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INTRODUCTIO NSRI International participated in the MUC-6 evaluation using the latest version of SRI's FASTUS system [1] . The FASTUS system was originally developed for participation in the MUC-4 evaluatio n [3] in 1992, and the performance of FASTUS in MUC-4 helped demonstrate the viability of finit e state technologies in constrained natural-language understanding tasks . The system has undergon e significant revision since MUC-4, and it is safe to say that the current system does not share a singl e line of code with the original . The fundamental ideas behind FASTUS, however, are retained i n the current system : an architecture consisting of cascaded finite state transducers, each providin g an additional level of analysis of the input, together with merging of the final results . This paper will describe the version of the FASTUS system employed in MUC-6 and highlight the innovations that distinguish it from previous versions described in the literature . SRI used the FASTUS system for each of the MUC-6 tasks : the named entity task, the templateentity task, the coreference task, and the scenario template task . Because a single system, with a single configuration, was used to run all the tasks, and because the first three tasks are in som e sense prerequisites to the fourth, we will focus our attention in this paper on the scenario templat e task . BASIC FASTUSThe SRI FASTUS system is based on a series of finite-state transducers that compute the transformation of text from sequences of characters to domain templates . This architecture has proven t o be very flexible, and has been applied with success to a number of different information extractio n tasks in widely varying domains . We have applied FASTUS to extraction of information about terrorist incidents [3], extraction of information about joint ventures [2], indexing of legal document s for hypertext, extracting extensive information from military texts (Warbreaker Message Handler) , extraction of information from spoken dialogues [4], and a number of other smaller systems an d pilot applications . We have applied FASTUS to Japanese texts [2, 4] as well as English .Each transducer (or "phase") in the series takes the output of the previous phase and map s it into structures that comprise the input to the next phase, or that contain the domain templat e
Current research suggests that hourly rounds on hospitalized patients may be associated with improvements in care delivery and in the patients' perception of care, as well as a reduction in patient safety events. Implementing an hourly rounding protocol involves a major change in nursing staff workflow and a substantial training and education program to ensure the success of the program. This quasi-experimental study aimed to determine if a standardized hourly rounding process (SHaRP), implemented through a formal education program, would result in improved efficiency, quality, safety, and patient satisfaction metrics when compared to a less standardized process introduced through the traditional train-the-trainer method. Data were collected over a 6-month period and results were trended for an additional 6 months later to determine if significant gains were sustained over time. Significant reductions in call light use during the study period (p = .001) and the number of steps taken by the day-shift staff (p = .02) were seen on the intervention unit. Differences in the number of patient falls, 30-day readmission rates, and patients' perception of care were not statistically significant.
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