CLINICIAN COMPREHENSION OF QUALITY INDICATOR PRESENTATIONS IN KIDNEY FAILURE CARE
DR CHRISTOPHER DAVIES1,2, EMILY DUNCANSON1,3, NICHOLAS GRAY1,4,5, STEPHEN MCDONALD1,2,6
1Australia & New Zealand Dialysis & Transplant Registry (ANZDATA), South Australian Health and Medical Research Institute, Adelaide, Australia, 2Adelaide Medical School, Faculty of Health & Medical Sciences, The University of Adelaide, Adelaide, Australia, 3School of Psychology, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, Australia, 4Renal Unit, Sunshine Coast University Hospital, Birtinya, Australia, 5School of Health, University of Sunshine Coast, Sippy Downs, Australia, 6Central & Northern Adelaide Renal & Transplantation Services (CNARTS), Royal Adelaide Hospital, Adelaide, Australia
Aim: To assess which format for presentation of kidney failure care quality indicator data is best understood by clinicians.
Background: The Australia and New Zealand Dialysis and Transplant Registry (ANZDATA) publishes reports that compare units by their quality of care. Alternative presentation options to the current format may provide improved comprehension and ease of interpretation.
Methods: An online survey targeted at nephrologists was conducted from August 2022 to September 2023. Four alternative presentations of centre-specific standardised mortality rates were provided; the two currently used formats (tables and funnel plots) and two new alternatives. The new options, developed according to recommendations from the literature, were a table with icons showing hospitals underperforming, and a forest plot indicating the underperforming hospitals. Participants were asked which hospitals were underperforming in each presentation and about the ease/difficulty of the interpretation.
Results: 74 respondents completed at least one section of the survey. Among these, 66% were aged 40-59 and 64% were male.
The best comprehension was for the table with icons, with 94% able to correctly identify the complete list of underperforming hospitals. The forest plot was also well comprehended at 87%. The funnel plot had the lowest correct interpretation of all units (65%), with the simple table having 77%.
The forest plot was the rated easiest to interpret, with 88% responding easy (or higher), with the funnel plot and then table with icons next easiest respectively at 73% and 65% easy. The simple table was rated as most difficult with only 35% responding easy.
Conclusions: Alternative presentation options for ANZDATA quality indicators are likely to provide improved clinician comprehension and ease of use, with implementation planned for future reports.
Biography:
Dr Christopher Davies is the Lead Biostatistician at the Australia and New Zealand Dialysis and Transplant Registry (ANZDATA) within the South Australian Health and Medical Research Institute. At ANZDATA, Christopher provides statistical support for the generation of regular reports and the extraction of data for custom external requests. Christopher also conducts analyses for ANZDATA research projects and in collaboration with those in the nephrology community. Christopher completed a PhD in Statistics at the University of Adelaide, focussing on group-based trajectory modelling. His research interests include methods for comparing centres, and for longitudinal data.