Impact of diagnostic checklists on the interpretation of normal and abnormal electrocardiograms

Abstract Objectives Checklists that aim to support clinicians’ diagnostic reasoning processes are often recommended to prevent diagnostic errors. Evidence on checklist effectiveness is mixed and seems to depend on checklist type, case difficulty, and participants’ expertise. Existing studies primarily use abnormal cases, leaving it unclear how the diagnosis of normal cases is affected by checklist use. We investigated how content-specific and debiasing checklists impacted performance for normal and abnormal cases in electrocardiogram (ECG) diagnosis. Methods In this randomized experiment, 42 first year general practice residents interpreted normal, simple abnormal, and complex abnormal ECGs without a checklist. One week later, they were randomly assigned to diagnose the ECGs again with either a debiasing or content-specific checklist. We measured residents’ diagnostic accuracy, confidence, patient management, and time taken to diagnose. Additionally, confidence-accuracy calibration was assessed. Results Accuracy, confidence, and patient management were not significantly affected by checklist use. Time to diagnose decreased with a checklist (M=147s (77)) compared to without a checklist (M=189s (80), Z=−3.10, p=0.002). Additionally, residents’ calibration improved when using a checklist (phase 1: R2=0.14, phase 2: R2=0.40). Conclusions In both normal and abnormal cases, checklist use improved confidence-accuracy calibration, though accuracy and confidence were not significantly affected. Time to diagnose was reduced. Future research should evaluate this effect in more experienced GPs. Checklists appear promising for reducing overconfidence without negatively impacting normal or simple ECGs. Reducing overconfidence has the potential to improve diagnostic performance in the long term.