Data Reliability and Coding Completeness of Cancer Registry Information Using Reabstracting Method in the National Cancer Institute: Thailand, 2012 to 2014

Purpose: Data quality is a core value of cancer registries, which bring about greater understanding of cancer distribution and determinants. Thailand established its cancer registry in 1986; however, studies focusing on data reliability have been limited. This study aimed to assess the coding completeness and reliability of the National Cancer Institute (NCI) hospital-based cancer registry, Thailand. Methods: This study was conducted using the reabstracting method. We focused on seven cancer sites—the colon, rectum, liver, lung, breast, cervix, and prostate—registered between 2012 and 2014 in the NCI hospital-based cancer registry. Missing data were identified for coding completeness calculation among important variables. The agreement rate and κ coefficient were computed to represent data reliability. Results: For reabstracting, we retrieved 957 medical records from a total of 5,462. These were selected using the probability proportional to size method, stratified by topology, sex, and registered year. The overall coding completeness of the registered and reabstracted data was 89.9% and 93.6%, respectively. In addition, the overall agreement rate among variables ranged from 84.7% to 99.6%, and κ coefficient ranged from 0.619 to 0.995. The misclassification among unilateral organs caused lower coding completeness and agreement rate of laterality coding. The completeness of current residency could be improved using the reabstracting method. The lowest agreement rate was found among various categories of diagnosis basis. Sex misclassification for male breast cancer was identified. Conclusion: The coding completeness and data reliability of the NCI hospital-based cancer registry met the standard in most critical variables. However, some challenges remain to improve the data quality. The reabstracting method could identify the critical points affecting the quality of cancer registry data