Measuring risk and information preservation: toward new metrics for de-identification of clinical texts

Authors:
Lynette Hirschman;John Aberdeen
Affiliations:
The MITRE Corporation, Bedford, MA;The MITRE Corporation, Bedford, MA
Venue:
Louhi '10 Proceedings of the NAACL HLT 2010 Second Louhi Workshop on Text and Data Mining of Health Documents
Year:
2010

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Abstract

Current metrics for de-identification are based on information extraction metrics, and do not address the real-world questions "how good are current systems", and "how good do they need to be". Metrics are needed that quantify both the risk of re-identification and information preservation. We review the challenges in de-identifying clinical texts and the current metrics for assessing clinical de-identification systems. We then introduce three areas to explore that can lead to metrics that quantify re-identification risk and information preservation.