Using Natural Language Processing to Classify Serious Illness Communication with Oncology Patients
One core measure of healthcare quality set forth by the Institute of Medicine is whether care decisions match patient goals. High-quality "serious illness communication" about patient goals and prognosis is required to support patient-centered decision-making, however current methods are n...
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Veröffentlicht in: | AMIA ... Annual Symposium proceedings 2022, Vol.2022, p.168-177 |
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Hauptverfasser: | , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | One core measure of healthcare quality set forth by the Institute of Medicine is whether care decisions match patient goals. High-quality "serious illness communication" about patient goals and prognosis is required to support patient-centered decision-making, however current methods are not sensitive enough to measure the quality of this communication or determine whether care delivered matches patient priorities. Natural language processing (NLP) offers an efficient method for identification and evaluation of documented serious illness communication, which could serve as the basis for future quality metrics in oncology and other forms of serious illness. In this study, we trained NLP algorithms to identify and characterize serious illness communication with oncology patients. |
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ISSN: | 2153-4063 2153-4063 1559-4076 |