A Learning Health System for Stroke:; Pre-Hospital Pathway Aid (PHPA) app

The Pre-Hospital Pathway Aid (PHPA) app resulted in ambulance staff being able to take decisions within seconds on the most appropriate and the nearest specialist care team for patients with suspected stroke.  


Across Greater Manchester three specialist centres, known as Hyper Acute Stroke Units (HASUs), provide expert and urgent care for people who have a stroke or are suspected of having a stroke. The Greater Manchester Stroke Operational Delivery Network (GMSODN) found in 2015 that around half of suspected stroke patients taken to the HASUs turned out not to have strokes. Patients who present stroke-like symptoms could be experiencing seizures, sepsis, or migraines that can be confused with a stroke and these are sometimes called ‘stroke mimics’. The mimics workstream was developed to reduce the number of stroke mimics being transferred to HASUs, allowing HASU clinicians to focus on delivering specialist stroke care whilst also ensuring that patients with other conditions can receive care more quickly at the nearest Emergency Department. Working with the GMSODN, the Collaboration for Leadership in Applied Health Research and Care Greater Manchester (CLAHRC GM), D2Digital and the North West Ambulance Service (NWAS), the GM CHC stroke team extracted data from a large, linked dataset of pre-hospital and hospital data for patients on the acute stroke pathway and identified how many false positive (mimics) and false negatives (missed strokes) were occurring within Greater Manchester. The Pre- Hospital Pathway Aid (PHPA) app was then developed to aid stroke recognition. The app follows the standard Face Arm Speech (FAST) assessment and the exclusion conditions as a flowchart in a user-friendly digital format. The ambulance staff, who work across organisations with different stroke pathway protocols and procedures, are now supported in real time to identify the most appropriate and nearest location for treatment. During the pilot, around 43% of interactions with the PHPA app resulted in correct identification of a negative FAST test (mimics) within seconds followed by appropriate transfer to the emergency department and avoiding the HASU. The PHPA app is now being used across the NWAS service in Greater Manchester with additional use cases identified for the linked dataset developed as part of this project.

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