We analyze the deterioration of clinical data quality due to anonymization. The result shows that data quality remained high with micro-aggregation and also verify the availability of noise addition to prevent illegal re-identification by matching another personal data. The Amended Act on the Protection of Personal Informationin Japan, scheduled to go into full effect in the May of 2017, will open a way to provide medical records to third parties by de-identifying personal data. For de-identifying data, the law mandates the processing of personal information in accordance with standards stipulated by the rules of the Personal Information Protection Committee (PPC) [1] and the relevant guidelines. Currently, the PPC states that the five requirements must be met for the provision of data to a third party without personal agreement. At present, however, it is not clear what process will be sufficient to fulfill these rules because of the lack of technical guidelines for the anonymization process. The nature of an appropriate anonymization process may change depending on the content of the data and type of analysis. Our study examines use cases for clinical data to establish the best practice in anonymization.
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