Background: The Movember funded TrueNTH Global Registry (TNGR) aims to improve care by collecting and analysing a consistent dataset to identify variation in disease management, benchmark care delivery in accordance with best practice guidelines and provide this information to those in a position to enact change. We discuss considerations of designing and implementing a quality of care report for TNGR.
Methods: Eleven working group sessions were held prior to and as reports were being built with representation from clinicians, data managers and investigators contributing to TNGR. The aim of the meetings was to understand current data display approaches, share literature review findings and ideas for innovative approaches. Preferred displays were evaluated with two surveys (survey 1: 5 clinicians and 5 non-clinicians, 83% response rate; survey 2: 17 clinicians and 18 non-clinicians, 93% response rate).
Results: Consensus on dashboard design and three data-display preferences were achieved. The dashboard comprised two performance summary charts; one summarising site's relative quality indicator (QI) performance and another to summarise data quality. Binary outcome QIs were presented as funnel plots. Patient-reported outcome measures of function score and the extent to which men were bothered by their symptoms were presented in bubble plots. Time series graphs were seen as providing important information to supplement funnel and bubble plots. R Markdown was selected as the software program principally because of its excellent analytic and graph display capacity, open source licensing model and the large global community sharing program code enhancements.
Conclusions: International collaboration in creating and maintaining clinical quality registries has allowed benchmarking of process and outcome measures on a large scale. A registry report system was developed with stakeholder engagement to produce dynamic reports that provide user-specific feedback to 132 participating sites across 13 countries.
Keywords: R Markdown; benchmarking; data display; data science; international registry; quality indicators (health care).