South Korea is assumed to be a high-context culture with extensive shared information and an emphasis on relationships in doing business. The following study reported here tests this assumption and illustrates similarities and differences between Korean and American writers in an attempt to document language differences between high-and lowcontext societies. Data in the texts studied did not confirm the high/low contextfeatures expected. South Korean texts showed more similarities to than differences from the American texts, and the language features found suggest a more complex context situation than the high/low context model may be able to accommodate.

According to traditional concepts of hospital governance, each institution is considered responsible for the care of a defined community. Evaluation of hospital performance and effective service planning both require that hospitals' service communities be identified. However, in metropolitan regions it is difficult to associate a geographic population with any one hospital because of the wide choice of facilities available to area residents. The service community concept becomes more meaningful in these regions if several hospitals with overlapping geographic communities are defined as a cluster. This paper describes a two-step method for identifying hospital clusters and their associated service communities. The first step involves analysis of patient origin data to identify logical clusters of hospitals. Three algorithms for performing this analysis are presented. In the second step, analytical findings are reviewed by a panel of area planners and hospital experts who, considering additional qualitative factors, determine how the hospitals may be most appropriately grouped. Experience in using this method for hospitals in the seven-county region around Detroit, Michigan suggests that reasonable clusters can be identified, although clusters of central city hospitals are less well-defined than those in the suburban areas.

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