Uncertainty and Variation in Indirect Exposure Assessments: An Analysis of Exposure to Tetrachlorodibenzo-p-Dioxin from a Beef Consumption Pathway

Indirect exposures to 2,3,7,8-tetrachlorodibenzo- p -dioxin (TCDD) and other toxic materials released in incinerator emissions have been identified as a significant concern for human health. As a result, regulatory agencies and researchers have developed specific approaches for evaluating exposures from indirect pathways. This paper presents a quantitative assessment of the effect of uncertainty and variation in exposure parameters on the resulting estimates of TCDD dose rates received by individuals indirectly exposed to incinerator emissions through the consumption of home-grown beef. The assessment uses a nested Monte Carlo model that separately characterizes uncertainty and variation in dose rate estimates. Uncertainty resulting from limited data on the fate and transport of TCDD are evaluated, and variations in estimated dose rates in the exposed population that result from location-specific parameters and individuals'behaviors are characterized. The analysis indicates that lifetime average daily dose rates for individuals living within 10 km of a hypothetical incinerator range over three orders of magnitude. In contrast, the uncertainty in the dose rate distribution appears to vary by less than one order of magnitude, based on the sources of uncertainty included in this analysis. Current guidance for predicting exposures from indirect exposure pathways was found to overestimate the intakes for typical and high-end individuals.     

Omnibus Tests of The Martingale Assumption in The Analysisof Recurrent Failure Time Data

The Andersen-Gill multiplicative intensity(MI) model is well-suited to the analysis of recurrent failuretime data. The fundamental assumption of the MI model is thatthe process M_i(t) for subjects i=1,,n,defined to be the difference between a subject's counting processand compensator, i.e., N_i(t) A_i(t); >0,is a martingale with respect to some filtration. We propose omnibusprocedures for testing this assumption. The methods are basedon transformations of the estimated martingale residual process ^M _i (t) a function of consistent estimatesof the log-intensity ratios and the baseline cumulative hazard.Under a correctly specified model, the expected value of ^M _i (t)is approximately equal to zero with approximately uncorrelatedincrements. These properties are exploited in the proposed testingprocedures. We examine the effects of censoring and covariateeffects on the operating characteristics of the proposed methodsvia simulation. The procedures are most sensitive to the omissionof a time-varying continuous covariate. We illustrate use ofthe methods in an analysis of data from a clinical trial involvingpatients with chronic granulatomous disease.     

Estimating the expense of a mandatory home-and community-based personal assistance services benefit under Medicaid

Personal assistance services (PAS) are essential for many people of all ages with significant disabilities, but these services are not always available to individuals at home or in the community, in large part due to a significant bias toward institutions in the Medicaid program. This study aims to provide an estimate of the expense of a mandatory personal assistance services (PAS) benefit under Medicaid for persons with low incomes, low assets, and significant disability. DESIGN AND METHODS: We use year 2003 data from the Survey of Income and Program Participation to estimate the number of people living in households who would be eligible, based on having an institutional level of need and meeting financial criteria for low income and low assets, combined with additional survey data on annual expenditures under Medicaid programs providing PAS. RESULTS: New expenditures for PAS are estimated to be $1.4-$3.7 billion per year (in 2006 dollars), depending on the rate of participation, for up to half a million new recipients, more than a third of whom would be ages 65 and older. These estimated expenditures are a tenth of those estimated by the Congressional Budget Office for implementing the Medicaid Community-Based Attendant Services and Supports Act (MiCASSA). IMPLICATIONS: Creating a mandatory PAS benefit for those with an institutional level of need is a fiscally achievable policy strategy to redress the imbalance between institutional and community-based services under Medicaid.     

Change and inertia in the New York state medicaid personal care services program: an institutional case study

This study analyzes how competing logics (belief systems) of stakeholders have influenced patterns of change and inertia in the development of the New York Medicaid Personal Care Services (PCS) program. A case-study methodology was used to collect documents, statistics, and interview data from four key stakeholder groups: state and city officials, PCS agencies, a labor union, and consumer advocates covering the period 1999 to 2005. The New York PCS program is one of the oldest, largest, and most stable programs in the United States. Its early unionization of workers resulted in relatively generous wages and benefits and made New York number one nationally in PCS spending per capita. In spite of wide support from stakeholder groups, the overall number of participants has gradually declined since 1999. A consumer-directed model of personal care developed in 1995 challenged the status quo and has grown steadily. Resistance by public officials, agency providers, and union representatives to the consumer-directed model has resulted in a small program that is often targeted toward individuals labeled "difficult to serve." Dominant stakeholders in New York have ensured a stable personal care program that has resisted change and led to program inertia.     

PORTFOLIO MODELING IN MULTIPLE-CRITERIA SITUATIONS UNDER UNCERTAINTY: COMMENT

In a recent issue of Decision Sciences, Muhlemann, Lockett, and Gear [8] developed a multiple-objective, stochastic linear programming formulation of the multiperiod portfolio selection problem under uncertainty. The purpose of this note is to offer some extensions to their multicriteria approach which is otherwise viewed as an excellent attempt at modeling realistic aspects of the portfolio selection problem. Further, integer goal programming combined with simulation is suggested as an alternate approach for solving the dynamic multiple-objective problem.