Establishing a framework for privacy-preserving record linkage among electronic health record and administrative claims databases within PCORnet<sup>®</sup>, the National Patient-Centered Clinical Research Network.
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2022-10
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Abstract
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The aim of this study was to determine whether a secure, privacy-preserving record linkage (PPRL) methodology can be implemented in a scalable manner for use in a large national clinical research network.Results
We established the governance and technical capacity to support the use of PPRL across the National Patient-Centered Clinical Research Network (PCORnet®). As a pilot, four sites used the Datavant software to transform patient personally identifiable information (PII) into de-identified tokens. We queried the sites for patients with a clinical encounter in 2018 or 2019 and matched their tokens to determine whether overlap existed. We described patient overlap among the sites and generated a "deduplicated" table of patient demographic characteristics. Overlapping patients were found in 3 of the 6 site-pairs. Following deduplication, the total patient count was 3,108,515 (0.11% reduction), with the largest reduction in count for patients with an "Other/Missing" value for Sex; from 198 to 163 (17.6% reduction). The PPRL solution successfully links patients across data sources using distributed queries without directly accessing patient PII. The overlap queries and analysis performed in this pilot is being replicated across the full network to provide additional insight into patient linkages among a distributed research network.Type
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Kiernan, Daniel, Thomas Carton, Sengwee Toh, Jasmin Phua, Maryan Zirkle, Darcy Louzao, Kevin Haynes, Mark Weiner, et al. (2022). Establishing a framework for privacy-preserving record linkage among electronic health record and administrative claims databases within PCORnet®, the National Patient-Centered Clinical Research Network. BMC research notes, 15(1). p. 337. 10.1186/s13104-022-06243-5 Retrieved from https://hdl.handle.net/10161/34268.
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Scholars@Duke
Darcy Louzao
Keith Allen Marsolo
Dr. Marsolo is a faculty member in the Department of Population Health Sciences (DPHS) and a member of the Duke Clinical Research Institute (DCRI). His current research focuses on infrastructure to support the use of electronic health records (EHRs) and other real-world data sources in observational and comparative effectiveness research and public health surveillance, as well as standards and architectures for multi-center learning health systems. He serves as faculty advisor to the DPHS DataShare Shared Facility and faculty lead for the Pragmatic Health Services Research (PHSR) functional group within the DCRI. Dr. Marsolo received his PhD in Computer Science from The Ohio State University, with a dissertation on data mining, specifically the modeling and classification of biomedical data.
Prior to joining DPHS, Dr. Marsolo was an an Associate Professor in the Division of Biomedical Informatics (BMI) at Cincinnati Children’s Hospital Medical Center (CCHMC). While at CCHMC, Dr. Marsolo served as faculty advisor for BMI Data Services, a shared facility that supported distributed data sharing networks and also developed registry platforms to support learning networks. These included a configurable system for capturing summary or practice-level measures, and a “data-in-once” architecture that allowed information to be collected in the EHR and then be automatically transferred to a registry in order to support chronic care management, quality improvement and research.Area of Expertise: Informatics, Data Quality, Common Data Models, Data Standards and Data Harmonization
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