Risk Estimation and Value-of-Information Analysis for Three Proposed Genetic Screening Programs for Chronic Beryllium Disease Prevention

Genetic differences (polymorphisms) among members of a population are thought to influence susceptibility to various environmental exposures. In practice, however, this information is rarely incorporated into quantitative risk assessment and risk management. We describe an analytic framework for predicting the risk reduction and value-of-information (VOI) resulting from specific risk management applications of genetic biomarkers, and we apply the framework to the example of occupational chronic beryllium disease (CBD), an immune-mediated pulmonary granulomatous disease. One described Human Leukocyte Antigen gene variant, HLA-DP beta 1*0201, contains a substitution of glutamate for lysine at position 69 that appears to have high sensitivity (approximately 94%) but low specificity (approximately 70%) with respect to CBD among individuals occupationally exposed to respirable beryllium. The expected postintervention CBD prevalence rates for using the genetic variant (1) as a required job placement screen, (2) as a medical screen for semiannual in place of annual lymphocyte proliferation testing, or (3) as a voluntary job placement screen are 0.08%, 0.8%, and 0.6%, respectively, in a hypothetical cohort with 1% baseline CBD prevalence. VOI analysis is used to examine the reduction in total social cost, calculated as the net value of disease reduction and financial expenditures, expected for proposed CBD intervention programs based on the genetic susceptibility test. For the example cohort, the expected net VOI per beryllium worker for genetically based testing and intervention is $13,000, $1,800, and $5,100, respectively, based on a health valuation of $1.45 million per CBD case avoided. VOI results for alternative CBD evaluations are also presented. Despite large parameter uncertainty, probabilistic analysis predicts generally positive utility for each of the three evaluated programs when avoidance of a CBD case is valued at $1 million or higher. Although the utility of a proposed risk management program may be evaluated solely in terms of risk reduction and financial costs, decisions about genetic testing and program implementation must also consider serious social, legal, and ethical factors.     

AN IMPROVED HEURISTIC FOR STAFFING TELEPHONE CALL CENTERS WITH LIMITED OPERATING HOURS

Many telephone call centers that experience cyclic and random customer demand adjust their staffing over the day in an attempt to provide a consistent target level of customer service. The standard and widely used staffing method, which we call the stationary independent period by period (SIPP) approach, divides the workday into planning periods and uses a series of stationary independent Erlang‐c queuing models—one for each planning period—to estimate minimum staffing needs. Our research evaluates and improves upon this commonly used heuristic for those telephone call centers with limited hours of operation during the workday. We show that the SIPP approach often suggests staffing that is substantially too low to achieve the targeted customer service levels (probability of customer delay) during critical periods. The major reasons for SIPP‘ s shortfall are as follows: (1) SIPP's failure to account for the time lag between the peak in customer demand and when system congestion actually peaks; and (2) SIPP’ s use of the planning period average arrival rate, thereby assuming that the arrival rate is constant during the period. We identify specific domains for which SIPP tends to suggest inadequate staffing. Based on an analysis of the factors that influence the magnitude of the lag in infinite server systems that start empty and idle, we propose and test two simple “lagged” SIPP modifications that, in most situations, consistently achieve the service target with only modest increases in staffing.     

How to shape positive relationships in medical practices and hospitals

Managing workplace conflict is one of the most important, stressful, and time-consuming tasks faced by today's medical leaders. Poorly managed workplace conflict can alienate patients, demoralize staff, increase turnover, damage relationships with valued referral sources and third party carriers concerned about patient satisfaction, and lead medical practices to costly "corporate divorces." Physician executives cannot solve the problems caused by disruptive doctors simply by bolstering their own conflict management skills or by policing offenders. The larger contexts within which inappropriate workplace behavior occurs must also be assessed and addressed. The true leadership challenge is to intervene in ways that help to foster a "culture" of appropriate interpersonal dynamics throughout your organization. This requires learning to think and to intervene systematically.     

