Cost-effectiveness Analysis of Vascular Access Referral Policies in CKD.

BACKGROUND: The optimal timing of vascular access referral for patients with chronic kidney disease who may need hemodialysis (HD) is a pressing question in nephrology. Current referral policies have not been rigorously compared with respect to costs and benefits and do not consider patient-specific factors such as age. STUDY DESIGN: Monte Carlo simulation model. SETTING & POPULATION: Patients with chronic kidney disease, referred to a multidisciplinary kidney clinic in a universal health care system. MODEL, PERSPECTIVE, & TIMEFRAME: Cost-effectiveness analysis, payer perspective, lifetime horizon. INTERVENTION: The following vascular access referral policies are considered: central venous catheter (CVC) only, arteriovenous fistula (AVF) or graft (AVG) referral upon HD initiation, AVF (or AVG) referral when HD is forecast to begin within 12 (or 3 for AVG) months, AVF (or AVG) referral when estimated glomerular filtration rate is <15 (or <10 for AVG) mL/min/1.73m2. OUTCOMES: Incremental cost-effectiveness ratios (ICERs, in 2014 US dollars per quality-adjusted life-year [QALY] gained). RESULTS: The ICER of AVF (AVG) referral within 12 (3) months of forecasted HD initiation, compared to using only a CVC, is ∼$105k/QALY ($101k/QALY) at a population level (HD costs included). Pre-HD AVF or AVG referral dominates delaying referral until HD initiation. The ICER of pre-HD referral increases with patient age. Results are most sensitive to erythropoietin costs, ongoing HD costs, and patients' utilities for HD. When ongoing HD costs are excluded from the analysis, pre-HD AVF dominates both pre-HD AVG and CVC-only policies. LIMITATIONS: Literature-based estimates for HD, AVF, and AVG utilities are limited. CONCLUSIONS: The cost-effectiveness of vascular access referral is largely driven by the annual costs of HD, erythropoietin costs, and access-specific utilities. Further research is needed in the field of dialysis-related quality of life to inform decision making regarding vascular access referral.

Timing of arteriovenous fistula creation in patients With CKD: a decision analysis.

BACKGROUND: The optimal time for arteriovenous fistula (AVF) referral is uncertain. Improving the timeliness of referral may reduce central venous catheter (CVC) use. STUDY DESIGN: Monte Carlo simulation model. SETTING & POPULATION: Patients with chronic kidney disease (CKD) followed up in a multidisciplinary clinic, overall and stratified by age. MODEL, PERSPECTIVE, & TIMEFRAME: Decision analysis, patient, patient's lifetime. INTERVENTION: AVF referral, using 1 of 2 strategies: refer when hemodialysis is anticipated to begin within a certain time frame or refer when estimated glomerular filtration rate (eGFR) drops below a certain threshold. OUTCOMES: A range of values for each strategy are compared to each other with respect to incident vascular access type (AVF or CVC), percentage of patients with an unnecessary AVF creation, and life expectancy after dialysis therapy initiation. RESULTS: A 15-month referral time frame gave 34% with incident CVCs, 14% with unnecessary AVFs, and a life expectancy of 1,751 days. Time frames of 12-18 months performed similarly. Referral at eGFR of 20 mL/min/1.73 m(2) gave 38% with incident CVCs, 20% with unnecessary AVFs, and life expectancy of 1,742 days. Using an eGFR threshold of 15 mL/min/1.73 m(2), 10% had an unnecessary AVF. Policy performance was affected by CKD progression rate and age. For fast progressors (ΔeGFR = -7mL/min/1.73 m(2) per year), referral at eGFR of 25 mL/min/1.73 m(2) achieved a similar incident CVC percentage (~40%) as referral at 15 mL/min/1.73 m(2) in slower progressors (ΔeGFR = -2.78 mL/min/1.73 m(2) per year). For patients aged 70-80 and 80-90 years, time frames of 15-18 months yielded 16%-22% with unnecessary AVFs (vs 9%-11% in 50- to 60-year-olds); an eGFR threshold strategy of 20 mL/min/1.73 m(2) yielded 24% unnecessary AVFs in 80- to 90-year-olds versus 16% in 50- to 60-year-olds. LIMITATIONS: Our model does not consider patients with nonlinear CKD progression or acute kidney injury. We did not include arteriovenous grafts or consider cost or quality of life. CONCLUSIONS: In general, AVF referral within about 12 months of the estimated time to dialysis performed best among time frame strategies, and referral at eGFR < 15-20 mL/min/1.73 m(2) performed best among threshold strategies. The timing of referral should also be guided by the individual rate of CKD progression. Elderly patients with CKD could be referred later to reduce the risk of creating an AVF that is never used.

State-space size considerations for disease-progression models.

Markov models of disease progression are widely used to model transitions in patients' health state over time. Usually, patients' health status may be classified according to a set of ordered health states. Modelers lump together similar health states into a finite and usually small, number of health states that form the basis of a Markov chain disease-progression model. This increases the number of observations used to estimate each parameter in the transition probability matrix. However, lumping together observably distinct health states also obscures distinctions among them and may reduce the predictive power of the model. Moreover, as we demonstrate, precision in estimating the model parameters does not necessarily improve as the number of states in the model declines. This paper explores the tradeoff between lumping error introduced by grouping distinct health states and sampling error that arises when there are insufficient patient data to precisely estimate the transition probability matrix.

Increasing the efficiency of Monte Carlo cohort simulations with variance reduction techniques.

The authors discuss techniques for Monte Carlo (MC) cohort simulations that reduce the number of simulation replications required to achieve a given degree of precision for various output measures. Known as variance reduction techniques, they are often used in industrial engineering and operations research models, but they are seldom used in medical models. However, most MC cohort simulations are well suited to the implementation of these techniques. The authors discuss the cost of implementation versus the benefit of reduced replications.

A methodological framework for optimally reorganizing liver transplant regions.

BACKGROUND: The United States is divided currently into 11 transplant regions, which vary in area and number of organ procurement organizations (OPOs). Region size affects organ travel time and organ viability at transplant. PURPOSE: To develop a methodologic framework for determining optimal configurations of regions maximizing transplant allocation efficiency and geographic parity. METHODS: An integer program was designed to maximize a weighted combination of 2 objectives: 1) intraregional transplants, 2) geographic parity-maximizing the lowest intraregional transplant rate across all OPOs. Two classes of functions relating liver travel time to liver viability were also examined as part of the sensitivity analyses. RESULTS: Preliminary results indicate that reorganizing regions, while constraining their number to 11, resulted in up to 17 additional transplants/year depending on the travel-viability function; when not constrained, it resulted in up to 18/year of increase. CONCLUSION: Our analysis indicates that liver transplantation may benefit through region reorganization. The analytic method developed here should be applicable to other organs and sets of organs.

A clinically based discrete-event simulation of end-stage liver disease and the organ allocation process.

BACKGROUND: The optimal allocation of scarce donor livers is a contentious health care issue requiring careful analysis. The objective of this article was to design a biologically based discrete-event simulation to test proposed changes in allocation policies. METHODS: The authors used data from multiple sources to simulate end-stage liver disease and the complex allocation system. To validate the model, they compared simulation output with historical data. RESULTS: Simulation outcomes were within 1% to 2% of actual results for measures such as new candidates, donated livers, and transplants by year. The model overestimated the yearly size of the waiting list by 5% in the last year of the simulation and the total number of pretransplant deaths by 10%. CONCLUSION: The authors created a discrete-event simulation model that represents the biology of end-stage liver disease and the health care organization of transplantation in the United States.

Treatment evolution and new standards of care: implications for cost-effectiveness analysis.

BACKGROUND: Traditional approaches to cost-effectiveness analysis have not considered the downstream possibility of a new standard of care coming out of the research and development pipeline. However, the treatment landscape for patients may change significantly over the course of their lifetimes. OBJECTIVE: To present a Markov modeling framework that incorporates the possibility of treatment evolution into the incremental cost-effectiveness ratio (ICER) that compares treatments available at the present time. DESIGN: . Markov model evaluated by matrix algebra. Measurements. The author evaluates the difference between the new and traditional ICER calculations for patients with chronic diseases facing a lifetime of treatment. RESULTS: The bias of the traditional ICER calculation may be substantial, with further testing revealing that it may be either positive or negative depending on the model parameters. The author also performs probabilistic sensitivity analyses with respect to the possible timing of a new treatment discovery and notes the increase in the magnitude of the bias when the new treatment is likely to appear sooner rather than later. Limitations. The modeling framework is intended as a proof of concept and therefore makes simplifying assumptions such as time stationarity of model parameters and consideration of a single new drug discovery. CONCLUSIONS: For diseases with a more active research and development pipeline, the possibility of a new treatment paradigm may be at least as important to consider in sensitivity analysis as other parameters that are often considered.