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Pre-hospital stroke recognition in a UK centralised stroke system: a qualitative evaluation of current practice
Lisa Brunton1, Ruth Boaden1, Sarah Knowles1
1The University of Manchester.
Insights
Pre-hospital clinicians often struggle to accurately diagnose stroke, leading to delays and misdiagnoses. Improving stroke recognition through better tools, feedback, and education is crucial for patient care.
Area of Science:
- Emergency Medicine
- Health Services Research
- Qualitative Research
Background:
- Many ambulance patients with suspected stroke are misdiagnosed, impacting timely treatment for non-stroke conditions and burdening stroke teams.
- The Greater Manchester Connected Health Cities stroke project aims to improve pre-hospital stroke recognition by analyzing ambulance and hospital data.
- This study focuses on understanding pre-hospital clinicians' perspectives on stroke recognition challenges.
Purpose of the Study:
- To explore pre-hospital clinicians' experiences and challenges in recognizing stroke.
- To gather qualitative data to inform the development of service improvement innovations for stroke recognition.
- To understand barriers and facilitators to accurate pre-hospital stroke diagnosis.
Main Methods:
- Qualitative study involving focus groups and semi-structured interviews with pre-hospital clinicians.
- Thematic analysis guided by Normalisation Process Theory (NPT) was used for data interpretation.
- Participants included clinicians of various grades from the North West Ambulance Service NHS Trust (NWAS) in Greater Manchester.
Main Results:
- Clinicians were unaware of false positive stroke rates on the stroke pathway.
- Limited job feedback hinders learning and skill development for pre-hospital clinicians.
- Difficulty in ruling out stroke, recognizing differential diagnoses, and a lack of confidence were reported, with greater concern for missed strokes.
Conclusions:
- Qualitative findings support the need for innovations to enhance pre-hospital stroke recognition.
- Potential improvements include an enhanced FAST tool, better communication with Hyper Acute Stroke Unit (HASU) clinicians, and targeted education on stroke pathways and differential diagnoses.
Background:
A significant number of patients conveyed via ambulance to hyper acute stroke units (HASU) with suspected stroke have other diagnoses. This may delay treatment for non-stroke patients and cause burden to stroke teams. The Greater Manchester (GM) Connected Health Cities (CHC) stroke project links historical North West Ambulance Service NHS Trust (NWAS) data with Salford Royal Hospital electronic data to study stroke pathway compliance and accuracy of paramedic diagnosis and aims to use these data to improve pre-hospital clinicians' accurate recognition of stroke through development of service improvement innovations. We report on supplementary qualitative work required to understand stroke recognition from the pre-hospital clinician's perspective.
Methods:
Focus groups and semi-structured interviews were conducted with pre-hospital clinicians of various grades, working in the GM area of NWAS. Focus groups and interviews were audio recorded and transcribed verbatim. We used thematic analysis informed by normalisation process theory (NPT) to analyse the data. This theory helps us to understand how innovations are developed, implemented and sustained into healthcare practice.
Results:
Sixteen pre-hospital clinicians took part in two focus groups, one dyad interview and five one-to-one interviews. Analysis identified that respondents were unaware of false positive stroke rates entering onto the stroke pathway. Pre-hospital clinicians receive limited feedback from jobs and this impedes their ability to learn from their experiences. Respondents reported difficulty in ruling out stroke in certain patient cohorts and difficulty in recognising differential diagnoses. They expressed a lack of confidence to rule out stroke in the pre-hospital setting. They also expressed greater concern for 'missed strokes'.
Conclusion:
The qualitative findings support the development of innovations to improve accurate recognition of stroke in the pre-hospital setting.An enhanced FAST tool, better relations with HASU clinicians, feedback and education on the stroke pathway and differential diagnoses were all considered useful to improve accurate stroke recognition.
