The Family Team at Boston Healthcare for the Homeless Program: an integrated approach to care in outreach settings

Since 1986, the Family Team at Boston Health Care for the Homeless Program has implemented an integrated, inter-professional, team-based model of care to serve families experiencing homelessness. The Family Team employs key strategies delineated by the well-established Health Care for the Homeless model, which emphasizes the importance of outreach medicine and a case management “one-stop shop approach”. We include an account of a specific case where the Family Team’s unique model helped a refugee family in Massachusetts access medical and social services otherwise more difficult to obtain. The Family Team’s onsite presence in the hotel-shelter and the team-based approach facilitated diagnosis of and successful treatment for cervical cancer in a mother of eight children. This case report suggests that the Health Care for the Homeless model of care should be more widely adopted in order to best serve homeless families.

Abbreviations: Boston Health Care for the Homeless Program (BHCHP); Emergency Assistance (EA); Health Care for the Homeless (HCH); Massachusetts General Hospital (MGH)     

Multivariate Bayesian U-type asymmetric designs for non parametric response surface prediction under correlated errors

The objective of this paper is to study U-type designs for Bayesian non parametric response surface prediction under correlated errors. The asymptotic Bayes criterion is developed in terms of the asymptotic approach of Mitchell et al. (1994 Mitchell, T., Sacks, J., Ylvisaker, D. (1994). Asymptotic Bayes criteria for nonparametric response surface design. Ann. Stat. 22:634–651.[Crossref], [Web of Science ®] , [Google Scholar]) for a more general covariance kernel proposed by Chatterjee and Qin (2011 Chatterjee, K., Qin, H. (2011). Generalized discrete discrepancy and its applications in experimental designs. J. Stat. Plann. Inference 141:951–960.[Crossref], [Web of Science ®] , [Google Scholar]). A relationship between the asymptotic Bayes criterion and other criteria, such as orthogonality and aberration, is then developed. A lower bound for the criterion is also obtained, and numerical results show that this lower bound is tight. The established results generalize those of Yue et al. (2011 Yue, R.X., Qin, H., Chatterjee, K. (2011). Optimal U-type design for Bayesian nonparametric multiresponse prediction. J. Stat. Plann. Inference 141:2472–2479.[Crossref], [Web of Science ®] , [Google Scholar]) from symmetrical case to asymmetrical U-type designs.     

A new extension strategy on three-level factorials under wrap-around L2-discrepancy

Sequential experiment is an indispensable strategy and is applied immensely to various fields of science and engineering. In such experiments, it is desirable that a given design should retain the properties as much as possible when few runs are added to it. The designs based on sequential experiment strategy are called extended designs. In this paper, we have studied theoretical properties of such experimental strategies using uniformity measure. We have also derived a lower bound of extended designs under wrap-around L₂-discrepancy measure. Moreover, we have provided an algorithm to construct uniform (or nearly uniform) extended designs. For ease of understanding, some examples are also presented and a lot of sequential strategies for a 27-run original design are tabulated for practice.     

A NEW APPROACH TO DISCRIMINATION AND CLASSIFICATION USING A HAUSDORFF TYPE DISTANCE

A new method of discrimination and classification based on a Hausdorff type distance is proposed. In two groups, the Hausdorff distance is defined as the sum of the furthest distance of the nearest elements of one set to another. This distance has some useful properties and is exploited in developing a discriminant criterion between individual objects belonging to two groups based on a finite number of classification variables. The discrimination criterion is generalized to more than two groups in a couple of ways. Several data sets are analysed and their classification accuracy is compared to that obtained from linear discriminant function and the results are encouraging. The method in simple, lends itself to parallel computation and imposes less stringent conditions on the data.     

