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Identifying barriers and facilitators to improving prehospital care of asthma: views of ambulance clinicians

By Deborah Shaw, Stacey Knowles and A. Niroshan Siriwardena


Background: In 2008/09 there were nearly 80,000 emergency hospital admissions for asthma. Current UK guidelines emphasise the importance of evidence-based prehospital assessment and treatment of asthma for improving patient outcomes and reducing hospitalisation, morbidity and mortality. National benchmarking of ambulance clinical performance indicators for asthma has revealed important unexplained variations in care across ambulance services. Little research has been undertaken to understand the reasons for poor levels of care. Objective: The aim of this study was to gather data on ambulance clinicians’ perceptions and beliefs around prevailing and best practice for management of asthma. This was used to identify the factors which prevent or enable better asthma care in ambulance services. Methods: We used a phenomenological qualitative approach, which addresses how individuals use their experiences to make sense of their world, focusing on participants’ lived experiences of care delivery for asthma. We used focus groups of ambulance clinicians to gather data on barriers and facilitators to better asthma care. Recordings and notes were taken, transcribed and then analysed using QSR NVivo 8. A coding framework was developed based on a priori concepts but with emergent themes added during the analysis. Results: Two focus groups were conducted with eight and five participants respectively. A number of preliminary themes and subthemes were identified. The study identified issues relating to clarity of ambulance guidelines, conflicts between training and guidance, misconceptions about the importance of objective assessment and over reliance on non-objective assessment. Some practitioners believed that hospital staff were not interested in prehospital peak flow assessments. Conclusion: Our findings will inform improved systems of care for asthma and the effect on indicators will be measured using time series methods. This approach could be used more widely to improve management of specific clinical conditions where quality of care is demonstrated to be suboptimal

Topics: B990 Subjects Allied to Medicine not elsewhere classified, A300 Clinical Medicine
Year: 2010
OAI identifier:

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