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

被引:1
作者
Pathak, Aditi [1 ]
Serrer, Laina [1 ]
Zapata, Daniela [1 ]
King, Raymond [2 ]
Mirel, Lisa B. [3 ]
Sukalac, Thomas [4 ]
Srinivasan, Arunkumar [5 ]
Baier, Patrick [1 ]
Bhalla, Meera [1 ]
David-Ferdon, Corinne [6 ]
Luxenberg, Steven [6 ]
Gundlapalli, Adi, V [6 ]
机构
[1] Amer Inst Res, Arlington, VA 22202 USA
[2] Ctr Dis Control & Prevent, Natl Ctr Chron Dis Prevent & Hlth Promot, Atlanta, GA 30341 USA
[3] Natl Sci Fdn, Natl Ctr Sci & Engn Stat, Alexandria, VA 22314 USA
[4] Ctr Dis Control & Prevent, Ctr Forecasting & Outbreak Analyt, Atlanta, GA 30333 USA
[5] Ctr Dis Control & Prevent, Natl Ctr Immunizat & Resp Dis, Atlanta, GA 30333 USA
[6] Ctr Dis Control & Prevent, Off Publ Hlth Data Surveillance & Technol, 1600 Clifton Rd, Atlanta, GA 30333 USA
关键词
privacy-preserving record linkage; PPRL; public health; data linkage; SYSTEMS;
D O I
10.1093/jamia/ocae196
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.Results PPRL has a high level of linkage quality and accuracy. PPRL linkage quality was comparable to that of clear text linkage methods (requiring direct personally identifiable information [PII]) for linkage across various settings and research questions. Accuracy of PPRL depended on several components, such as PPRL technique, and the proportion of missingness and errors in underlying data. Strategies to increase adoption include increasing understanding of PPRL, improving data owner buy-in, establishing governance structure and oversight, and developing a public health implementation strategy for PPRL.Discussion PPRL protects privacy by eliminating the need to share PII for linkage, but the accuracy and linkage quality depend on factors including the choice of PPRL technique and specific PII used to create encrypted identifiers. Large-scale implementations of PPRL linking millions of observations-including PCORnet, National Institutes for Health N3C, and the Centers for Disease Control and Prevention COVID-19 project have demonstrated the scalability of PPRL for public health applications.Conclusions Applications of PPRL in public health have demonstrated their value for the public health community. Although gaps must be addressed before wide implementation, PPRL is a promising solution to data linkage challenges faced by the public health ecosystem.
引用
收藏
页码:2605 / 2612
页数:8
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