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Data resource profile: the allergic disease database of the Korean National Health Insurance Service
Sunyong Yoo, Dong-Wook Kim, Young-Eun Kim, Jong Heon Park, Yeon-Yong Kim, Kyu-dong Cho, Mi-Ji Gwon, Jae-In Shin, Eun-Joo Lee
Epidemiol Health. 2021;43:e2021010.   Published online January 21, 2021
DOI: https://doi.org/10.4178/epih.e2021010
  • 14,329 View
  • 431 Download
  • 3 Web of Science
  • 3 Crossref
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
Researchers have been interested in probing how the environmental factors associated with allergic diseases affect the use of medical services. Considering this demand, we have constructed a database, named the Allergic Disease Database, based on the National Health Insurance Database (NHID). The NHID contains information on demographic and medical service utilization for approximately 99% of the Korean population. This study targeted 3 major allergic diseases, including allergic rhinitis, atopic dermatitis, and asthma. For the target diseases, our database provides daily medical service information, including the number of daily visits from 2013 and 2017, categorized by patients’ characteristics such as address, sex, age, and duration of residence. We provide additional information, including yearly population, a number of patients, and averaged geocoding coordinates by <i>eup, myeon</i>, and <i>dong</i> district code (the smallest-scale administrative units in Korea). This information enables researchers to analyze how daily changes in the environmental factors of allergic diseases (e.g., particulate matter, sulfur dioxide, and ozone) in certain regions would influence patients’ behavioral patterns of medical service utilization. Moreover, researchers can analyze long-term trends in allergic diseases and the health effects caused by environmental factors such as daily climate and pollution data. The advantages of this database are easy access to data, additional levels of geographic detail, time-efficient data-refining and processing, and a de-identification process that minimizes the exposure of identifiable personal information. All datasets included in the Allergic Disease Database can be downloaded by accessing the National Health Insurance Service data sharing webpage (https://nhiss.nhis.or.kr).
Summary
Korean summary
알레르기질환DB는 환경적 변화와 의료이용 연관성 연구를 지원하기 위해 만들어진 누구나 다운로드 가능한 공개용DB이다. 알레르기질환DB는 한국 전국민의 사회인구학적 특성 및 의료이용 정보가 구축되어 있는 국민건강보험공단의 국민건강정보DB를 활용하여 구축되었다. 알레르기질환DB는 2013년~2017년 알레르기성 비염, 아토피, 천식 상병코드로 청구된 의료이용 정보를 제공하고 있으며, 이를 활용하여 특정 지역에 다양한 환경적 변화와 의료이용과의 연관성 연구 등에 활발히 활용될 것으로 기대된다.
Key Message
The Allergic Disease Database based on the National Health Insurance Data is constructed for analyzing how environmental factors affect the use of medical services. The database provides most Korean medical service information of allergic diseases, such as allergic rhinitis, atopic dermatitis, and asthma from 2013 and 2017. This information enables researchers to study how daily changes of environmental factors in certain regions would influence patients’ behavioral patterns of medical service utilization. Moreover, researchers can analyze the long-term trend of allergic diseases, and health effects caused by environmental factors such as daily climate and pollution data.

