Exploring the Ability of Natural Language Processing to Extract Data From Nursing Narratives

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Abstract

Natural Language Processing (NLP) offers an approach for capturing data from narratives and creating structured reports for further computer processing. We explored the ability of a NLP system, Medical Language Extraction and Encoding (MedLEE), on nursing narratives. MedLEE extracted 490 concepts from narrative text in a sample of 553 oncology nursing process notes. The most frequently monitored and recorded signs and symptoms were related to chemotherapy care, such as adverse reactions, shortness of breath, nausea, pain, and bleeding. In terms of nursing interventions, chemotherapy, blood culture, medication, and blood transfusion were commonly recorded in free text. NLP may provide a feasible approach to extract data related to patient safety/quality measures and nursing outcomes by capturing nursing concepts that are not recorded through structured data entry. For better NLP performance in the domain of nursing, additional nursing terms and abbreviations must be added to MedLEE's lexicon.

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