PubMed · 14574181
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Mary G Heinen, Geraldine A Coyle, April V Hamilton. 2003. Barcoding makes its mark on daily practice.. https://pubmed.ncbi.nlm.nih.gov/14574181/
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OBJECTIVES: We present in this article experiments on multi-language information extraction and access in the medical domain. For such applications, multilingual terminology plays a crucial role when working on specialized languages and specific domains. MATERIAL AND METHODS: We propose firstly a method for enriching multilingual thesauri which extracts new terms from parallel corpora, and secondly, a new approach for bilingual lexicon extraction from comparable corpora, which uses a bilingual thesaurus as a pivot. We illustrate their use in multi-language information retrieval (English/German) in the medical domains. RESULTS: Our experiments show that these automatically extracted bilingual lexicons are accurate enough (85% precision for term extraction) for semi-automatically enriching mono- or bi-lingual thesauri such as the universal medical language system, and that their use in cross-language information retrieval significantly improves the retrieval performance (from 22 to 40% average precision) and clearly outperforms existing bilingual lexicon resources (both general lexicons and specialized ones). CONCLUSION: We show in this paper first that bilingual lexicon extraction from parallel corpora in the medical domain could lead to accurate, specialized lexicons, which can be used to help enrich existing thesauri and second that bilingual lexicons extracted from comparable corpora outperform general bilingual resources for cross-language information retrieval.
Extraction of relevant information from free-text clinical notes is becoming increasingly important in healthcare to provide personalized care to patients. The purpose of this dictionary-based NLP study was to determine the effects of using varying drug lexicons to automatically extract medication information from electronic medical records. A convenience training sample of 52 documents, each containing at least one medication, and a randomized test sample of 100 documents were used in this study. The training and test set documents contained a total of 681 and 641 medications respectively. Three sets of drug lexicons were used as sources for medication extraction: first, containing drug name and generic name; second with drug, generic and short names; third with drug, generic and short names followed by filtering techniques. Extraction with the first drug lexicon resulted in 83.7% sensitivity and 96.2% specificity for the training set and 85.2% sensitivity and 96.9% specificity for the test set. Adding the list of short names used for drugs resulted in increasing sensitivity to 95.0%, but decreased the specificity to 79.2% for the training set. Similar results of increased sensitivity of 96.4% and 80.1% specificity were obtained for the test set. Combination of a set of filtering techniques with data from the second lexicon increased the specificity to 98.5% and 98.8% for the training and test sets respectively while slightly decreasing the sensitivity to 94.1% (training) and 95.8% (test). Overall, the lexicon with filtering resulted in the highest precision, i.e., extracted the highest number of medications while keeping the number of extracted non-medications low.
OBJECTIVE: Data from the Veterans Health Administration (VHA) were used to evaluate the strengths and weaknesses of the Global Assessment of Functioning (GAF), a single-item mental health status measure, as an outcome measure for large mental health care systems. METHODS: The sample consisted of VHA mental health patients who had at least two GAF scores 45 days apart in 2002 (N=283,754). First, to evaluate the discriminant validity of the GAF change measures, the authors examined the association of these measures with sociodemographic and clinical characteristics. Facility-level risk-adjusted measures of GAF change were then created in three different clinical samples at more than 130 VHA medical centers, adjusting for patients' sociodemographic characteristics and diagnoses. The internal consistency of the scale created by using these items and their consistency across medical centers over time was evaluated. RESULTS: The analysis supported the discriminant validity of the GAF-derived measures. As expected, veterans who had a diagnosis of schizophrenia or Alzheimer's disease or who had service-connected disability ratings above 50 percent had lower baseline GAF scores and showed less improvement. The overall GAF performance measure had a high level of internal consistency (a standardized alpha of .85) and was highly consistent across facilities over time. CONCLUSIONS: The results of this study provide preliminary empirical support for cautious use of a GAF-derived scale in monitoring changes in average facility-level outcomes over time. However, because of the potential for gaming of the measures and uncontrolled variation in the scale's administration across facilities, the scale should not be used to compare outcomes across facilities.