Delphi approach to prioritising research in cardiovascular and kidney disease using routinely collected data

Chronic kidney disease (CKD) and cardiovascular disease (CVD) are leading global causes of morbidity and mortality, often coexisting and sharing common risk factors. Despite their interconnection, clinical care and research for affected individuals remain siloed and fragmented. Recognising the need for integrated approaches, this study aimed to identify and prioritise key research questions at the intersection of CKD and CVD that can be addressed using real-world healthcare data to inform more cohesive and data-driven strategies for improving outcomes across both disease areas.

A three-round modified Delphi process was conducted: Round 1 online survey collected open-ended research questions about CKD-CVD priorities via BHF Data Science Centre, Kidney Research UK, UK Renal Health Data Network and HDR UK public involvement channels; Round 2 in-person workshop refined and consolidated items; Round 3 online survey prioritised items across urgency, feasibility and impact using 5-point scales.

Survey mean scores for each research question were calculated across the three prioritisation domains, each scored out of 5. The top-ranked questions were identified based on overall scores.

Six thematic domains emerged: risk prediction and early detection, treatment optimisation, health inequities, multimorbidity, disease mechanisms and data infrastructure. The highest-rated research priority was "What are the most effective strategies for prevention, early diagnosis and intervention in CKD?" with a mean score of 12.6 (SD 1.1). Other top priorities included evaluating the cost-effectiveness of early treatment, identifying predictors of kidney failure and assessing the benefits of treating cardiovascular and renal conditions independently.

Across domains, prevention/early detection and early treatment in CKD consistently ranked highest, indicating near-term opportunities for data-enabled cardio-renal research and service improvement; these priorities can inform funder calls, data linkage work and evaluation studies.