Smartphone Apps Launched for Atrial Fibrillation Patients and their Healthcare Providers

Novel smartphone and tablet applications (apps) for atrial fibrillation patients and healthcare professionals have been launched by heart experts. The objectives and design of the apps are outlined in a paper published online today in EP Europace,(1) with a summary published in the European Heart Journal.(2)

Atrial fibrillation is the most common heart rhythm disorder and significantly increases the risk of stroke and death. One in four middle-aged adults in Europe and the US will develop atrial fibrillation, and the incidence and prevalence are rising.

"Around two-thirds of people in Europe and the US have a mobile device and use it as their main way of accessing online information," said lead author Dr Dipak Kotecha, a clinician scientist in cardiovascular medicine at the Institute of Cardiovascular Sciences, University of Birmingham, UK. "This presents a big opportunity to improve self management and shared decision making in atrial fibrillation."

The My AF app and AF Manager app were designed by the European Society of Cardiology (ESC) Guidelines Task Force on Atrial Fibrillation and the CATCH ME consortium of which the ESC is a partner. The apps were developed over the last two years in tandem with the writing of the 2016 ESC Guidelines on atrial fibrillation.(3)

Both apps are freely available for Android and iOS devices through the Google Play, and Apple stores.

My AF is for patients with atrial fibrillation. It provides information about the condition, the risk of stroke, atrial fibrillation treatments, and tips on improving lifestyle. Patients can record symptoms and quality of life in a diary which can be shared with a nominated health professional before each consultation to maximise face-to-face time.

Developed in collaboration with patients and patient support groups, My AF provides high quality information in a simple format which is suitable for adults of all ages. Work is underway to translate the app into several languages.

Dr Kotecha said: "The app aims to encourage active patient involvement in the management of their condition. There is evidence that patient education can improve self-care, adherence to therapy, and long-term outcomes."

AF Manager is for doctors, nurses and other healthcare professionals. It is the first app of its kind to be submitted for CE certification and is in the final stages of approval. AF Manager imports information shared by the patient and allows the healthcare professional to amend details and enter other medical information, such as electrocardiogram or echocardiography data. The Treatment Manager tool within the app then suggests individualised treatment options based on ESC guidelines.(4) After a consultation, the notes, treatment decisions, and medication dosages can be entered and then shared with the patient.

"Many studies have shown that when clinicians follow guideline recommendations, patients have better outcomes," said Dr Kotecha. "All of the decision aids in AF Manager are based on ESC guidelines so we hope this will encourage guideline implementation. Patients will have the option to anonymously donate their data which will enable us to assess the guideline adherence rate."

The apps are linked to allow transfer of data between patients and healthcare professionals via a secure server at the University of Birmingham, UK. Patients control who can view and edit their data. When data sharing is enabled, updates are synced on both apps. All shared information is encrypted and password protected.

Dr Kotecha said: "We know that effective management of atrial fibrillation is suited to shared decision making and we have created the apps in the hope of facilitating this process. Sharing information should save clinicians time and enable them to devote consultations to choosing the best treatments."

He concluded: "The dynamic nature of this technology will allow us to modify and update the features and content to reflect feedback from users, as well as future versions of the ESC atrial fibrillation guidelines."

About the CATCH ME consortium
The CATCH ME (Characterising Atrial fibrillation by Translating its Causes into Health Modifiers in the Elderly) Consortium is a European collaboration which aims to improve the prevention and treatment of atrial fibrillation and its complications. CATCH ME is funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 633196.

About the European Society of Cardiology
The ESC brings together health care professionals from more than 140 countries, working to advance cardiovascular medicine and help people to live longer, healthier lives.

1. Kotecha D, et al. European Society of Cardiology (ESC) smartphone and tablet applications for patients with atrial fibrillation and their healthcare providers. EP Europace. 2017. DOI: 10.1093/europace/eux299
2. Kotecha D, Kirchhof P. ESC Apps for Atrial Fibrillation. Eur Heart J. 2017;38:2643–2645.
3. 2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS. Eur Heart J. 2016;37(38):2893–2962. doi: 10.1093/eurheartj/ehw210
4. The full capabilities of the Treatment Manager tool will be available once the app is CE certified.

Most Popular Now

Unlocking the 10 Year Health Plan

The government's plan for the NHS is a huge document. Jane Stephenson, chief executive of SPARK TSL, argues the key to unlocking its digital ambitions is to consider what it...

Alcidion Grows Top Talent in the UK, wit…

Alcidion has today announced the addition of three new appointments to their UK-based team, with one internal promotion and two external recruits. Dr Paul Deffley has been announced as the...

AI can Find Cancer Pathologists Miss

Men assessed as healthy after a pathologist analyses their tissue sample may still have an early form of prostate cancer. Using AI, researchers at Uppsala University have been able to...

New Training Year Starts at Siemens Heal…

In September, 197 school graduates will start their vocational training or dual studies in Germany at Siemens Healthineers. 117 apprentices and 80 dual students will begin their careers at Siemens...

AI, Full Automation could Expand Artific…

Automated insulin delivery (AID) systems such as the UVA Health-developed artificial pancreas could help more type 1 diabetes patients if the devices become fully automated, according to a new review...

How AI could Speed the Development of RN…

Using artificial intelligence (AI), MIT researchers have come up with a new way to design nanoparticles that can more efficiently deliver RNA vaccines and other types of RNA therapies. After training...

MIT Researchers Use Generative AI to Des…

With help from artificial intelligence, MIT researchers have designed novel antibiotics that can combat two hard-to-treat infections: drug-resistant Neisseria gonorrhoeae and multi-drug-resistant Staphylococcus aureus (MRSA). Using generative AI algorithms, the research...

AI Hybrid Strategy Improves Mammogram In…

A hybrid reading strategy for screening mammography, developed by Dutch researchers and deployed retrospectively to more than 40,000 exams, reduced radiologist workload by 38% without changing recall or cancer detection...

Are You Eligible for a Clinical Trial? C…

A new study in the academic journal Machine Learning: Health discovers that ChatGPT can accelerate patient screening for clinical trials, showing promise in reducing delays and improving trial success rates. Researchers...

Penn Developed AI Tools and Datasets Hel…

Doctors treating kidney disease have long depended on trial-and-error to find the best therapies for individual patients. Now, new artificial intelligence (AI) tools developed by researchers in the Perelman School...

Global Study Reveals How Patients View M…

How physicians feel about artificial intelligence (AI) in medicine has been studied many times. But what do patients think? A team led by researchers at the Technical University of Munich...

New AI Tool Addresses Accuracy and Fairn…

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms...