Addressing Disclosure Concerns and Analysis Demands in a Real-Time Online Analytic System

作者：Krenzke Tom^*; Gentleman Jane F; Li Jianzhu; Moriarity Chris

来源：Journal of Official Statistics, 2013, 29(1): 99-124.

DOI：10.2478/jos-2013-0006

• Confidentiality
• data utility
• disclosure risk
• statistical disclosure control

This article focuses on methods for enhancing access to survey data produced by government agencies. In particular, the National Center for Health Statistics (NCHS) is developing methods that could be used in an interactive, integrated, real-time online analytic system (OAS) to facilitate analysis by the public of both restricted and public use survey data. Data from NCHS' National Health Interview Survey (NHIS) are being used to investigate, develop, and evaluate such methods. We assume the existence of public use microdata files, as is the case for the NHIS, so disclosure avoidance methods for such an OAS must account for that critical constraint. Of special interest is the analysis of state-level data because health care is largely administered at the state level in the U.S., and state identifiers are not on the NHIS public use files. This article describes our investigations of various possible choices of methods for statistical disclosure control and the challenges of providing such protection in a real-time OAS that uses restricted data. Full details about the specific disclosure control methods used by a working OAS could never be publicly released for confidentiality reasons. NCHS is still evaluating whether to implement an OAS that uses NHIS restricted data, and this article provides a snapshot of a research and developmental project in progress.

• 出版日期2013-3