Pre-hospital stroke diagnosis in a UK centralised stroke system: mixed methods evaluation of current practice

L Brunton, Kyriaki Paroutoglou, C Ashton, S Bennett, C Sammut-Powell, K Woodward-Nutt, R Boaden, S Knowles, N Peek, A Parry-Jones

Research output: Contribution to journalArticlepeer-review


Introduction: Many patients diverted to hyper acute stroke units (HASUs) with suspected stroke have other diagnoses. This may delay treatment for non-stroke patients and overburden stroke teams. We sought to describe real world pre-hospital stroke recognition in a UK centralised stroke system.

Methods: We extracted all patients presenting to Salford HASU on the stroke pathway from 01/08/2015 to 28/02/2017. Case notes were manually reviewed by a Consultant Stroke Physician where discharge diagnosis was not coded. To identify false negative cases, all patients with a discharge diagnosis of stroke were extracted. Linked ambulance data were manually extracted from scanned records. Additional qualitative work was undertaken.

Results: 5,809 patients were conveyed via ambulance, to the HASU on the stroke pathway during the study period; currently, 5,125 cases have been analysed. 2003 (39%) were false-positives. Of these, the 5 most common diagnoses were sepsis (n = 360 [7%]), migraine (n = 282 [6%]), epilepsy (n = 277 [5%]), limb/face pathology (n = 124 [2%]), syncope (n = 110 [2%]). To date, 84 stroke patients were identified as false-negatives, but further analysis of ambulance records is required. Analysis of focus group and interview data with 16 pre-hospital clinicians identifies respondents receive limited feedback from jobs which impedes their ability to learn from experiences. Respondents report difficulty in recognising differential diagnoses, expressing lack of confidence to rule out stroke and greater concern for ‘missed strokes’. An enhanced FAST tool, better relations with hospital clinicians, and education on differential diagnoses were all considered necessary to improve accurate stroke detection.

Conclusion: Findings support the development of pre-hospital interventions to improve stroke recognition.
Original languageEnglish
Pages (from-to)11-11
Number of pages1
JournalInternational Journal of Stroke
Publication statusPublished - 3 Dec 2018


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