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.

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.

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.

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.

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.

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.

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.