ABSTRACT
Background: The COVID pandemic necessitated an altered approach to transthoracic echocardiography, especially in COVID cases. Whether this has effected echocardiography lab quality is unknown. Objectives: We sought to determine whether echocardiography lab quality measures during the COVID pandemic were different from those prior to the pandemic and whether quality and comprehensiveness of echocardiograms performed during the pandemic was different between COVID and non-COVID patients. Methods: The four quality measures (diagnostic errors, appropriateness of echocardiogram, American College of Cardiology Image Quality metric and Comprehensive Exam metric in structurally normal hearts) reported quarterly in our lab were compared between two quarters during COVID (2020) and pre-COVID (2019). Each component of these metrics was also assessed in randomly selected echocardiograms in COVID patients and compared to non-COVID echocardiograms. Results: For non-COVID echocardiograms, the image quality metric did not change between 2019 and 2020 and the comprehensive exam metric improved. Diagnostic error rate did not change, and appropriateness of echocardiogram indications improved. When COVID and non-COVID echocardiograms were compared, the image quality metric and comprehensiveness exam metric were lower for COVID cases (image quality mean 21.3/23 for non-COVID, 18.6/23 for COVID, p < 0.001 and comprehensive exam mean 29.5/30 for non-COVID, 27.7/39 for COVID, p < 0.001). In particular, systemic and pulmonary veins, pulmonary arteries and aortic arch were not adequately imaged in COVID patients. For studies in which a follow-up echocardiogram was available, no new pathology was found. Conclusions: At our center, though diagnostic error rate did not change during the pandemic and the proportion of echocardiograms ordered for appropriate indications increased, imaging quality in COVID patients was compromised, especially for systemic and pulmonary veins, pulmonary arteries and arch. Though no new pathology was noted on the small number of patients who had follow-up studies, we are paying careful attention to these structures to avoid diagnostic errors going forward.
ABSTRACT
BACKGROUND: Multicentre research databases can provide insights into healthcare processes to improve outcomes and make practice recommendations for novel approaches. Effective audits can establish a framework for reporting research efforts, ensuring accurate reporting, and spearheading quality improvement. Although a variety of data auditing models and standards exist, barriers to effective auditing including costs, regulatory requirements, travel, and design complexity must be considered. MATERIALS AND METHODS: The Congenital Cardiac Research Collaborative conducted a virtual data training initiative and remote source data verification audit on a retrospective multicentre dataset. CCRC investigators across nine institutions were trained to extract and enter data into a robust dataset on patients with tetralogy of Fallot who required neonatal intervention. Centres provided de-identified source files for a randomised 10% patient sample audit. Key auditing variables, discrepancy types, and severity levels were analysed across two study groups, primary repair and staged repair. RESULTS: Of the total 572 study patients, data from 58 patients (31 staged repairs and 27 primary repairs) were source data verified. Amongst the 1790 variables audited, 45 discrepancies were discovered, resulting in an overall accuracy rate of 97.5%. High accuracy rates were consistent across all CCRC institutions ranging from 94.6% to 99.4% and were reported for both minor (1.5%) and major discrepancies type classifications (1.1%). CONCLUSION: Findings indicate that implementing a virtual multicentre training initiative and remote source data verification audit can identify data quality concerns and produce a reliable, high-quality dataset. Remote auditing capacity is especially important during the current COVID-19 pandemic.