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: Very low birth weight infants (VLBWIs) continue to face high mortality risk influenced by the care quality of neonatal intensive care units (NICUs). Under-standing the impact of workload and regional differences on these rates is crucial for improving outcomes.Purpose: This study aimed to assess how the structural and staffing attributes of NICUs influence the mortality rates of VLBWIs, emphasizing the significance of the availability of medical personnel and the regional distribution of care facilities. Methods: Data from 69 Korean NICUs collected by the Korean Neonatal Network between January 2015 and December 2016 were retrospectively analyzed. The NICUs were classified by various parameters: capacity (small, medium, large), nurse-to-bed ratio (1–4), and regional location (A, B, C). Pediatrician staffing was also analyzed and NICUs categorized by beds per pediatrician into low (≤10), medium (11–15), and high (≥16). The NICUs were classified by mortality rates into high-performance (1st and 2nd quartiles) and low-performance (3rd and 4th quartiles). Demographic, perinatal, and neonatal outcomes were analyzed using multivariate logistic regression to explore the association between NICU characteristics and mortality rates. Results: This study included 4,745 VLBWIs (mean gestational age, 28.4 weeks; mean birth weight, 1,088 g; 55.4% male) and found significant variations in survival rates across NICUs linked to performance and staffing levels. High-performing NICUs, often with lower bed-to-staff ratios and advanced care levels, had higher survival rates. Notably, NICUs with 2 rather than 1 neonatologist were associated with reduced mortality rates. The study also underscored regional disparities, with NICUs in certain areas showing less favorable survival rates. Conclusion Adequate NICU staffing and proper facility location are key to lowering the number of VLBWI deaths. Enhancing staffing and regional healthcare equity is crucial for improving the survival of this population.

Background: Very low birth weight infants (VLBWIs) continue to face high mortality risk influenced by the care quality of neonatal intensive care units (NICUs). Under-standing the impact of workload and regional differences on these rates is crucial for improving outcomes.Purpose: This study aimed to assess how the structural and staffing attributes of NICUs influence the mortality rates of VLBWIs, emphasizing the significance of the availability of medical personnel and the regional distribution of care facilities. Methods: Data from 69 Korean NICUs collected by the Korean Neonatal Network between January 2015 and December 2016 were retrospectively analyzed. The NICUs were classified by various parameters: capacity (small, medium, large), nurse-to-bed ratio (1–4), and regional location (A, B, C). Pediatrician staffing was also analyzed and NICUs categorized by beds per pediatrician into low (≤10), medium (11–15), and high (≥16). The NICUs were classified by mortality rates into high-performance (1st and 2nd quartiles) and low-performance (3rd and 4th quartiles). Demographic, perinatal, and neonatal outcomes were analyzed using multivariate logistic regression to explore the association between NICU characteristics and mortality rates. Results: This study included 4,745 VLBWIs (mean gestational age, 28.4 weeks; mean birth weight, 1,088 g; 55.4% male) and found significant variations in survival rates across NICUs linked to performance and staffing levels. High-performing NICUs, often with lower bed-to-staff ratios and advanced care levels, had higher survival rates. Notably, NICUs with 2 rather than 1 neonatologist were associated with reduced mortality rates. The study also underscored regional disparities, with NICUs in certain areas showing less favorable survival rates. Conclusion Adequate NICU staffing and proper facility location are key to lowering the number of VLBWI deaths. Enhancing staffing and regional healthcare equity is crucial for improving the survival of this population.

Background: Very low birth weight infants (VLBWIs) continue to face high mortality risk influenced by the care quality of neonatal intensive care units (NICUs). Under-standing the impact of workload and regional differences on these rates is crucial for improving outcomes.Purpose: This study aimed to assess how the structural and staffing attributes of NICUs influence the mortality rates of VLBWIs, emphasizing the significance of the availability of medical personnel and the regional distribution of care facilities. Methods: Data from 69 Korean NICUs collected by the Korean Neonatal Network between January 2015 and December 2016 were retrospectively analyzed. The NICUs were classified by various parameters: capacity (small, medium, large), nurse-to-bed ratio (1–4), and regional location (A, B, C). Pediatrician staffing was also analyzed and NICUs categorized by beds per pediatrician into low (≤10), medium (11–15), and high (≥16). The NICUs were classified by mortality rates into high-performance (1st and 2nd quartiles) and low-performance (3rd and 4th quartiles). Demographic, perinatal, and neonatal outcomes were analyzed using multivariate logistic regression to explore the association between NICU characteristics and mortality rates. Results: This study included 4,745 VLBWIs (mean gestational age, 28.4 weeks; mean birth weight, 1,088 g; 55.4% male) and found significant variations in survival rates across NICUs linked to performance and staffing levels. High-performing NICUs, often with lower bed-to-staff ratios and advanced care levels, had higher survival rates. Notably, NICUs with 2 rather than 1 neonatologist were associated with reduced mortality rates. The study also underscored regional disparities, with NICUs in certain areas showing less favorable survival rates. Conclusion Adequate NICU staffing and proper facility location are key to lowering the number of VLBWI deaths. Enhancing staffing and regional healthcare equity is crucial for improving the survival of this population.

