NHS Long Term Plan Webinar Series
The ticking time bomb of undiagnosed atrial fibrillation
Accelerating detection through the NHS recovery
10 March 2021
13:00 - 14:00 GMT
This event has been sponsored by Daiichi Sankyo UK. All content to be delivered during the course of this webinar has been reviewed to ensure adherence to the requirements within the ABPI Code of Practice.
The NHS Long Term Plan, prioritised the prevention of 150,000 CVD events by 2028, along with a number of ambitions to reduce preventable outpatient and hospital admissions. Whilst there has been progress in improving the detection and diagnosis of Atrial Fibrillation, a common abnormal heart arrhythmia, in recent years, the impact of the COVID19 pandemic risks negatively impacting these efforts.
At least 1/3 ischemic strokes occur as a result of atrial fibrillation (AF) (Ref 1). Early detection of AF and appropriate management can reduce the risk of stroke by 2/3rds (Ref 2). At least 40% of AF is asymptomatic, so case-finding in those at greatest risk of stroke has been shown to be cost-effective, readily acceptable and scalable (Ref 3). People living with AF face a range of challenges both in understanding and accessing effective care. Even when the care provided is optimal, low levels of adherence can increase the risk of complications. This webinar will complement and enhance the previous Govconnect webinars by helping health professionals, practitioners and policy-makers to understand and address patient engagement. It will be particularly relevant for those involved in the delivery of healthcare, policy development, and those with an interest in AF-related stroke prevention.
This webinar will focus on contemporary tools to detect and diagnose AF, both during and beyond the COVID19 pandemic, and provide a platform to learn from examples of best practice in this area.
After watching this webinar, participants will be able to:
Understand the current evidence for AF case-finding;
Know what technology is available to enhance detection and diagnosis; and
Be able to identify AF on an ECG.
(Job Code: CVD/21/0039)