On the analysis of unbalanced two-level supersaturated designs via generalized linear models

Supersaturated designs (SSDs) are factorial designs in which the number of experimental runs is smaller than the number of parameters to be estimated in the model. While most of the literature on SSDs has focused on balanced designs, the construction and analysis of unbalanced designs has not been developed to a great extent. Recent studies discuss the possible advantages of relaxing the balance requirement in construction or data analysis of SSDs, and that unbalanced designs compare favorably to balanced designs for several optimality criteria and for the way in which the data are analyzed. Moreover, the effect analysis framework of unbalanced SSDs until now is restricted to the central assumption that experimental data come from a linear model. In this article, we consider unbalanced SSDs for data analysis under the assumption of generalized linear models (GLMs), revealing that unbalanced SSDs perform well despite the unbalance property. The examination of Type I and Type II error rates through an extensive simulation study indicates that the proposed method works satisfactorily.     

Knowledge Creation and Dissemination in Operations and Supply Chain Management

During the last 25 years, the ecosystem of knowledge creation and dissemination in operations and supply chain management has improved remarkably. We now see OM as a vibrant community and an ecosystem in steady state. Yet, there are many opportunities ahead to revitalize our field and to expand our influence. In the spirit of continuous improvement, we propose that we focus our major efforts on accelerating the following four developments: First, having greatly expanded the domain of operations management, we should continue to expand its boundaries. Second, after a visible increase in exploratory studies, our community should accelerate our pursuit of such research. Third, we encourage OM faculty to develop programs that enable Ph.D. students to carry out part of their work in actual organizational settings. Fourth, we should further strengthen our interactions with the business community and create mechanisms to systematically disseminate our research to its members.     

Fertility intentions and maternal health behaviour during and after pregnancy

This study examines associations between fertility intentions and maternal health behaviours during and after pregnancy among a nationally representative sample of 3,442 women from India. Two waves of data (2005, 2012) from the India Human Development Survey were analyzed to investigate the influence of unwanted births on women’s use of antenatal care, timely postnatal care, and the delivery setting using binary and ordered logistic regression, partial proportional odds models, and propensity score weighting. Fifty-eight per cent of sample births were unwanted. Regression results show that, net of maternal and household characteristics, women with unwanted births were less likely to obtain any antenatal care and had fewer antenatal tests performed. Unwantedness was also associated with a lower likelihood of delivering in an institutional setting and of obtaining timely postnatal care. The relationships between unwantedness and antenatal care, postnatal care, and delivery setting were robust to models accounting for propensity weighting.     

An Enhanced Concave Program Relaxation for Choice Network Revenue Management

The network choice revenue management problem models customers as choosing from an offer set, and the firm decides the best subset to offer at any given moment to maximize expected revenue. The resulting dynamic program for the firm is intractable and approximated by a deterministic linear program called the CDLP which has an exponential number of columns. However, under the choice‐set paradigm when the segment consideration sets overlap, the CDLP is difficult to solve. Column generation has been proposed but finding an entering column has been shown to be NP‐hard. In this study, starting with a concave program formulation called SDCP that is based on segment‐level consideration sets, we add a class of constraints called product constraints (σPC), that project onto subsets of intersections. In addition, we propose a natural direct tightening of the SDCP called , and compare the performance of both methods on the benchmark data sets in the literature. In our computational testing on the data sets, 2PC achieves the CDLP value at a fraction of the CPU time taken by column generation. For a large network our 2PC procedure runs under 70 seconds to come within 0.02% of the CDLP value, while column generation takes around 1 hour; for an even larger network with 68 legs, column generation does not converge even in 10 hours for most of the scenarios while 2PC runs under 9 minutes. Thus we believe our approach is very promising for quickly approximating CDLP when segment consideration sets overlap and the consideration sets themselves are relatively small.     

Foreign aid,public investment,and the informal economy

This paper examines the absorption of foreign aid in the presence of formal and informal production. Calibrating a two-sector open economy model to 67 aid-recipient countries for 1990–2019, we show that an increase in foreign aid drives resources into the informal sector, and away from the formal sector. With untied aid, the expansion of the informal sector can lead to an economic contraction through the Dutch Disease effect. An economic expansion with an increase in the share of formal production can be attained by re-allocating existing aid to public investment rather than an increase in the aggregate level of aid.