2019
DOI: 10.1089/jpm.2018.0326
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Natural Language Processing to Assess End-of-Life Quality Indicators in Cancer Patients Receiving Palliative Surgery

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Cited by 80 publications
(62 citation statements)
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“… 10 Free-text data represent 70% to 80% of all data in EHRs and often provide more contextual information than structured data. 11 , 12 …”
Section: Introductionmentioning
confidence: 99%
“… 10 Free-text data represent 70% to 80% of all data in EHRs and often provide more contextual information than structured data. 11 , 12 …”
Section: Introductionmentioning
confidence: 99%
“…Our NLP software, ClinicalRegex, identifies predefined keywords or phrases within clinical notes, considering varieties in language and punctuation. 80–82 ClinicalRegex also allows for rapid semiautomated review that ensures that keywords have not been taken out of context. For each NLP process (ie, goals-of-care discussion), we have built a keyword library that identifies relevant documentation within clinical notes.…”
Section: Methodsmentioning
confidence: 99%
“…For instance, at one institution, among patients receiving gastrostomy tubes, 90% died in the hospital or were severely disabled on discharge, but only 12% of those patients received a documented goals of care assessment prior to the procedure. Another institution with a 68% rate of documented goals of care discussions in patients undergoing gastrostomy tube placement, only 20% of those discussions occurred pre-procedure (53). Given the risks and discomfort involved in palliative surgical procedures, it is important that goals of care discussions precede any procedural intervention.…”
Section: What Surgeons Can Bring To the Palliative Care Teammentioning
confidence: 99%