http://schca-ir.schmc.ac.kr/handle/2022.oak/165 2026-10-22T20:59:35Z 2026-10-22T20:59:35Z Bohyun Kim http://schca-ir.schmc.ac.kr/handle/2022.oak/4948 2025-10-23T06:17:48Z 2024-12-31T15:00:00Z

Title: Does the current apixaban dosing strategy adequately fit and ensure safety in Korean patients with atrial fibrillation? All Author(s): Bohyun Kim Abstract: No abstract available

2024-12-31T15:00:00Z Hyejin Ryu Sumi Sung Kuenyoul Park Min-Sun Kim YeJin Oh Shinae Yu Eun-Jung Cho Sollip Kim http://schca-ir.schmc.ac.kr/handle/2022.oak/4936 2025-09-17T08:04:01Z 2024-12-31T15:00:00Z

Title: Comparative study of LOINC and SNOMED CT in panel mapping: enhancing interoperability in laboratory testing All Author(s): Hyejin Ryu; Sumi Sung; Kuenyoul Park; Min-Sun Kim; YeJin Oh; Shinae Yu; Eun-Jung Cho; Sollip Kim Abstract: Background: We aimed to evaluate and compare the applicability of Logical Observation Identifiers Names and Codes (LOINC) and SNOMED CT in mapping frequently requested panel tests. Method: Frequently requested panel tests were identified from the test records of two major referral laboratories. Subsequently, LOINC and SNOMED CT mappings were cross-validated, and the results were classified based on pre-defined criteria. A consensus was reached among the teams. A comparative structural analysis was performed by aligning the mapped SNOMED CT concepts with LOINC codes and visualizing the selected items with conditionality to evaluate the differences in representation. Results: We conducted 23 panel tests. Exact mapping was achieved for 87.0% of the panel tests using LOINC: two failures were recorded due to the lack of a suitable code, and one panel test was classified as narrowly mapped. In contrast, SNOMED CT achieved the exact mapping for 78.2% of the panel tests, with 12 mappings requiring post-coordination to represent the test concepts. SNOMED CT mapping failures stemmed from missing primitive concepts and limited pre-coordinated codes. LOINC offered detailed component specifications and predefined panel codes. In contrast, SNOMED CT relied on post-coordination to address gaps in the pre-defined codes, allowing the addition of new combinations where necessary. Conclusion: LOINC demonstrated advantages in mapping frequently performed panel tests with higher exact mapping rates and structured panel codes. However, leveraging SNOMED CT's flexibility through initiatives such as the LOINC Ontology project could enhance interoperability and standardization in laboratory data exchange.

2024-12-31T15:00:00Z Tark Kim Yoon-Kyoung Hong Sunghee Park Jongtak Jung Oh-Hyun Cho Hee Bong Shin Tae Youn Choi Young Jin Choi Mi-Na Kim Yong Pil Chong http://schca-ir.schmc.ac.kr/handle/2022.oak/4931 2025-09-10T06:35:29Z 2024-12-31T15:00:00Z

Title: Genetic Epidemiology and Antimicrobial Susceptibilities of Carbapenem-Resistant Pseudomonas aeruginosa Isolates from a Multicenter Study in Korea All Author(s): Tark Kim; Yoon-Kyoung Hong; Sunghee Park; Jongtak Jung; Oh-Hyun Cho; Hee Bong Shin; Tae Youn Choi; Young Jin Choi; Mi-Na Kim; Yong Pil Chong Abstract: Owing to concern that carbapenemase-producing strains among carbapenem-resistant Pseudomonas aeruginosa (CRPA) isolates is on the rise, we investigated the genetic epidemiology and antimicrobial susceptibilities of clinical CRPA isolates collected in four academic hospitals in Korea. Carbapenemase genes were detected in 46 of 63 CRPA isolates (73.0%) collected between 2021 and 2024, and blaNDM ST773 was the most common genotype (27 isolates, 42.9%), followed by blaNDM ST644 (9 isolates, 14.3%) and blaIMP ST235 (7 isolates, 11.1%). Overall susceptibility to ceftazidime/avibactam was only 17.5%, and none of the carbapenemase-producing isolates were susceptible to it. All ST644 strains were also resistant to aztreonam.

2024-12-31T15:00:00Z Kuenyoul Park Min-Sun Kim YeJin Oh John Hoon Rim Shinae Yu Hyejin Ryu Eun-Jung Cho Kyunghoon Lee Ha Nui Kim Inha Chun AeKyung Kwon Sollip Kim Jae-Woo Chung Hyojin Chae Ji Seon Oh Hyung-Doo Park Mira Kang Yeo-Min Yun Jong-Baeck Lim Young Kyung Lee Sail Chun http://schca-ir.schmc.ac.kr/handle/2022.oak/4797 2025-03-14T01:23:46Z 2024-12-31T15:00:00Z

Title: Gaps and Similarities in Research Use LOINC Codes Utilized in Korean University Hospitals: Towards Semantic Interoperability for Patient Care All Author(s): Kuenyoul Park; Min-Sun Kim; YeJin Oh; John Hoon Rim; Shinae Yu; Hyejin Ryu; Eun-Jung Cho; Kyunghoon Lee; Ha Nui Kim; Inha Chun; AeKyung Kwon; Sollip Kim; Jae-Woo Chung; Hyojin Chae; Ji Seon Oh; Hyung-Doo Park; Mira Kang; Yeo-Min Yun; Jong-Baeck Lim; Young Kyung Lee; Sail Chun Abstract: Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests. Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion: This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

2024-12-31T15:00:00Z