Citations

Citations to this article as recorded by  
  • Evaluation of the Regulatory Required Post-Authorization Safety Study for Propacetamol: Nested Case-Control and Case-Time-Control Studies
    Sungho Bea, Dongwon Yoon, Han Eol Jeong, Juhong Jung, Seung-Mok Park, Juhee Jeon, Young-Min Ye, Jae-Hyun Lee, Ju-Young Shin
    Yonsei Medical Journal.2024; 65(2): 120.     CrossRef
  • The relationship between exposure to environmental noise and risk of atopic dermatitis, asthma, and allergic rhinitis
    Yongho Lee, Seunghyun Lee, Seula Park, Seong-Kyu Kang, June-Hee Lee, Dong-Wook Lee, Won-Jun Choi, Wanhyung Lee
    Ecotoxicology and Environmental Safety.2023; 268: 115677.     CrossRef
  • Increased risk of cataract surgery in patients with allergic disease: a population based cohort study
    Ji-Sun Paik, Kyungdo Han, Gahee Nam, Sun-Kyoung Park, Ho Sik Hwang, Yoon Hong Chun, Kyung-Sun Na
    Scientific Reports.2022;[Epub]     CrossRef
Family tree database of the National Health Information Database in Korea
Yeon-Yong Kim, Hae-young Hong, Kyu-Dong Cho, Jong Heon Park
Epidemiol Health. 2019;41:e2019040.   Published online October 1, 2019
DOI: https://doi.org/10.4178/epih.e2019040
  • 14,425 View
  • 167 Download
  • 7 Web of Science
  • 6 Crossref
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
We constructed the family tree database (DB) by using a new family code system that can logically express interpersonal family relationships and by comparing and complementing health insurance eligibility data and resident register data of the National Health Information Database (NHID). In the family tree DB, Parents and grandparents are matched for more than 95% of those who were born between 2010 and 2017. Codes for inverse relationships and extended relationships are generated using sequences of the three-digit basic family codes. The family tree DB contains variables such as sex, birth year, family relations, and degree of kinship (maximum of 4) between subjects and family members. Using the family tree DB, we find that prevalence rates of hypertension, diabetes, ischemic heart disease, cerebrovascular disease, and cancer are higher for those with family history. The family tree DB may omit some relationships due to incomplete past data, and some family relations cannot be uniquely determined because the source data only contain relationships between head and members of the household. The family tree DB is a part of the NHID, and researchers can submit requests for data on the website at http://nhiss.nhis.or.kr. Requested data will be provided after approval from the data service review board. However, the family tree DB can be limitedly provided for studies with high public value in order to maximize personal information protection.
Summary
Korean summary
가족관계도(family tree) DB는 건강보험공단이 보유하는 건강보험 가입자정보와 행정전산망 정보를 바탕으로 가공·구축된 자료다. 4촌까지의 가족 관계를 파악할 수 있으며, 세대주 중심의 관계코드가 아닌 개인 단위의 논리적 기호로 구성된 관계코드를 통해 촌수, 계통, 성별을 구분하도록 하였다. 이를 바탕으로 의학적, 사회정책적으로 다양한 연구가 가능하다.

Citations

Citations to this article as recorded by  
  • Association between familial aggregation of chronic kidney disease and its incidence and progression
    Jae Young Kim, Sung-youn Chun, Hyunsun Lim, Tae Ik Chang
    Scientific Reports.2023;[Epub]     CrossRef
  • Association of Chronic Kidney Disease With Atrial Fibrillation in the General Adult Population: A Nationwide Population‐Based Study
    Seon‐Mi Kim, Yujin Jeong, Yae Lim Kim, Minjung Kang, Eunjeong Kang, Hyunjin Ryu, Yunmi Kim, Seung Seok Han, Curie Ahn, Kook‐Hwan Oh
    Journal of the American Heart Association.2023;[Epub]     CrossRef
  • Genograma y árbol genealógico
    María Yanes-Rodríguez, María Concepción Cruz-Cánovas, Enrique José Gamero-de-Luna
    Medicina de Familia. SEMERGEN.2022; 48(3): 200.     CrossRef
  • National General Health Screening Program in Korea: history, current status, and future direction
    Dong Wook Shin, Juhee Cho, Jae Hyun Park, BeLong Cho
    Precision and Future Medicine.2022; 6(1): 9.     CrossRef
  • Clinical Study Using Healthcare Claims Database
    Jin-Su Park, Chan Hee Lee
    Journal of Rheumatic Diseases.2021; 28(3): 119.     CrossRef
  • Comparison between calcium channel blocker with angiotensin converting enzyme inhibitor or angiotensin II type 1 receptor blocker combination on the development of new-onset diabetes in hypertensive Korean patients
    Yong Hoon Kim, Ae-Young Her, Seung-Woon Rha, Byoung Geol Choi, Se Yeon Choi, Jae Kyeong Byun, Dong Oh Kang, Won Young Jang, Woohyeun Kim, Ju Yeol Baek, Woong Gil Choi, Tae Soo Kang, Jihun Ahn, Sang-Ho Park, Sung Hun Park, Ji Yeon Hong, Ji Young Park, Min-
    Journal of Diabetes & Metabolic Disorders.2020; 19(1): 405.     CrossRef

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