Atrial fibrillation (AF) is a common irregular heart rhythm associated with a five-fold increase in stroke risk. It is often not recognised as it can occur intermittently and without symptoms. A promising approach to detect AF is to use a handheld electrocardiogram (ECG) sensor for screening. However, the ECG recordings must be manually reviewed, which is time-consuming and costly. Our aims were to: (i) evaluate the manual review workload; and (ii) evaluate strategies to reduce the workload. In total, 2141 older adults were asked to record their ECG four times per day for 1-4 weeks in the SAFER (Screening for Atrial Fibrillation with ECG to Reduce stroke) Feasibility Study, producing 162,515 recordings. Patients with AF were identified by: (i) an algorithm classifying recordings based on signal quality (high or low) and heart rhythm; (ii) a nurse reviewing recordings to correct algorithm misclassifications; and (iii) two cardiologists independently reviewing recordings from patients with any evidence of rhythm abnormality. It was estimated that 30,165 reviews were required (20,155 by the nurse, and 5005 by each cardiologist). The total number of reviews could be reduced to 24,561 if low-quality recordings were excluded from review; 18,573 by only reviewing ECGs falling under certain pathological classifications; and 18,144 by only reviewing ECGs displaying an irregularly irregular rhythm for the entire recording. The number of AF patients identified would not fall considerably: from 54 to 54, 54 and 53, respectively. In conclusion, simple approaches may help feasibly reduce the manual workload by 38.4% whilst still identifying the same number of patients with undiagnosed, clinically relevant AF.