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.

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.

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.

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.

Background: Single room isolation with contact precautions is widely regarded as a fundamental strategy to prevent the transmission of multidrug-resistant organisms (MDROs). However, its implementation demands substantial resources, limiting its universal application to all MDROs. In this study, we assessed the effect of discontinuing single room isolation for vancomycin-resistant Enterococcus (VRE). Methods: This is a retrospective, observational study conducted at a single 750-bed tertiary center. We conducted an interrupted time series analysis to compare incidence rates and trends of new-onset VRE colonization and bacteremia during the one year before and after the strategy change on January 1, 2023. Results: Single-room occupancy decreased from 79.7% pre-intervention to 23.6% postintervention (P < 0.001). The incidence rate of new-onset VRE colonization was 0.452 and 0.535 per 1,000 patient-days in the pre- and post-intervention periods, respectively, with no statistically significant difference (P = 0.202). However, there was a slightly increasing trend (0.036 [95% confidence interval, −0.002, 0.074] increase per month, P = 0.066). The new-onset VRE bacteremia incidence rate was not differed in incidence (0.060 and 0.055, P= 0.571) or trend (P = 0.720). Conclusion Our study suggests that discontinuing single-room isolation for VRE patients may not affect the incidence of new-onset VRE bacteremia, but caution is needed due to the potential increase in colonization.

Background: Single room isolation with contact precautions is widely regarded as a fundamental strategy to prevent the transmission of multidrug-resistant organisms (MDROs). However, its implementation demands substantial resources, limiting its universal application to all MDROs. In this study, we assessed the effect of discontinuing single room isolation for vancomycin-resistant Enterococcus (VRE). Methods: This is a retrospective, observational study conducted at a single 750-bed tertiary center. We conducted an interrupted time series analysis to compare incidence rates and trends of new-onset VRE colonization and bacteremia during the one year before and after the strategy change on January 1, 2023. Results: Single-room occupancy decreased from 79.7% pre-intervention to 23.6% postintervention (P < 0.001). The incidence rate of new-onset VRE colonization was 0.452 and 0.535 per 1,000 patient-days in the pre- and post-intervention periods, respectively, with no statistically significant difference (P = 0.202). However, there was a slightly increasing trend (0.036 [95% confidence interval, −0.002, 0.074] increase per month, P = 0.066). The new-onset VRE bacteremia incidence rate was not differed in incidence (0.060 and 0.055, P= 0.571) or trend (P = 0.720). Conclusion Our study suggests that discontinuing single-room isolation for VRE patients may not affect the incidence of new-onset VRE bacteremia, but caution is needed due to the potential increase in colonization.