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Prospective cohort data quality assurance and quality control strategy and method: Korea HIV/AIDS Cohort Study

Epidemiology and Health 2020년 42권 1호 p.63 ~ 63
김수민, 최은수, 최보율, 김민정, 김상일, 최준용, 김신우, 송준영, 김윤정, 기미경, 유명수, 이정규, 박보영,
소속 상세정보
김수민 ( Kim Soo-Min ) - Yonsei University College of Commerce and Economics Department of Applied Statistics
최은수 ( Choi Yun-Su ) - Hanyang University Institute for Health and Society
최보율 ( Choi Bo-Youl ) - Hanyang University Institute for Health and Society
김민정 ( Kim Min-Jeong ) - Hanyang University Institute for Health and Society
김상일 ( Kim Sang-Il ) - Catholic University College of Medicine Seoul St. Mary’s Hospital Department of Internal Medicine
최준용 ( Choi Jun-Young ) - Yonsei University College of Medicine Department of Internal Medicine
김신우 ( Kim Shin-Woo ) - Kyungpook National University School of Medicine Department of Internal Medicine
송준영 ( Song Joon-Young ) - Korea University College of Medicine Department of Internal Medicine
김윤정 ( Kim Youn-Jeong ) - Catholic University College of Medicine Incheon St. Mary’s Hospital Department of Internal Medicine
기미경 ( Kee Mee-Kyung ) - Korea National Institute of Health Center for Infectious Diseases Research Division of Viral Disease Research
유명수 ( Yoo Myeong-Su ) - Korea National Institute of Health Center for Infectious Diseases Research Division of Viral Disease Research
이정규 ( Lee Jeong-Gyu ) - Korea National Institute of Health Center for Infectious Diseases Research Division of Viral Disease Research
박보영 ( Park Bo-Young ) - Hanyang University College of Medicine Department of Preventive Medicine

Abstract


OBJECTIVES: The aim of effective data quality control and management is to minimize the impact of errors on study results by identifying and correcting them. This study presents the results of a data quality control system for the Korea HIV/AIDS Cohort Study that took into account the characteristics of the data.

METHODS: The HIV/AIDS Cohort Study in Korea conducts repeated measurements every 6 months using an electronic survey administered to voluntarily consenting participants and collects data from 21 hospitals. In total, 5,795 sets of data from 1,442 participants were collected from the first investigation in 2006 to 2016. The data refining results of 2015 and 2019 were converted into the data refining rate and compared.

RESULTS: The quality control system involved 3 steps at different points in the process, and each step contributed to data quality management and results. By improving data quality control in the pre-phase and the data collection phase, the estimated error value in 2019 was 1,803, reflecting a 53.9% reduction from 2015. Due to improvements in the stage after data collection, the data refining rate was 92.7% in 2019, a 24.21%p increase from 2015.

CONCLUSIONS: Despite this quality management strategy, errors may still exist at each stage. Logically possible errors for the post-review refining of downloaded data should be actively identified with appropriate consideration of the purpose and epidemiological characteristics of the study data. To improve data quality and reliability, data management strategies should be systematically implemented.

키워드

HIV/AIDS; Quality control; Cohort studies; Data adjustment; Data quality; Data accuracy

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