Psychosocial versus biomedical risk factors in Kevorkian's first forty-seven physician-assisted deaths

This article examines biomedical and psychosocial data on the first forty-seven cases of physician-assisted suicide (PAS) of Kevorkian as collected by means of both a physical autopsy and a preliminary psychological autopsy. The following patterns emerge: 1) The physical condition of these PAS patients was not typical of the conditions that lead to death in the United States. 2) Consistent with the above findings, our pilot data indicate that only 31.1 percent of these patients were terminal. While 73.9 percent were described as reporting pain, only 42.6 percent were revealed at autopsy to have a specific anatomical basis for their pain. However 36 percent were described as depressed, 66 percent as having some disability, and perhaps of key importance, 90 percent expressed a fear of dependency. Most important, our pilot data suggest the possibility of large gender differences, since 3) 68.1 percent of these forty-seven PAS's are women and only 31.9 percent are men. This represents the reverse of the gender pattern for completed suicides in the United States in 1995, resembling instead the approximate pattern for unsuccessful suicide attempts. 4) Approximately 75 percent of both men and women in the above sample were described as reporting pain. Men were almost twice as likely to have had an anatomical basis for the pain and three times as likely to be terminal. Our pilot data indicate PAS women are more likely to be described as depressed and twice as likely to have had a history of previous unsuccessful suicide attempts. 5) Kevorkian's patients were older than the typical unaided suicides in America. Reported pain decreases with age as does depression; however anatomical basis for pain increases slightly with age, and no age effect emerges for terminality. 6) Approximately two-thirds of those physician-assisted suicides were at middle SES levels. History of disability was the biggest risk factor for the low SES patients and fear of dependency for the high SES patients.     

The rescission of behaviors: Inconsistent responses in adolescent sexuality data

In longitudinal survey research, certain questions can be rescinded illogically. For instance, respondents who at Time 1 report having had sexual intercourse may at Time 2 report never having done so. This paper reports measurement techniques and analyses of these types of inconsistencies from an ongoing longitudinal adolescent sexuality project. Inconsistencies in intercourse, masturbation, and other sexual behaviors are reported and compared to rates from other studies and other less sensitive behaviors within the same study. Three conclusions are presented: (1) inconsistencies should be considered a natural part of any longitudinal survey process and should be incorporated into the response model; (2) inconsistency rates in these particular data support the contention that adolescent sexuality data of appropriate quality for analytical purposes can be obtained; and (3) inconsistency rates in fact contain substantive information concerning the processes under consideration.     

Bayesian Nonparametric Hidden Markov Models with application to the analysis of copy-number-variation in mammalian genomes

We consider the development of Bayesian Nonparametric methods for product partition models such as Hidden Markov Models and change point models. Our approach uses a Mixture of Dirichlet Process (MDP) model for the unknown sampling distribution (likelihood) for the observations arising in each state and a computationally efficient data augmentation scheme to aid inference. The method uses novel MCMC methodology which combines recent retrospective sampling methods with the use of slice sampler variables. The methodology is computationally efficient, both in terms of MCMC mixing properties, and robustness to the length of the time series being investigated. Moreover, the method is easy to implement requiring little or no user-interaction. We apply our methodology to the analysis of genomic copy number variation.     

Epsilon Birnbaum–Saunders distribution family: properties and inference

In this paper we introduce a new extension for the Birnbaum–Saunder distribution based on the family of the epsilon-skew-symmetric distributions studied in Arellano-Valle et al. (J Stat Plan Inference 128(2):427–443, 2005). The extension allows generating Birnbaun–Saunders type distributions able to deal with extreme or outlying observations (Dupuis and Mills, IEEE Trans Reliab 47:88–95, 1998). Basic properties such as moments and Fisher information matrix are also studied. Results of a real data application are reported illustrating good fitting properties of the proposed model.     

Estimating variation from data with varying element sizes

In some applications (repeated surveys, process control, monitoring use of resources etc), observations are often based on elements of varying size. This paper describes two methods of estimating the underlying variation. One method measures deviations from an overall estimate of a location parameter, while the other method is based on successive differences. Both are 'one-pass' estimates and are thus programmable without storing all the data.     

Four tests of fit for the beta-binomial distribution

Tests based on the Anderson–Darling statistic, a third moment statistic and the classical Pearson–Fisher X ² statistic, along with its third-order component, are considered. A small critical value and power study are given. Some examples illustrate important applications.