Spatio-temporal Structure of US Critical Care Transfer Network.

AMIA Joint Summits on Translational Science proceedings AMIA Summit on Translational Science(2013)

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摘要
Most Americans are in Intensive Care Units (ICUs) at some point during their lives. There is wide variation in the outcome quality of ICUs and so, thousands of patients who die each year in ICUs may have survived if they were at the appropriate hospital. In spite of a policy agenda from IOM calling for effective transfer of patients to more capable hospitals to improve outcomes, there appear to be substantial inefficiencies in the existing system. In particular, patients recurrently transfer to secondary hospitals rather than to a most-preferred option. We present data mining schemes and significance tests to discover these inefficient cascades. We analyze critical care transfer data in Medicare across nearly 5,000 hospitals in the United States over 10 years and present evidence that these transfers to secondary hospitals repeatedly cascade across multiple transfers, and that some hospitals seem to be involved in many cascades.
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关键词
critical care,medicare claims,administrative data,alerts,cascades,data mining,transfer networks
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