Determining the sensitivity of emergency dispatcher and paramedic diagnosis of stroke: statewide registry linkage study

Amminadab L Eliakundu; Dominique A Cadilhac; Joosup Kim; Monique F Kilkenny; Kathleen L Bagot; Emily Andrew; Shelley Cox; Christopher F Bladin; Michael Stephenson; Lauren Pesavento; Lauren Sanders; Ben Clissold; Henry Ma; Karen Smith

doi:10.1002/emp2.12750

Determining the sensitivity of emergency dispatcher and paramedic diagnosis of stroke: statewide registry linkage study

J Am Coll Emerg Physicians Open. 2022 Jul 1;3(4):e12750. doi: 10.1002/emp2.12750. eCollection 2022 Aug.

Authors

Amminadab L Eliakundu¹, Dominique A Cadilhac^{1

2}, Joosup Kim^{1

2}, Monique F Kilkenny^{1

2}, Kathleen L Bagot^{1

2}, Emily Andrew^{3

4}, Shelley Cox^{3

4}, Christopher F Bladin^{2

3}, Michael Stephenson^{3

4

5}, Lauren Pesavento⁶, Lauren Sanders⁷, Ben Clissold⁸, Henry Ma^{1

9}, Karen Smith^{3

4

5}

Affiliations

¹ Stroke and Ageing Research Department of Medicine School of Clinical Sciences at Monash Health Monash University Victoria Australia.
² Stroke Division Florey Institute of Neurosciences & Mental Health University of Melbourne Victoria Australia.
³ Ambulance Victoria Victoria Australia.
⁴ Department of Epidemiology and Preventive Medicine Monash University Victoria Australia.
⁵ Department of Paramedicine Monash University Victoria Australia.
⁶ The Melbourne Brain Centre and Department of Neurology The Royal Melbourne Hospital Victoria Australia.
⁷ Department of Neurology St Vincent's Hospital Fitzroy Victoria Australia.
⁸ Department of Neurology Geelong Hospital Geelong Victoria Australia.
⁹ Department of Neurology Monash Medical Centre, Monash University Clayton Victoria Australia.

Abstract

Introduction: Correctly identifying people with suspected stroke is essential for ensuring rapid treatment. Our aims were to determine the sensitivity of emergency dispatcher and paramedic identification of patients with stroke, the factors associated with correct identification, and whether there were any implications for hospital arrival times.

Methods: Observational study using patient-level data from the Australian Stroke Clinical Registry (2015-2017) linked with ambulance and emergency department records for the state of Victoria. The registry diagnosis was the reference standard to compare with the provisional diagnoses made by emergency services personnel classified as "suspected" and "not suspected" stroke/transient ischemic attack (TIA). Multivariable logistic and quintile regressions were used to determine factors associated with correct identification and timely arrival to hospital.

Results: Overall, 4717 (64%) were matched to ambulance transport records (median age: 73 years, 43% female). Stroke/TIA was suspected in 56% of registrants by call-takers and 69% by paramedics. Older patients (75+ years) (adjusted odds ratio [aOR]: 0.61; 95% confidence interval [CI]: 0.49-0.75), females (aOR: 0.86; 95% CI: 0.75-0.99), those with severe stroke or intracerebral hemorrhage were less often suspected as stroke. Cases identified as stroke had a shorter arrival time to hospital (unadjusted median minutes: stroke, 54 [43, 72] vs not stroke, 66 [51, 89]).

Conclusions: Emergency dispatchers and paramedics identified over half of patients with stroke in the prehospital setting. Important patient characteristics, such as being female and those having a severe stroke, were found that may enable refinement of prehospital ambulance protocols and dispatcher/paramedic education. Those correctly identified as stroke, arrived earlier to hospital optimizing their chances of receiving time-critical treatments.

Keywords: ambulances; big data; emergency medical services; paramedics; prehospital; registries; sensitivity; stroke.