A new paradigm for accelerating clinical data science at Stanford\n Medicine

Le résumé fourni par la source

Stanford Medicine is building a new data platform for our academic research\ncommunity to do better clinical data science. Hospitals have a large amount of\npatient data and researchers have demonstrated the ability to reuse that data\nand AI approaches to derive novel insights, support patient care, and improve\ncare quality. However, the traditional data warehouse and Honest Broker\napproaches that are in current use, are not scalable. We are establishing a new\nsecure Big Data platform that aims to reduce time to access and analyze data.\nIn this platform, data is anonymized to preserve patient data privacy and made\navailable preparatory to Institutional Review Board (IRB) submission.\nFurthermore, the data is standardized such that analysis done at Stanford can\nbe replicated elsewhere using the same analytical code and clinical concepts.\nFinally, the analytics data warehouse integrates with a secure data science\ncomputational facility to support large scale data analytics. The ecosystem is\ndesigned to bring the modern data science community to highly sensitive\nclinical data in a secure and collaborative big data analytics environment with\na goal to enable bigger, better and faster science.\n

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