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The research reported in this paper attempts to make a case for the notion that it may be advantageous for Operations Research (OR)/Management Science (MS) units in organizations to focus on the existing infrastructure of the organization and the means to change the infrastructure as an integral part of their strategy to achieve organizational legitimization. In other words, unless the appropriate organizational form exists, or seems amenable to modification, the acceptance and implementation of rational OR/MS decision algorithms, that is their acceptance by top management and client groups such as corporate planning, marketing, production, will be severely inhibited. This makes it particularly important to explore the measurement of organizational form and the construction of indices that later may be refined and on the basis of a relatively broad and diverse data base, allow the design of organizational forms that can accommodate organizational innovation. Overall, the analysis of organizational form indicators used here implies that removal of organizational bottlenecks is imperative for the implementation of OR/MS decision aids, and should lead to immediate improvements in decision making processes in the region.

The article discusses research being done on the use of data-mining algorithms (DMA) to detect surprise adverse drug reactions (ADR). It references a study by M. Hauben, S. Horn and L. Reich published in the 2007 issue of "Drug Safety." According to the authors, the identification of surprise reactions may serve as an important niche for DMA. Among the characteristics used to define surprise reactions include a low drug-attributable risk, intermediate seriousness and a lack of the classical hallmarks of idiosynchratic ADR.

The article discusses research being done on the use of data-mining algorithms (DMA) for detecting surprise adverse drug reactions. It references a study by M. Hauben et al in the 2007 issue of "Drug Safety." The use of proportional reporting ratios (PRR) and the empirical Bayesian algorithm multi-item gamma Poisson shrinker thresholds resulted in ±65 percent of the cases and provided a signal of disproportionate reporting for a particular drug pairing.