AMIA Annu Symp Proc - Using natural language processing on the free text of clinical documents to screen for evidence of homelessness among US veterans.

Tópicos

{ record(1888) medic(1808) patient(1693) }
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{ method(2212) result(1239) propos(1039) }
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{ data(2317) use(1299) case(1017) }
{ medic(1828) order(1363) alert(1069) }
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{ group(2977) signific(1463) compar(1072) }
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{ data(3008) multipl(1320) sourc(1022) }
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{ method(1969) cluster(1462) data(1082) }

Resumo

Information retrieval algorithms based on natural language processing (NLP) of the free text of medical records have been used to find documents of interest from databases. Homelessness is a high priority non-medical diagnosis that is noted in electronic medical records of Veterans in Veterans Affairs (VA) facilities. Using a human-reviewed reference standard corpus of clinical documents of Veterans with evidence of homelessness and those without, an open-source NLP tool (Automated Retrieval Console v2.0, ARC) was trained to classify documents. The best performing model based on document level work-flow performed well on a test set (Precision 94%, Recall 97%, F-Measure 96). Processing of a na?ve set of 10,000 randomly selected documents from the VA using this best performing model yielded 463 documents flagged as positive, indicating a 4.7% prevalence of homelessness. Human review noted a precision of 70% for these flags resulting in an adjusted prevalence of homelessness of 3.3% which matches current VA estimates. Further refinements are underway to improve the performance. We demonstrate an effective and rapid lifecycle of using an off-the-shelf NLP tool for screening targets of interest from medical records.

Resumo Limpo

inform retriev algorithm base natur languag process nlp free text medic record use find document interest databas homeless high prioriti nonmed diagnosi note electron medic record veteran veteran affair va facil use humanreview refer standard corpus clinic document veteran evid homeless without opensourc nlp tool autom retriev consol v arc train classifi document best perform model base document level workflow perform well test set precis recal fmeasur process nave set random select document va use best perform model yield document flag posit indic preval homeless human review note precis flag result adjust preval homeless match current va estim refin underway improv perform demonstr effect rapid lifecycl use offtheshelf nlp tool screen target interest medic record

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