What is already known about this topic and why is it important?
Registry analysis demonstrated home dialysis usage varies widely by centre, despite clear economic and likely patient benefits. This included poorer access to home dialysis for deprived/BAME populations, but the drivers for these differences remain unclear. A previous analysis (Castledine et al, NDT) described some broad-brush practices associated with higher home dialysis usage
How will you carry out your study?
WP1 – Ethnographic study of 4 centres selected to represent good and average practice, including areas with significant BAME and deprived populations. Non-participant observation, plus think-aloud interviews and semi-structured interviews of staff and patients will be used.
WP2 – detailed survey of all English renal units describing centre-level characteristics relevant to home dialysis usage, based on known associations, those considered potentially relevant and those identified by the ethnographic study (WP1). These results will be combined with patient-level Registry data, allowing a graphical Markov model to identify potentially important drivers of home dialysis and a multistate model to estimate effects from changing practices.
WP3 – A health economic model reflecting the range of health states associated with renal replacement therapy will be informed by the output from WP2 to quantify the potential impact of changing practice.
WP4 - combine the data from previous WP’s to synthesise/interpret it in order to develop a number of potential intervention bundles that could reduce/eliminate the centre effect in home therapy uptake. The impact of these bundles will then, in an iterative process with the data from WP2 and WP3, be assessed using the explanatory statistical model and the updated health economic model for the trade-off between benefits/ceiling costs.
WP5 - development of an intervention by co-design in two workshops, with representation from doctors, nurses, allied health professionals, patients and policy leads.
How will you decide which patients are included in your study?
All incident RRT patients over the most recent complete 4 year period.
How many patients do you anticipate including?
We anticipate approximately 31,000 patients
For how long will you follow up these patients?
Until the date of most recent data i.e. the end of the 4 year block.
What value will UKRR data add to the project?
This will form a crucial part of the study, allowing identification of the underlying drivers of home dialysis to inform development of an effective intervention. It will also allow the estimation of rates of dialysis use modalities, transplant and mortality, to understand the impact of change and health economic benefit from the recommended intervention.
What new information will your study generate and how will this benefit patients?
This study will produce the most detailed understanding of drivers of home dialysis usage and the patient and health economic benefits associated with effective interventions. Patients will benefit through introduction of an intervention that will address between-centre variation, as well as improved access to home dialysis for deprived and BAME groups where there is currently variability in practice and outcome.
