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Measures of decision sensitivity that have been applied to medical decision problems were examined. Traditional threshold proximity methods have recently been supplemented by probabilistic sensitivity analysis, and by entropy-based measures of sensitivity. The authors propose a fourth measure based upon the expected value of perfect information (EVPI),… (More)

- Gordon B Hazen
- 2003

The most commonly cited drawback to using the internal rate of return to evaluate deterministic cash flow streams is the possibility of multiple conflicting internal rates, or no internal rate at all. We claim, however, that contrary to current consensus, multiple or nonexistent internal rates are not contradictory, meaningless or invalid as rates of… (More)

T o demonstrate post hoc robustness of decision problems to parameter estimates, analysts may conduct a probabilistic sensitivity analysis, assigning distributions to uncertain parameters and computing the probability of decision change. In contrast to classical threshold proximity methods of sensitivity analysis, no appealing graphical methods are… (More)

OBJECTIVE
To quantify the trade-off between the expected increased short- and long-term costs and the expected increase in quality-adjusted life expectancy (QALE) associated with total hip arthroplasty (THA) for persons with functionally significant hip osteoarthritis.
DESIGN
A cost-effectiveness study was performed from the societal perspective by… (More)

- James C Felli, Gordon B Hazen
- 1998

The most common methods of sensitivity analysis (SA) in decision-analytic modeling are based either on proximity in parameter-space to decision thresholds or on the range of payoffs that accompany parameter variation. As an alternative, we propose the use of the expected value of perfect information (EVPI) as a sensitivity measure and argue from first… (More)

W hen a decision analyst desires a sensitivity analysis on model parameters that are estimated from data, a natural approach is to vary each parameter within one or two standard errors of its estimate. This approach can be problematic if parameter estimates are correlated or if model structure does not permit obvious standard error estimates. Both of these… (More)

In this paper we present a review of stochastic trees, a convenient modeling approach for medical treatment decision analyses. Stochastic trees are a generalization of decision trees that incorporate useful features from continuous-time Markov chains. We also discuss StoTree, a freely available software tool for the formulation and solution of stochastic… (More)

- Gordon B Hazen, Jayavel Sounderpandian
- 1999

Suppose you must choose between two pieces of information A and B. In the absence of cost, you would prefer to obtain A rather than B, and in fact would be willing to take more risk to obtain A than B. Nevertheless, you would pay more money for B than for A. Are your preferences consistent with expected utility? The answer is yes; they may very well be. We… (More)

H ealth status is inherently a multiattribute construct. We examine multiattribute utility decompositions for the quality-adjusted life year (QALY) utility model commonly employed in medical decision and cost-effectiveness analyses. We consider several independence conditions on preference, including the classical notions of preferential independence and… (More)

- James C Felli, Gordon B Hazen
- 2003

I t has come to our attention that inadvertent errors in an earlier article of ours have contributed to a small controversy 1 on the proper procedure for estimating the expected value of perfect information using Monte Carlo simulation. The errors occur in our procedure MC1 2(p101) for forming a Monte Carlo simulation estimate of the information value EVPI… (More)