Stefanos A. Zenios

An Empiric Estimate of the Value of Life: Updating the Renal Dialysis Cost‐Effectiveness Standard

OBJECTIVES Proposals to make decisions about coverage of new technology by comparing the technologys incremental cost-effectiveness with the traditional benchmark of dialysis imply that the incremental cost-effectiveness ratio of dialysis is seen a proxy for the value of a statistical year of life. The frequently used ratio for dialysis has, however, not been updated to reflect more recently available data on dialysis. METHODS We developed a computer simulation model for the end-stage renal disease population and compared cost, life expectancy, and quality adjusted life expectancy of current dialysis practice relative to three less costly alternatives and to no dialysis. We estimated incremental cost-effectiveness ratios for these alternatives relative to the next least costly alternative and no dialysis and analyzed the population distribution of the ratios. Model parameters and costs were estimated using data from the Medicare population and a large integrated health-care delivery system between 1996 and 2003. The sensitivity of results to model assumptions was tested using 38 scenarios of one-way sensitivity analysis, where parameters informing the cost, utility, mortality and morbidity, etc. components of the model were by perturbed +/-50%. RESULTS The incremental cost-effectiveness ratio of dialysis of current practice relative to the next least costly alternative is on average

Dynamic Allocation of Kidneys to Candidates on the Transplant Waiting List

129,090 per quality-adjusted life-year (QALY) (

Dynamic Multidrug Therapies for HIV: A Control Theoretic Approach

61,294 per year), but its distribution within the population is wide; the interquartile range is

Diminishing significance of HLA matching in kidney transplantation

71,890 per QALY, while the 1st and 99th percentiles are

Primum non nocere: avoiding harm to vulnerable wait list candidates in an indirect kidney exchange.

65,496 and

Supply Auctions and Relational Contracts for Procurement

488,360 per QALY, respectively. Higher incremental cost-effectiveness ratios were associated with older age and more comorbid conditions. Sensitivity to model parameters was comparatively small, with most of the scenarios leading to a change of less than 10% in the ratio. CONCLUSIONS The value of a statistical year of life implied by dialysis practice currently averages

Recipient Choice Can Address the Efficiency-Equity Trade-off in Kidney Transplantation: A Mechanism Design Model

129,090 per QALY (

Evidence-based organ allocation ∗

61,294 per year), but is distributed widely within the dialysis population. The spread suggests that coverage decisions using dialysis as the benchmark may need to incorporate percentile values (which are higher than the average) to be consistent with the Rawlsian principles of justice of preserving the rights and interests of societys most vulnerable patient groups.

Modeling the transplant waiting list: A queueing model with reneging

The crux of the kidney allocation problem is the trade-off between clinical efficiency and equity. We consider a dynamic resource allocation problem with the tri-criteria objective of maximizing the quality-adjusted life expectancy of transplant candidates (clinical efficiency) and minimizing two measures of inequity: a linear function of the likelihood of transplantation of the various types of patients, and a quadratic function that quantifies the differences in mean waiting times across patient types. The dynamic status of patients is modeled by a set of linear differential equations, and an approximate analysis of the optimal control problem yields a dynamic index policy. We construct a large-scale simulation model using data from over 30,000 transplants, and the simulation results demonstrate that, relative to the organ allocation policy currently employed in the United States, the dynamic index policy increases the quality-adjusted life expectancy and reduces the mean waiting time until transplantation for all six demographic groups (two sexes, races, and age groups) under consideration.

A Dynamic Principal-Agent Model with Hidden Information: Sequential Optimality Through Truthful State Revelation

Motivated by the inability of current drug treatment to provide long-term benefit to HIV-infected individuals, we derive HIV therapeutic strategies by formulating and analyzing a mathematical control problem. The model tracks the dynamics of uninfected and infected CD4+ cells and free plasma virus, and allows the virus to mutate into various strains. At each point in time, several different therapeutic options are available, where each option corresponds to a combination of reverse transcriptase inhibitors. The controller observes the individuals current status and chooses among the therapeutic options in a dynamic fashion in order to minimize the total viral load. Our initial numerical results suggest that dynamic therapies have the potential to significantly outperform the static protocols that are currently in use; by anticipating and responding to the disease progression, the dynamic strategy reduces the total free virus, increases the uninfected CD4+ count, and delays the emergence of drug-resistant strains.