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Natural Language Processing and Inference Rules as Strategies for Updating Problem List in an Electronic Health Record

UNLABELLED
Physicians do not always keep the problem list accurate, complete and updated.


OBJECTIVE
To analyze natural language processing (NLP) techniques and inference rules as strategies to maintain completeness and accuracy of the problem list in EHRs.


METHODS
Non systematic literature review in PubMed, in the last 10 years. Strategies to maintain the EHRs problem list were analyzed in two ways: inputting and removing problems from the problem list.


RESULTS
NLP and inference rules have acceptable performance for inputting problems into the problem list. No studies using these techniques for removing problems were published Conclusion: Both tools, NLP and inference rules have had acceptable results as tools for maintain the completeness and accuracy of the problem list.