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Introduction Interventions are needed to improve early detection of indications for dialysis before development of severe symptoms or complications. This may reduce suboptimal dialysis starts, prevent hospitalizations, and decrease costs. Our objectives were to explore assumptions around a nurse-led virtual case management intervention for patients with late-stage chronic kidney disease (CKD) with a 2-year Kidney Failure Risk Equation (KFRE) estimated risk of kidney failure ≥80% and to estimate how these assumptions affect potential cost savings. Methods We performed a cost-minimization analysis by developing a decision analytic microsimulation model constructed from the perspective of the health payer. Our primary outcome was the break-even point, defined as the maximum amount a health payer could spend on the intervention without incurring any net financial loss or gain. The intervention group received remote telemonitoring, including daily measurement of several health metrics (blood pressure, oxygen saturation, and weight), and a validated symptom questionnaire accompanied by nurse-led case management, whereas the comparator group received usual care. We assumed patients received the intervention for a maximum of 2 years. Results The break-even point was $7339 per late-stage CKD patient enrolled in the intervention. Based on the distribution of time receiving the intervention, we determined a maximum monthly intervention cost of $703.37. In probabilistic sensitivity analyses, we found that 75% of simulations produced break-even points between $3929 and $9460. Conclusion Nurse-led virtual home monitoring interventions in patients with CKD at high risk of kidney failure have the potential for significant cost savings from the perspective of the health payer., Graphical abstract

Rationale & Objective The kidney failure population is growing, necessitating the expansion of dialysis programs. These programs are costly and require a substantial amount of health care resources. Tools that accurately forecast resource use can aid efficient allocation. The objective of this study is to describe the development of an economic simulation model that incorporates treatment history and detailed modality transitions for patients with kidney disease using real-world data to estimate associated costs, utility, and survival by initiating modality. Study Design Cost-utility model with microsimulation. Setting & Population Adult incident maintenance dialysis patients in Canada who initiated facility-based hemodialysis (HD) or home peritoneal dialysis (PD) between 2004 and 2013. Intervention HD and PD. Outcomes Costs (related to dialysis, transplantation, infections, and hospitalizations), survival, utility, and dialysis modality mix over time. Model, Perspective, & Timeframe The model took the perspective of the health care payer. Patients were followed up for 10 years from initiation of dialysis. Our cost-utility analysis compared the intervention with receiving no treatment. Results During a 10-year time horizon, the cost-utility ratio for all patients initiating dialysis was $103,779 per quality-adjusted life-year (QALY) in comparison to no treatment. Patients who initiated with facility-based HD were treated at a cost-utility ratio of $104,880/QALY and patients who initiated with home PD were treated at a cost-utility ratio of $83,762/QALY. During this time horizon, the total mean cost and QALYs per patient were estimated at $350,774 ± $204,704 and 3.38 ± 2.05) QALYs respectively. Limitations The results do not include costs from the societal perspective. Rare patient trajectories were unable to be assessed. Conclusions This model demonstrates that patients who initiated dialysis with PD were treated more cost-effectively than those who initiated with HD during a 10-year time horizon., Graphical abstract