Proposed Framework for Adopting Privacy-Preserving Record Linkage for Public Health Action.

Objectives: To propose a framework for adoption of privacy-preserving record linkage (PPRL) for public health applications.

Methods: Twelve interviews with subject matter experts (SMEs) were conducted virtually and coded using an inductive approach. A collaborative session was conducted with SMEs to identify key steps in the PPRL project lifecycle which informed development of a PPRL implementation checklist.

Privacy preserving record linkage for public health action: opportunities and challenges.

Objectives: To understand the landscape of privacy preserving record linkage (PPRL) applications in public health, assess estimates of PPRL accuracy and privacy, and evaluate factors for PPRL adoption.

Materials And Methods: A literature scan examined the accuracy, data privacy, and scalability of PPRL in public health. Twelve interviews with subject matter experts were conducted and coded using an inductive approach to identify factors related to PPRL adoption.

Evaluating data quality for blended data using a data quality framework.

In 2020 the U.S. Federal Committee on Statistical Methodology (FCSM) released "A Framework for Data Quality", organized by 11 dimensions of data quality grouped among three domains of quality (utility, objectivity, integrity).

A Comparison of the Mortality Experience of U.S. Adults Estimated With the 2006-2018 National Health Interview Survey Linked Mortality Files and the Annual U.S. Life Tables.

Objective-Linking data is a powerful mechanism to provide policy-relevant information. The National Center for Health Statistics' Data Linkage Program produces linked mortality files (LMFs) for research by linking data from the National Center for Health Statistics' surveys, including the National Health Interview Survey (NHIS), to mortality data from the National Death Index. Assessing the accuracy of the linked data is an important step in ensuring its analytic use.

A methodological assessment of privacy preserving record linkage using survey and administrative data.

Background: The National Center for Health Statistics (NCHS) links data from surveys to administrative data sources, but privacy concerns make accessing new data sources difficult. Privacy-preserving record linkage (PPRL) is an alternative to traditional linkage approaches that may overcome this barrier. However, prior to implementing PPRL techniques it is important to understand their effect on data quality.