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Discharge status validation of the Chang Gung Research database in Taiwan
Yu-Tung Huang1, Ying-Jen Chen2, Shang-Hung Chang3
1Center for Big Data Analytics and Statistics, Department of Medical Research and Development, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
Insights
This study validated the Chang Gung Research Database (CGRD) for mortality data accuracy. Findings show high accuracy for electronic medical records after 2010, recommending their use for future research.
Area of Science:
- Medical Informatics
- Health Data Science
- Epidemiology
Background:
- The Chang Gung Research Database (CGRD) is a large, multi-institutional electronic medical records database in Taiwan.
- Validation of CGRD's data accuracy, particularly for discharge status and mortality, is crucial but has been limited.
- This study addresses the need to validate the accuracy of CGRD for mortality outcome research.
Purpose of the Study:
- To validate the accuracy of discharge status, with a specific focus on mortality, within the Chang Gung Research Database (CGRD).
- To assess the reliability of CGRD data for epidemiological studies relying on mortality outcomes.
Main Methods:
- An observational study was conducted, linking CGRD data with the Taiwan Disease Registry (TDR).
- Validation metrics included accuracy, positive predictive value (PPV), and underestimated mortality rate (UEM).
- Analyses considered variations by year, sex, age, and primary cause for admission (PCA).
Main Results:
- Overall accuracy for mortality coding in CGRD discharge status exceeded 97% within one week post-discharge.
- Data accuracy improved annually, surpassing 98% after 2010.
- Underestimated mortality rates (UEM) were below 10% after 2010, though accuracy varied by age and primary cause for admission, with elderly patients showing lower accuracy and higher UEM.
Conclusions:
- The Chang Gung Research Database (CGRD) demonstrates high accuracy for mortality data, especially for inpatient records after 2010.
- Prioritizing CGRD data from 2010 onwards is recommended for mortality outcome follow-up studies.
- Careful consideration of age and primary cause for admission is advised when interpreting CGRD mortality data.
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.