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KMID : 1001020210190040232
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Journal of Urologic Oncology
2021 Volume.19 No. 4 p.232 ~ p.243
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Construction of a Retrospective Cohort to Observe 10-Year Urologic Cancer Treatment Trends at the Biggest Medical Center of South Korea
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Choi Se-Young
Kim Ho-Heon
Lim Bum-Jin
Lee Jong-Won
Kim Young-Seok
Kim Jeong-Kon
Lee Jae-Lyun
Cho Yong-Mee
You Dal-San
Jeong In-Gab
Song Che-Ryn
Hong Jun-Hyuk
Kim Choung-Soo
Ahn Han-Jong
Hong Bum-Sik
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Abstract
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Purpose: To construct a urologic cancer database using a standardized, reproducible method, and to assess preliminary characteristics of this cohort.
Materials and Methods: Patients with prostate, bladder, and kidney cancers who were en-rolled with diagnostic codes in the electronic medical record (EMR) at Asan Medical Center from 2007?2016 were included. Research Electronic Data Capture (REDCap) was used to design the Asan Medical Center-Urologic Cancer Database (AMC-UCD). The process included developing a data dictionary, applying branching logic, mapping clinical data warehouse structures, al-pha testing, clinical record summary testing, creating “standards of procedure,” importing data, and entering data. Descriptive statistics were used to identify rates of surgeries and numbers of patients.
Results: Clinical variables (n=407) were selected to develop a data dictionary from REDCap. In total, 20,198 urologic cancer patients visited our institution from 2007?2016 (bladder can-cer, 4,616; kidney cancer, 5,750; prostate cancer, 10,330). The overall numbers of patients and surgeries increased over time, with robotic surgeries rapidly growing over a decade. The most common treatment for urologic cancer was surgery, followed by chemotherapy and radiation therapy.
Conclusions: Using a standardized method, the AMC-UCD fosters multidisciplinary research. This constructed database provides access to clinical statistics to effectively assist research. Preliminary data should be refined through EMR chart review. The successful organization of data from 2007?2016 provides a framework for future periods of investigation and prospective models.
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KEYWORD
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Database, Research Electronic Data Capture, REDCap, Urologic oncology, Genito-urinary oncology
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