About the study

Global National Institute for Health Research(NIHR) AF is an international research, ongoing in the University of Jaffna, Sri Lanka, in collaboration with the University of Birmingham, Brazil and China.

AF is commonest sustained cardiac rhythm disorder globally, conferring a major burden of morbidity and mortality from stroke, heart failure, and dementia. However, there is a lack of baseline data and awareness of AF in developing countries such as Sri Lanka.

To the comprehensive and effective management, a simple 3-step approach (the ‘ABC pathway’) is proposed to streamline primary and secondary care AF management, i.e. Avoid stroke (Anticoagulation), Better symptom management (with rate or rhythm control), and Cardiovascular/ comorbidity risk management.

We have identified four key areas that need to be tackled to improve health systems to manage AF.  

Those are:

  • A targeted screening program
  • Better diagnosis and risk stratification
  • Early referral to hospital clinics
  • Improved data sharing and communication between the community and hospital care

AF project management at the University of Jaffna​

In Sri Lanka, NIHR AF study is leading by Dr R Surenthirakumaran, Senior Lecturer at Department of Community and Family Medicine of the University of Jaffna. The University of Jaffna entered into a Memorandum of Understanding (MOU) with the University of Birmingham, UK. The MOU was approved by the Cabinet of Ministers, Sri Lanka. The project has implemented through the University of Jaffna under the Ministry of Higher Education.

Themes and Aims
In order to achieve the project goal, three themes have been proposed.

Theme I

Aim: To assess the prevalence and associated risk factors of Atrial Fibrillation and case-finding strategies for AF.
Lead: Dr.S.Kumaran MBBS, DFM, MD 

A community-based survey among 10,000 above 50 years old in Northern Province, Sri Lanka was proposed. The community-survey is implemented through a mobile data collection process called “REDCap” to get the general health data, related health care cost and risk status for AF.  A mobile-based single lead ECG called “Alivecor – Kardia is taken from all participants laboratory investigations for basic and novel biomarkers to evaluate the risk and prognosis will be done. Bio samples will be stored using cryo banking and from these baseline data sub cohorts and nested case control studies will take place.  

Theme II

Aim: To find out the existing AF management pathway and adopting an existing acute care mHealth platform through  co-production with patients, healthcare professionals and managers to enable integrated community-based AF management.
Lead: Dr B.Kumarendran MBBS, M.Sc, MD, FRSPH 

Evaluation of existing AF management pathway is done with the possible key stakeholders  through  pathway mapping, focus group discussions and interviews via qualitative and quantitative studies.  From the AF pathway mapping data, a comprehensive mHealth platform will be implemented at the health care settings in an iterative process manner through consecutive adoptive evaluations to manage AF. The existing acute care platform fuses mobile data entry with visual analytics from acute care facilities nationwide to provide patient and health services information up to 90 days following discharge. Built for smart-phones using Android technology, the platform has been co-designed and co-evaluated  in partnership with multidisciplinary clinical and administrative teams, highlighting the platform’s adaptive interconnectivity. Alongside in-application visualization, real-time information regarding patient acuity, activity and measures of care quality are displayed in dashboards, facilitating stakeholder driven  care evaluation and resource prioritization. The research team will  partner  with  Guo  and team  on  expertise  from  the  pilot  mAFa  (mobile Atrial Fibrillation application) trial and the ongoing mAFa II outcome trial testing the ABC pathway in China (Lip Co-PI), to modify the platform’s functionality to  include decision support tools  for  AF,  chronic  disease specific data capture and multi-user synchronized communication. The collaboration will harness existing expertise in application design, data structuring and mobile communication. Once the patient’s clinical and demographic information has been captured, risk prediction tools (CHADS2 VASc & HAS – BLED2) will automatically calculate risk scores, alerting clinicians to priorities  in  referral and providing decision support, as operationalized in the mAFa pilot trial,  in early recognition and management of AF.

Theme III