Multidisciplinary Delphi consensus on challenges and key factors for an optimal care model in chronic kidney disease

Chronic kidney disease (CKD) is associated with high morbidity, burden, and resource utilization, and represents a major challenge for healthcare systems. The purpose of this study was to analyse the care patterns for these patients and to reach a consensus on the key factors that should be implemented for an optimal care model in CKD, through a multidisciplinary and integrative vision.

A multidisciplinary panel of professionals with experience in the field of CKD was formed, composed of an advisory committee of 15 experts and an additional panel of 44 experts. Challenges and areas for improvement across the continuum of care were identified through review of scientific evidence and individual interviews with the advisory committee. Key factors for an optimal model of care in CKD were agreed and assessed using the Rand/UCLA consensus methodology (adapted Delphi), evaluating their appropriateness and necessity.

38 key factors were identified for an optimal CKD patient care model, organised into four challenges: (1) Development of CKD management models and increased visibility of the disease, (2) Prevention, optimisation of screening, early diagnosis and registration of CKD at all levels of care, (3) Comprehensive, multidisciplinary and coordinated monitoring, ensuring therapeutic optimisation and continuity of care, and (4) Reinforcement of CKD training for health care professionals and patients. 35 key factors were assessed by the panel as adequate and clearly necessary, and of these, 14 were considered highly imperative.

There is consensus on the need to prioritise CKD care at both institutional and societal levels, moving towards optimal models of CKD care based on prevention and early detection of the disease, as well as comprehensive and coordinated patient monitoring and training and awareness-raising at all levels. The key factors identified constitute a roadmap that can be implemented in the different Autonomous Communities and contribute to a significant improvement in the patient's care.