Automatable Distributed Regression Analysis of Vertically Partitioned Data Facilitated by PopMedNet: Feasibility and Enhancement Study
| Autor: | Aleksandra B. Slavkovic, Qoua L. Her, Thomas Kent, Sengwee Toh, Yury Vilk, Yuji Samizo |
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| Rok vydání: | 2021 |
| Předmět: |
Computer science
Computer applications to medicine. Medical informatics Pooling R858-859.7 Health Informatics computer.software_genre 03 medical and health sciences Upload 0302 clinical medicine Software distributed data networks Health Information Management informatics 030212 general & internal medicine data networks SSH File Transfer Protocol privacy-protecting analytics Original Paper business.industry distributed regression analysis 030503 health policy & services Suite Regression analysis vertically partitioned data data Informatics File transfer Data mining 0305 other medical science business computer |
| Zdroj: | JMIR Medical Informatics JMIR Medical Informatics, Vol 9, Iss 4, p e21459 (2021) |
| ISSN: | 2291-9694 |
| DOI: | 10.2196/21459 |
| Popis: | Background In clinical research, important variables may be collected from multiple data sources. Physical pooling of patient-level data from multiple sources often raises several challenges, including proper protection of patient privacy and proprietary interests. We previously developed an SAS-based package to perform distributed regression—a suite of privacy-protecting methods that perform multivariable-adjusted regression analysis using only summary-level information—with horizontally partitioned data, a setting where distinct cohorts of patients are available from different data sources. We integrated the package with PopMedNet, an open-source file transfer software, to facilitate secure file transfer between the analysis center and the data-contributing sites. The feasibility of using PopMedNet to facilitate distributed regression analysis (DRA) with vertically partitioned data, a setting where the data attributes from a cohort of patients are available from different data sources, was unknown. Objective The objective of the study was to describe the feasibility of using PopMedNet and enhancements to PopMedNet to facilitate automatable vertical DRA (vDRA) in real-world settings. Methods We gathered the statistical and informatic requirements of using PopMedNet to facilitate automatable vDRA. We enhanced PopMedNet based on these requirements to improve its technical capability to support vDRA. Results PopMedNet can enable automatable vDRA. We identified and implemented two enhancements to PopMedNet that improved its technical capability to perform automatable vDRA in real-world settings. The first was the ability to simultaneously upload and download multiple files, and the second was the ability to directly transfer summary-level information between the data-contributing sites without a third-party analysis center. Conclusions PopMedNet can be used to facilitate automatable vDRA to protect patient privacy and support clinical research in real-world settings. |
| Databáze: | OpenAIRE |
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