Background: Very low birth weight infants (VLBWIs) continue to face high mortality risk influenced by the care quality of neonatal intensive care units (NICUs). Under-standing the impact of workload and regional differences on these rates is crucial for improving outcomes.Purpose: This study aimed to assess how the structural and staffing attributes of NICUs influence the mortality rates of VLBWIs, emphasizing the significance of the availability of medical personnel and the regional distribution of care facilities. Methods: Data from 69 Korean NICUs collected by the Korean Neonatal Network between January 2015 and December 2016 were retrospectively analyzed. The NICUs were classified by various parameters: capacity (small, medium, large), nurse-to-bed ratio (1–4), and regional location (A, B, C). Pediatrician staffing was also analyzed and NICUs categorized by beds per pediatrician into low (≤10), medium (11–15), and high (≥16). The NICUs were classified by mortality rates into high-performance (1st and 2nd quartiles) and low-performance (3rd and 4th quartiles). Demographic, perinatal, and neonatal outcomes were analyzed using multivariate logistic regression to explore the association between NICU characteristics and mortality rates. Results: This study included 4,745 VLBWIs (mean gestational age, 28.4 weeks; mean birth weight, 1,088 g; 55.4% male) and found significant variations in survival rates across NICUs linked to performance and staffing levels. High-performing NICUs, often with lower bed-to-staff ratios and advanced care levels, had higher survival rates. Notably, NICUs with 2 rather than 1 neonatologist were associated with reduced mortality rates. The study also underscored regional disparities, with NICUs in certain areas showing less favorable survival rates. Conclusion Adequate NICU staffing and proper facility location are key to lowering the number of VLBWI deaths. Enhancing staffing and regional healthcare equity is crucial for improving the survival of this population.

The initial treatment for differentiated thyroid cancer includes appropriate surgery and radioactive iodine (RAI) therapy, followed by thyroid-stimulating hormone (TSH) suppression therapy as long-term management to prevent recurrence. RAI therapy following thyroidectomy has the three main purposes: remnant ablation, adjuvant therapy, and therapy for known disease. To optimize the goals and targets of RAI therapy, postoperative disease assessment, determination of recurrence risk, and consideration of various individual factors are necessary. The objectives of RAI therapy are determined based on the individual’s recurrence risk, and the administered activity of RAI is then determined according to these treatment objectives. Adequate stimulation of serum TSH is necessary before RAI therapy, and recombinant human TSH is widely used because of its advantage in reducing the risk of exacerbation of comorbidities associated with levothyroxine discontinuation and improving patients’ quality of life. Additionally, reducing iodine intake through appropriate low-iodine diet is necessary. Whole-body scans are conducted to assess the disease status after RAI therapy. If planar whole-body scans are inconclusive, additional single-photon emission computed tomography (SPECT)/CT imaging is recommended. Over the past decade, prospective randomized or retrospective clinical studies on the selection of candidates for RAI therapy, administered activity, methods of TSH stimulation, and advantages of SPECT/CT have been published. Based on these latest clinical research findings and recommendations from relevant overseas medical societies, this clinical practice guideline presents the indications and methods for administering RAI therapy after thyroidectomy.

Based on the clinical, histopathological, and perioperative data of a patient with differentiated thyroid cancer (DTC), risk stratification based on their initial recurrence risk is a crucial follow-up (FU) strategy during the first 1–2 years after initial therapy. However, restratifiying the recurrence risk on the basis of current clinical data that becomes available after considering the response to treatment (ongoing risk stratification, ORS) provides a more accurate prediction of the status at the final FU and a more tailored management approach. Since the 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and DTC, the latest guidelines that include the National Comprehensive Cancer Network clinical practice and European Association for Medical Oncology guidelines have been updated to reflect several recent evidence in ORS and thyroid-stimulating hormone (TSH) suppression of DTC. The current clinical practice guideline was developed by extracting FU surveillance after the initial treatment section from the previous version of guidelines and updating it to reflect recent evidence. The current revised guideline includes recommendations for recent ORS, TSH target level based on risk stratification, FU tools for detection of recurrence and assessment of disease status, and long-term FU strategy for consideration of the disease status. These evidence-based recommendations are expected to avoid overtreatment and intensive FU of the majority of patients who will have a very good prognosis after the initial treatment of DTC patients, thereby ensuring that patients receive the most appropriate and effective treatment and FU options.