prioritizing response. In: Bass, RR, Brice, JH, Delbridge, TR, Gunderson, MR, editors. Medical oversight of EMS. Dubuque (IA): Kendall-Hunt Publishing; 2009. pp. 554–89.
10.Priority Dispatch. Available at: https://prioritydispatch.net/about/ (accessed September 9, 2018).
11.Clawson, JJ, Dernccoeur, KB. Principles of emergency medical dispatch. 4th ed. Upper Saddle River (NJ): Prentice Hall; 2009.
12.Cone, DC, Galante, N, MacMillan, DS. Can emergency medical dispatch systems safely reduce first-responder call volume? Prehosp Emerg Care 2008;12(4):479–85.
13.Michael, GE, Sporer, KA. Validation of low-acuity emergency medical services dispatch codes. Prehosp Emerg Care 2005;9(4):429–33.
14.Newbold, KB, Eyles, J, Birch, S, Spencer, A. Allocating resources in health care: alternative approaches to measuring needs in resource allocation formula in Ontario. Health Place 1998;4(1):7989.
15.Strauch, U, Bergmans, DC, Winkens, B, Roekaerts, PM. Short-term outcomes and mortality after interhospital intensive care transportation: an observational prospective cohort study of 368 consecutive transports with a mobile intensive care unit. BMJ Open 2015;5(4):e006801.
16.Canadian Institute for Health Information. Data quality documentation, National Ambulatory Care Reporting System – current-year information, 2012–2013. Ottawa, ON: Canadian Institute for Health Information; 2013. Available at: https://www.cihi.ca/sites/default/files/document/nacrs_dataquality_2012_2013_en.pdf (accessed September 9, 2018).
17.Canadian Institute for Health Information. Data quality documentation, National Ambulatory Care Reporting System – current-year information, 2014–2015. Ottawa, ON: Canadian Institute for Health Information; 2015. Available at: https://www.cihi.ca/sites/default/files/nacrs-dataquality_2014-2015_en_0.pdf (accessed September 9, 2018).
18.Sayers, A, Ben-Shlomo, Y, Blom, AW, Steele, F. Probabilistic record linkage. Int J Epidemiol 2016;45(3):954–64.
19.Newgard, CD. Validation of probabilistic linkage to match de-identified ambulance records to a state trauma registry. Acad Emerg Med 2006;13(1):6975.
20.Taljaard, M, McKenzie, JE, Ramsay, CR, Grimshaw, JM. The use of segmented regression in analysing interrupted time series studies: an example in pre-hospital ambulance care. Implement Sci 2014;9(1):7781.
21.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):192–8.
22.Blanchard, IE, Doig, CJ, Hagel, BE, et al. Emergency Medical Services response time and mortality in an urban setting. Prehosp Emerg Care 2012;16(1):142–51.
23.Sporer, KA, Johnson, NJ, Yeh, CC, Youngblood, GM. Can emergency medical dispatch codes predict prehospital interventions for common 9-1-1 call types? Prehosp Emerg Care 2008;12(4):470–8.

Keywords

Type Description Title
WORD
Supplementary materials

Tallon et al. supplementary material
Tallon et al. supplementary material

 Word (274 KB)
274 KB

Population-based analysis of the effect of a comprehensive, systematic change in an emergency medical services resource allocation plan on 24-hour mortality

  • John M. Tallon (a1) (a2), Lu Zheng (a1), Julie Wei (a1), William Dick (a2), George Papadopoulos (a1) and Ognjenka Djurdjev (a3)...

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed