-
cmext.ahrq.gov/confluence/download/export/pdfexport-20230731-310723-2103-503/114990887_2c59017dcb494875949c2bc5fbce2fb9-310723-2103-504.pdf?contentType=application/pdf
September 01, 2020 - providers for care coordination, in the most user-friendly and intuitive ways possible
And requires hospitals … Hospital improvement
innovation networks (HIINs) working with 4,000 acute care hospitals across the … nation have generated a 13 percent reduction in the number of
hospital acquired conditions between 2014 … demonstrate how AI tools, such as deep learning and neural networks, can be
used to predict unplanned hospital … N3C will enable the rapid collection and analysis of clinical,
laboratory, and diagnostic data from hospitals
-
cmext.ahrq.gov/confluence/download/export/downloadb6ZH1015505.zip?contentType=application/zip
September 01, 2022 - Individual is discharged from Hospital to SNF. … Data shared as care transitions from Hospital to SNF, then to home. … DEL) (Community Based Organization)
David Hill The MITRE Corporation Hospital EHR SNF EHR Home Health … Most acute hospital sites sent electronic clinical data (e.g., problems, orders, allergies, medications … DEL) (Community Based Organization)
David Hill The MITRE Corporation Hospital EHR SNF EHR Home Health
-
cmext.ahrq.gov/confluence/pages/viewpage.action?pageId=114991610
September 20, 2021 - providers for care coordination, in the most user-friendly and intuitive ways possible And requires hospitals … Hospital improvement innovation networks (HIINs) working with 4,000 acute care hospitals across the nation … have generated a 13 percent reduction in the number of hospital acquired conditions between 2014 and … demonstrate how AI tools, such as deep learning and neural networks, can be used to predict unplanned hospital … N3C will enable the rapid collection and analysis of clinical, laboratory, and diagnostic data from hospitals
-
cmext.ahrq.gov/confluence/pages/diffpages.action?originalId=114991733&pageId=114991610
September 20, 2021 - providers for care coordination, in the most user-friendly and intuitive ways possible And requires hospitals … Hospital improvement innovation networks (HIINs) working with 4,000 acute care hospitals across the nation … have generated a 13 percent reduction in the number of hospital acquired conditions between 2014 and … demonstrate how AI tools, such as deep learning and neural networks, can be used to predict unplanned hospital … N3C will enable the rapid collection and analysis of clinical, laboratory, and diagnostic data from hospitals
-
cmext.ahrq.gov/confluence/pages/diffpages.action?originalId=114991732&pageId=114991733
September 20, 2021 - providers for care coordination, in the most user-friendly and intuitive ways possible And requires hospitals … Hospital improvement innovation networks (HIINs) working with 4,000 acute care hospitals across the nation … have generated a 13 percent reduction in the number of hospital acquired conditions between 2014 and … demonstrate how AI tools, such as deep learning and neural networks, can be used to predict unplanned hospital … N3C will enable the rapid collection and analysis of clinical, laboratory, and diagnostic data from hospitals
-
cmext.ahrq.gov/confluence/pages/diffpages.action?originalId=114992885&pageId=114990887
October 14, 2021 - providers for care coordination, in the most user-friendly and intuitive ways possible And requires hospitals … Hospital improvement innovation networks (HIINs) working with 4,000 acute care hospitals across the nation … have generated a 13 percent reduction in the number of hospital acquired conditions between 2014 and … demonstrate how AI tools, such as deep learning and neural networks, can be used to predict unplanned hospital … N3C will enable the rapid collection and analysis of clinical, laboratory, and diagnostic data from hospitals
-
cmext.ahrq.gov/confluence/pages/viewpage.action?pageId=114991727
September 09, 2021 - providers for care coordination, in the most user-friendly and intuitive ways possible And requires hospitals … Hospital improvement innovation networks (HIINs) working with 4,000 acute care hospitals across the nation … have generated a 13 percent reduction in the number of hospital acquired conditions between 2014 and … demonstrate how AI tools, such as deep learning and neural networks, can be used to predict unplanned hospital … N3C will enable the rapid collection and analysis of clinical, laboratory, and diagnostic data from hospitals
-
cmext.ahrq.gov/confluence/pages/viewpage.action?pageId=114991733
September 20, 2021 - providers for care coordination, in the most user-friendly and intuitive ways possible And requires hospitals … Hospital improvement innovation networks (HIINs) working with 4,000 acute care hospitals across the nation … have generated a 13 percent reduction in the number of hospital acquired conditions between 2014 and … demonstrate how AI tools, such as deep learning and neural networks, can be used to predict unplanned hospital … N3C will enable the rapid collection and analysis of clinical, laboratory, and diagnostic data from hospitals
-
cmext.ahrq.gov/confluence/pages/viewpage.action?pageId=114991732
September 20, 2021 - providers for care coordination, in the most user-friendly and intuitive ways possible And requires hospitals … Hospital improvement innovation networks (HIINs) working with 4,000 acute care hospitals across the nation … have generated a 13 percent reduction in the number of hospital acquired conditions between 2014 and … demonstrate how AI tools, such as deep learning and neural networks, can be used to predict unplanned hospital … N3C will enable the rapid collection and analysis of clinical, laboratory, and diagnostic data from hospitals
-
cmext.ahrq.gov/confluence/download/export/pdfexport-20230802-020823-0057-1997/Why+ACTS+-+the+Urgent+Challenge_ed9103438d5f44698235bd52270f9948-020823-0057-1998.pdf?contentType=application/pdf
January 01, 1998 - created
and deployed (e.g., across patients, care teams, resource developers, insurance providers, hospitals
-
cmext.ahrq.gov/confluence/download/export/pdfexport-20230322-220323-2004-2235/Project+Kick-off+Meeting+Materia_d871741d36a94e90a537b70acdda4f70-220323-2004-2236.pdf?contentType=application/pdf
January 01, 2004 - Sc., R.N., FACMI, Brigham and Women's
Hospital/Harvard University
(PPTX, 13.9 MB)
02 Oct
2019
-
cmext.ahrq.gov/confluence/download/export/pdfexport-20230322-220323-2007-2239/Project+Kick-off+Meeting+Materia_ae6f2bf468034f1ea00a075476620463-220323-2007-2240.pdf?contentType=application/pdf
January 01, 2007 - Sc., R.N., FACMI, Brigham and Women's
Hospital/Harvard University
(PPTX, 13.9 MB)
02 Oct
2019
-
cmext.ahrq.gov/confluence/download/export/pdfexport-20230322-220323-2010-2243/Project+Kick-off+Meeting+Materia_4c529058f28649d3ba92935b6c75f1f7-220323-2010-2244.pdf?contentType=application/pdf
January 01, 2010 - Sc., R.N., FACMI, Brigham and Women's
Hospital/Harvard University
(PPTX, 13.9 MB)
02 Oct
2019
-
cmext.ahrq.gov/confluence/download/export/pdfexport-20230322-220323-2012-2245/Project+Kick-off+Meeting+Materia_9d4aeb9ee2c24dc4be0db535bf9855b4-220323-2012-2246.pdf?contentType=application/pdf
January 01, 2012 - Sc., R.N., FACMI, Brigham and Women's
Hospital/Harvard University
(PPTX, 13.9 MB)
02 Oct
2019
-
cmext.ahrq.gov/confluence/download/export/pdfexport-20230322-220323-2000-2231/Project+Kick-off+Meeting+Materia_8566aab6f04a492bbc637566f6fde095-220323-2000-2232.pdf?contentType=application/pdf
January 01, 2000 - Sc., R.N., FACMI, Brigham and Women's
Hospital/Harvard University
(PPTX, 13.9 MB)
02 Oct
2019
-
cmext.ahrq.gov/confluence/download/export/pdfexport-20230322-220323-2002-2233/Project+Kick-off+Meeting+Materia_002525b904514f42aea8d0116ee7b5d8-220323-2002-2234.pdf?contentType=application/pdf
January 01, 2002 - Sc., R.N., FACMI, Brigham and Women's
Hospital/Harvard University
(PPTX, 13.9 MB)
02 Oct
2019
-
cmext.ahrq.gov/confluence/download/export/pdfexport-20230322-220323-2005-2237/Project+Kick-off+Meeting+Materia_8e078aa9e32f45ab88a7527bfd287024-220323-2005-2238.pdf?contentType=application/pdf
January 01, 2005 - Sc., R.N., FACMI, Brigham and Women's
Hospital/Harvard University
(PPTX, 13.9 MB)
02 Oct
2019
-
cmext.ahrq.gov/confluence/download/export/pdfexport-20230322-220323-2008-2241/Project+Kick-off+Meeting+Materia_77013a1bd0ff435d94524a30002564bb-220323-2008-2242.pdf?contentType=application/pdf
January 01, 2008 - Sc., R.N., FACMI, Brigham and Women's
Hospital/Harvard University
(PPTX, 13.9 MB)
02 Oct
2019
-
cmext.ahrq.gov/confluence/download/export/pdfexport-20230322-220323-2013-2247/Project+Kick-off+Meeting+Materia_637979d30f104cedb7160c0d1976ce56-220323-2013-2248.pdf?contentType=application/pdf
January 01, 2013 - Sc., R.N., FACMI, Brigham and Women's
Hospital/Harvard University
(PPTX, 13.9 MB)
02 Oct
2019
-
cmext.ahrq.gov/confluence/download/temp/pdfexport-20230227-270223-2014-509/114990887_688d78ef73a2427e9d869b05dac7ea24-270223-2014-510.pdf?contentType=application/pdf
January 01, 2014 - providers for care coordination, in the most user-friendly and intuitive ways possible
And requires hospitals … Hospital improvement
innovation networks (HIINs) working with 4,000 acute care hospitals across the … nation have generated a 13 percent reduction in the number of
hospital acquired conditions between 2014 … demonstrate how AI tools, such as deep learning and neural networks, can be
used to predict unplanned hospital … N3C will enable the rapid collection and analysis of clinical,
laboratory, and diagnostic data from hospitals