PURPOSE: The purpose of this study was to analyze the equality between author key words used in the Journal of the Korean Orthopaedic Association and controlled vocabulary or medical subject headings (MeSH). MATERIALS AND METHODS: A total of 1,058 English key words in 320 papers (average 3.3 words in a paper) from 2009 to 2012 were eligible for this study. We classified them according to matched, partially matched, and non-matched terms. The partially matched terms were further dissected into entry terms, qualifiers, anteriorly or posteriorly matched, abbreviations, and pleurals. After descriptive analysis, we assayed patterns of errors in using MeSH, and reviewed frequently used non-MeSH terms. RESULTS: The rate of matched terms was 23.5% for an average of four years, and 34.8% for 2013, which is on the rise by year. The rate of partially matched terms was 34.8%, and that of non-matched terms was 41.7% for an average of four years. The most frequently used key words were Knee and Total knee arthroplasty (17 times), followed by Osteoarthritis (9), Femur, Hip, and Total hip arthroplasty (8). CONCLUSION: Use of proper keywords aligned with the international standards such as MeSH is important to be properly cited. The authors should pay attention and be educated on correct use of MeSH as key words.
Arthroplasty ; Arthroplasty, Replacement, Hip ; Femur ; Hip ; Knee ; Medical Subject Headings* ; Orthopedics ; Osteoarthritis ; Vocabulary, Controlled

OBJECTIVES: In this study, we proposed an algorithm for mapping standard terminologies for the automated generation of medical bills. As the Korean and American structures of health insurance claim codes for laboratory tests are similar, we used Current Procedural Terminology (CPT) instead of the Korean health insurance code set due to the advantages of mapping in the English language. METHODS: 1,149 CPT codes for laboratory tests were chosen for study. Each CPT code was divided into two parts, a Logical Observation Identifi ers Names and Codes (LOINC) matched part (matching part) and an unmatched part (unmatched part). The matching parts were assigned to LOINC axes. An ontology set was designed to express the unmatched parts, and a mapping strategy with Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) was also proposed. Through the proceeding analysis, an algorithm for mapping CPT with SNOMED CT arranged by LOINC was developed. RESULTS: 75% of the 1,149 CPT codes could be assigned to LOINC codes. Two hundred and twenty-five CPT codes had only one component part of LOINC, whereas others had more than two parts of LOINC. The system of LOINC axes was found in 309 CPT codes, scale 555, property 9, method 42, and time aspect 4. From the unmatched parts, three classes, 'types', 'objects', and 'subjects', were determined. By determining the relationship between the classes with several properties, all unmatched parts could be described. Since the 'subject to' class was strongly connected to the six axes of LOINC, links between the matching parts and unmatched parts were made. CONCLUSIONS: The proposed method may be useful for translating CPT into concept-oriented terminology, facilitating the automated generation of medical bills, and could be adapted for the Korean health insurance claim code set.
Current Procedural Terminology ; Insurance, Health ; Logic ; Logical Observation Identifiers Names and Codes ; Systematized Nomenclature of Medicine ; Translating

Medical Subject Headings (MeSH), a medical thesaurus created by the National Library of Medicine (NLM), is a useful resource for natural language processing (NLP). In this article, the current status of the Japanese version of Medical Subject Headings (MeSH) is reviewed. Online investigation found that Japanese-English dictionaries, which assign MeSH information to applicable terms, but use them for NLP, were found to be difficult to access, due to license restrictions. Here, we investigate an open-source Japanese-English glossary as an alternative method for assigning MeSH IDs to Japanese terms, to obtain preliminary data for NLP proof-of-concept.
Asian Continental Ancestry Group ; Humans ; Licensure ; Medical Subject Headings ; Methods ; National Library of Medicine (U.S.) ; Natural Language Processing ; Vocabulary, Controlled

