"First Case of Pseudonymized Data Integration" National Cancer Center Announces Lung Cancer Treatment Research

[Asia Economy Reporter Eunmo Koo] As the first achievement of data linkage using pseudonymized information introduced by last year's amendment to the Personal Information Protection Act, research results on lung cancer treatment from the National Cancer Center have been produced.

The National Cancer Center, the Personal Information Protection Commission, the Ministry of Health and Welfare, and other related organizations announced on the 27th the research results on mortality trends and death prediction of lung cancer patients based on linked data combining pseudonymized clinical information of lung cancer patients from the National Cancer Center, medical treatment information from the National Health Insurance Service, and death information from Statistics Korea. This case was promoted as one of the seven projects in five major fields utilizing pseudonymized information, and the results of each project will be announced sequentially.

Before the amendment of the Three Data Acts, when cancer patients used multiple hospitals, it was impossible to sufficiently know the occurrence of complications and chronic diseases with data from a single medical institution, and if the patient died after treatment, it was impossible to confirm the exact cause and timing of death. However, with the amendment of the Three Data Acts, data linkage and analysis of multiple institutions became possible through pseudonymized information linkage, enabling long-term tracking and observation of important information such as complications, chronic diseases, and death mainly occurring in cancer patients after treatment.

This study is the first case of linking pseudonymized health-related big data held by multiple institutions, including lung cancer patient information (20,000 patients) from the National Cancer Center, cancer patient medical treatment information (20,000 patients) from the National Health Insurance Service, and death information (4.23 million people) from Statistics Korea, aiming to analyze lung cancer treatment effects and develop prediction models for complications, chronic diseases, and death in lung cancer patients. This pseudonymized information linkage was conducted in accordance with the Personal Information Protection Act and the 'Healthcare Data Utilization Guidelines' announced by the Ministry of Health and Welfare.

This pilot case is evaluated as demonstrating the possibility of linking high-value clinical information from hospitals with data from multiple public institutions. By quickly and accurately identifying health information of patients who had been difficult to track, it is expected to shorten research periods and costs and contribute to preparing clinically meaningful real-world evidence. The pseudonymized information linkage following the amendment of the Three Data Acts is expected to enhance the utilization value of latent healthcare data and achieve significant results in various research fields such as healthcare artificial intelligence in the future.

Seohong Kwan, Director of the National Cancer Center, said, “For optimized treatment of cancer patients, it is very necessary to have full-cycle medical data from diagnosis, surgery, treatment, recurrence, metastasis, to death,” and added, “Through this pilot case, it is expected to help manage chronic diseases and promote health of lung cancer survivors, and it is anticipated to play a pivotal role in patient-centered medical services using national cancer big data in the future.”

Yoon Jong-in, Chairman of the Personal Information Protection Commission, said, “This case is the first step in a new path of linking pseudonymized information by pseudonymizing personal information, and the first attempt to create new utilization value of data by linking information from multiple institutions,” and added, “Through a prediction model that comprehensively prepares not only for cancer but also related complications and chronic diseases for cancer patients, it is expected to increase long-term survival rates and contribute diversely to public health promotion through the utilization of existing medical data.”

This content was produced with the assistance of AI translation services.