Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

The age- and sex-related differences on the impacts of body composition on diabetes mellitus (DM) remain uncertain.

The age- and sex-related differences on the impacts of body composition on diabetes mellitus (DM) remain uncertain.

Point-of-care ultrasound (POCUS) is a useful tool that is widely used in the emergency and intensive care areas. In Korea, insurance coverage of ultrasound examination has been gradually expanding in accordance with measures to enhance Korean National Insurance Coverage since 2017 to 2021, and which will continue until 2021. Full coverage of health insurance for POCUS in the emergency and critical care areas was implemented in July 2019. The National Health Insurance Act classified POCUS as a single or multiple-targeted ultrasound examination (STU vs. MTU). STU scans are conducted of one organ at a time, while MTU includes scanning of multiple organs simultaneously to determine each clinical situation. POCUS can be performed even if a diagnostic ultrasound examination is conducted, based on the physician's decision. However, the Health Insurance Review and Assessment Service plans to monitor the prescription status of whether the POCUS and diagnostic ultrasound examinations are prescribed simultaneously and repeatedly. Additionally, MTU is allowed only in cases of trauma, cardiac arrest, shock, chest pain, and dyspnea and should be performed by a qualified physician. Although physicians should scan all parts of the chest, heart, and abdomen when they prescribe MTU, they are not required to record all findings in the medical record. Therefore, appropriate prescription, application, and recording of POCUS are needed to enhance the quality of patient care and avoid unnecessary cut of medical budget spending. The present article provides background and clinical guidance for POCUS based on the implementation of full health insurance coverage for POCUS that began in July 2019 in Korea.

Background: The age- and sex-related differences on the impacts of body composition on diabetes mellitus (DM) remain uncertain. Methods: The fourth and fifth Korea National Health and Nutrition Examination Survey included 15,586 subjects over 30 years of age who completed dual-energy X-ray absorptiometry. We conducted a cross-sectional study to investigate whether muscle mass index (MMI), defined as appendicular skeletal muscle divided by body mass index (BMI), and fat mass index (FMI), defined as trunk fat mass divided by BMI, were differently associated with DM according to age and sex. Results: In multivariate logistic regression, the risk for DM significantly increased across quartiles of FMI in men aged ≥70.Meanwhile, MMI showed a protective association with DM in men of the same age. The odds ratios (ORs) for the highest quartile versus the lowest quartile of FMI and MMI were 3.116 (95% confidence interval [CI], 1.405 to 6.914) and 0.295 (95% CI, 0.157 to 0.554), respectively. In women, the ORs of DM was significantly different across FMI quartiles in those over age 50. The highest quartile of FMI exhibited increased ORs of DM in subjects aged 50 to 69 (OR, 1.891; 95% CI, 1.229 to 2.908) and ≥70 (OR, 2.275;95% CI, 1.103 to 4.69) compared to lowest quartile. However, MMI was not significantly associated with DM in women of all age groups. Conclusion Both FMI and MMI were independent risk factors for DM in men aged 70 years or more. In women over 50 years, FMI was independently associated with DM. There was no significant association between MMI and DM in women.

Point-of-care ultrasound (POCUS) is a useful tool that is widely used in the emergency and intensive care areas. In Korea, insurance coverage of ultrasound examination has been gradually expanding in accordance with measures to enhance Korean National Insurance Coverage since 2017 to 2021, and which will continue until 2021. Full coverage of health insurance for POCUS in the emergency and critical care areas was implemented in July 2019. The National Health Insurance Act classified POCUS as a single or multiple-targeted ultrasound examination (STU vs. MTU). STU scans are conducted of one organ at a time, while MTU includes scanning of multiple organs simultaneously to determine each clinical situation. POCUS can be performed even if a diagnostic ultrasound examination is conducted, based on the physician's decision. However, the Health Insurance Review and Assessment Service plans to monitor the prescription status of whether the POCUS and diagnostic ultrasound examinations are prescribed simultaneously and repeatedly. Additionally, MTU is allowed only in cases of trauma, cardiac arrest, shock, chest pain, and dyspnea and should be performed by a qualified physician. Although physicians should scan all parts of the chest, heart, and abdomen when they prescribe MTU, they are not required to record all findings in the medical record. Therefore, appropriate prescription, application, and recording of POCUS are needed to enhance the quality of patient care and avoid unnecessary cut of medical budget spending. The present article provides background and clinical guidance for POCUS based on the implementation of full health insurance coverage for POCUS that began in July 2019 in Korea.
Abdomen ; Budgets ; Chest Pain ; Critical Care ; Dyspnea ; Emergencies ; Heart ; Heart Arrest ; Insurance Coverage ; Insurance ; Insurance, Health ; Korea ; Medical Records ; National Health Programs ; Patient Care ; Point-of-Care Systems ; Prescriptions ; Shock ; Thorax ; Ultrasonography