OBJECTIVES: Efficient identification of subject experts or expert communities is vital for the growth of any organization. Most of the available expert finding systems are based on self-nomination, which can be biased, and are unable to rank experts. Thus, the objective of this work was to develop a robust and unbiased expert finding system which can quantitatively measure expertise. METHODS: Medical Subject Headings (MeSH) is a controlled vocabulary developed by the National Library of Medicine (NLM) for indexing research publications, articles and books. Using the MeSH terms associated with peer-reviewed articles published from India and indexed in PubMed, we developed a Web-based program which can be used to identify subject experts and subjects associated with an expert. RESULTS: We have extensively tested our system to identify experts from India in various subjects. The system provides a ranked list of experts where known experts rank at the top of the list. The system is general; since it uses information available with the PubMed, it can be implemented for any country. CONCLUSIONS: The expert finding system is able to successfully identify subject experts in India. Our system is unique because it allows the quantification of subject expertise, thus enabling the ranking of experts. Our system is based on peer-reviewed information. Use of MeSH terms as subjects has standardized the subject terminology. The system matches requirements of an ideal expert finding system.
Abstracting and Indexing as Topic ; Bias (Epidemiology) ; Data Mining ; Expert Systems ; India ; Medical Subject Headings* ; National Library of Medicine (U.S.) ; Online Systems ; Professional Competence ; Vocabulary, Controlled

PURPOSE: The purpose of this study was to analyze how accurately authors of the Journal of Korean Academy of Fundamentals of Nursing used MeSH terms as key words. METHOD: A total of 724 key words used in the 225 papers of Journal of Korean Academy of Fundamentals of Nursing from 2003 to 2007 were compared with MeSH terms. RESULTS: Fifty nine point eight percent of total key words were completely coincident with MeSH terms, 13.5% were entry terms, and 21.8% were not MeSH terms. The coincidence rates for 2003 and 2007 separately were 38.5% and 70.9%. Also, 25.3% of papers precisely used MeSH terms as key words and 8% did not use any MeSH terms. CONCLUSION: The results show that the coincidence rate of key words with MeSH terms was at a moderate level and gradually increased according to year. However, there is a need for us to understand MeSH more specifically and accurately.
Medical Subject Headings

OBJECTIVES: This study developed an integrated database for 15 regional biobanks that provides large quantities of high-quality bio-data to researchers to be used for the prevention of disease, for the development of personalized medicines, and in genetics studies. METHODS: We collected raw data, managed independently by 15 regional biobanks, for database modeling and analyzed and defined the metadata of the items. We also built a three-step (high, middle, and low) classification system for classifying the item concepts based on the metadata. To generate clear meanings of the items, clinical items were defined using the Systematized Nomenclature of Medicine Clinical Terms, and specimen items were defined using the Logical Observation Identifiers Names and Codes. To optimize database performance, we set up a multi-column index based on the classification system and the international standard code. RESULTS: As a result of subdividing 7,197,252 raw data items collected, we refined the metadata into 1,796 clinical items and 1,792 specimen items. The classification system consists of 15 high, 163 middle, and 3,588 low class items. International standard codes were linked to 69.9% of the clinical items and 71.7% of the specimen items. The database consists of 18 tables based on a table from MySQL Server 5.6. As a result of the performance evaluation, the multi-column index shortened query time by as much as nine times. CONCLUSIONS: The database developed was based on an international standard terminology system, providing an infrastructure that can integrate the 7,197,252 raw data items managed by the 15 regional biobanks. In particular, it resolved the inevitable interoperability issues in the exchange of information among the biobanks, and provided a solution to the synonym problem, which arises when the same concept is expressed in a variety of ways.
Biological Specimen Banks ; Classification ; Data Collection ; Genetics ; Korea* ; Logical Observation Identifiers Names and Codes ; Precision Medicine ; Systematized Nomenclature of Medicine

OBJECTIVES: This study developed an integrated database for 15 regional biobanks that provides large quantities of high-quality bio-data to researchers to be used for the prevention of disease, for the development of personalized medicines, and in genetics studies. METHODS: We collected raw data, managed independently by 15 regional biobanks, for database modeling and analyzed and defined the metadata of the items. We also built a three-step (high, middle, and low) classification system for classifying the item concepts based on the metadata. To generate clear meanings of the items, clinical items were defined using the Systematized Nomenclature of Medicine Clinical Terms, and specimen items were defined using the Logical Observation Identifiers Names and Codes. To optimize database performance, we set up a multi-column index based on the classification system and the international standard code. RESULTS: As a result of subdividing 7,197,252 raw data items collected, we refined the metadata into 1,796 clinical items and 1,792 specimen items. The classification system consists of 15 high, 163 middle, and 3,588 low class items. International standard codes were linked to 69.9% of the clinical items and 71.7% of the specimen items. The database consists of 18 tables based on a table from MySQL Server 5.6. As a result of the performance evaluation, the multi-column index shortened query time by as much as nine times. CONCLUSIONS: The database developed was based on an international standard terminology system, providing an infrastructure that can integrate the 7,197,252 raw data items managed by the 15 regional biobanks. In particular, it resolved the inevitable interoperability issues in the exchange of information among the biobanks, and provided a solution to the synonym problem, which arises when the same concept is expressed in a variety of ways.
Biological Specimen Banks ; Classification ; Data Collection ; Genetics ; Korea* ; Logical Observation Identifiers Names and Codes ; Precision Medicine ; Systematized Nomenclature of Medicine

