OBJECTIVES: A multi-centre, prospective, observational study aimed to recruit 500 newly diagnosed AF patients and 500 matched controls to assess AF symptom burden and HRQOL using THIN UK primary care data. Patient enrolment as soon after diagnosis as possible was vital. Existing methodology of identifying patients from fully processed data would not have enrolled patients as quickly as necessary to assess newly diagnosed AF. The objective was to assess the effectiveness of a novel methodology used to recruit patients as soon after diagnosis as possible from THIN. METHODS: Cases and controls matched by age, gender and geography were identified as soon as data were received from THIN practices rather than after data were fully processed (normal route for identifying patients). Patients were therefore identified within one week of diagnosis being recorded. Practices were contacted by THIN staff and asked to confirm eligibility. Practices invited eligible patients to participate, ensuring no direct contact between THIN staff and patients. Patients were asked to complete HRQOL questionnaires at enrolment, 6 and 12 months’ follow-up. RESULTS: Within 18 months, this method was successful in recruiting beyond the necessary sample size (516 case-control pairs). This methodology minimised the impact of recruitment and follow-up on clinical management of patients, who were seen at a frequency determined in accordance with their normal medical care only. Diagnostic assessments of patients were not required and so, other than the questionnaires, there was no additional burden to normal clinical practice. CONCLUSIONS: This is an innovative method for patient recruitment using THIN primary care patient data. Newly diagnosed AF patients who might be eligible and for whom clinical information is already available can be quickly identified. Large numbers of newly diagnosed patients can be recruited more rapidly compared to existing methods and followed up in an efficient and cost-effective way.