Discharge Status Validation of the Chang Gung Research Database in Taiwan

Overview

Journal Biomed J

Publisher Elsevier

Specialty General Medicine

Date 2021 Dec 31

PMID 34971827

Citations 13

Authors

Yu-Tung Huang

Ying-Jen Chen

Shang-Hung Chang

Chang-Fu Kuo

Mei-Hua Chen

Affiliations

Soon will be listed here.

Abstract

Background: The Chang Gung Research Database (CGRD) is the largest multi-institutional electronic medical records database in Taiwan and has been widely used to establish evidence studies. However, the accuracy of CGRD has rarely been validated. This study aims to validate the discharge status, especially with a focus on mortality, of admission data under CGRD.

Methods: We constructed an observational study using CGRD linked with TDR to validate the discharge status. The CGRD and TDR data were obtained from the Chang Gung Memorial Hospital system and the Health and Welfare Data Science Center, respectively. The accuracy, positive predictive value (PPV), and underestimated mortality rate (UEM) were employed as indicators for validation. Year, sex, age, and the primary cause for admission (PCA) were analyzed.

Results: A total of 1,972,044 admission records under CGRD were analyzed. The overall accuracy for mortality coding on discharge status was higher than 97% within one week after discharge. The accuracy increased by year and was more than 98% after 2010. A similar result was observed in UEM; the UEM within one week was lower than 10% after 2010. These indicators varied by age group and PCA-elderly patients had relatively lower accuracy and higher UEM (approximately 11%). The presence of UEM within one week was better but varied by disease.

Conclusions: Considering the data accuracy and UEM discharge status, prioritizing the use of inpatient data after 2010 under CGRD for mortality outcome follow-up studies is recommended.

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