Medical vocabularies in medical records are used in several synonyms and various expressions even though they are same concepts. Query expansion using a thesaurus enhances recall of medical information retrieval (IR) system for searching patient records or literatures. This study proposed IR system architecture applied the Metathesaurus of Unified Medical Language System (UMLS). To enhance the retrieval effectiveness at the same time to reduce retrieval time, we reconstructed condensed Metathesaurus (CMT), which is constituted of frequently used terms in medical records. We used 40,000 radiology reports of Brain CT/MRI at Seoul National University Hospital. The retrieval model we used is the Boolean methods. The results showed 15~27% effectiveness for searching relevant documents implementing the UMLS MT into IR system for query expansion. But it took 3.5 times longer for retrieval compared with non-MT implemented IR system. When we applied the CMT into IR system, however, the retrieval time reduced by 50% and the retrieval performance decreased only 8.7% compared with all MT implemented IR system. In this paper, we developed the medical document retrieval system applied UMLS MT for query expansion methods that can improve the relevant document retrieval performance, at the same time it can reduce the retrieval time through consisting condensed Metathesaurus for a specific domain.
Brain ; Computing Methodologies ; Humans ; Information Storage and Retrieval* ; Medical Records ; Seoul ; Unified Medical Language System* ; Vocabulary ; Vocabulary, Controlled

PURPOSE: The purpose of this study was to examine the evidence of programmatic and teaching initiatives implemented by nursing faculty to enhance the academic success rates of ethnically diverse students (EDS). METHODS: A search of the literature in the Cumulative Index to Nursing and Allied Health Literature and MEDLINE databases, wherein primary sources about programmatic and teaching initiative to promote academic success among EDS, was conducted. Using specific the Cumulative Index to Nursing and Allied Health Literature subject headings and Medical Subject Headings, 230 articles were retrieved from both databases. A total of 22 peer-reviewed articles published between 2000 and 2011 were included in the literature review. RESULTS: We found that evidence on the predominant programmatic and teaching initiatives for EDS academic success was inconclusive. The most common programmatic and teaching initiatives implemented by nursing faculty were peer mentoring, faculty-student mentoring, social networking, academic support, and financial support. CONCLUSION: Although positive student outcomes were reported about programmatic and teaching initiatives for EDS, the evidence remained inconclusive. Recommendations for policy and future research in this area of nursing education research were provided.
Achievement ; Faculty, Nursing ; Humans ; Medical Subject Headings ; Mentors ; Minority Groups ; Nursing Education Research ; Subject Headings

OBJECTIVES: The purpose of this study is to explore possibility of information sharing between the medical and nursing domains. METHODS: Narrative medical records of 281 hospitalization days of 36 gastrectomy patients were decomposed into single-meaning statements. These single-meaning statements were combined into unique statements by removing semantically redundant statements. Concepts from the statements describing patients' problem and medical procedures were mapped to Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) and International Classification for Nursing Practice (ICNP) concepts. RESULTS: A total 4,717 single-meaning statements were collected and these single-meaning statements were combined into 858 unique statements. Out of 677 unique statements describing patients' problems and medical procedures, about 85.5% statements were fully mapped to SNOMED CT. The remaining statements were partially mapped. In the mapping to the ICNP concepts, 17.4% of unique statements were fully mapped, 62.8% were partially mapped, and 19.8% were not mapped. About 32.3% of 705 concepts extracted from the statements were mapped to both SNOMED CT and ICNP concepts. CONCLUSIONS: These mapping results suggest that physicians' narrative medical records can be structured and can be used for electronic medical record system, and also it is possible for medicine and nursing to share patient care information.
Electronic Health Records ; Gastrectomy ; Hospitalization ; Humans ; Information Dissemination ; Information Management ; Medical Records ; Patient Care ; Systematized Nomenclature of Medicine ; Vocabulary, Controlled