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Background A distributed data network approach combined with distributed regression analysis (DRA) can reduce the risk of disclosing sensitive individual and institutional information in multicenter studies. However, software that facilitates large-scale and efficient implementation of DRA is limited. Objective This study aimed to assess the precision and operational performance of a DRA application comprising a SAS-based DRA package and a file transfer workflow developed within the open-source distributed networking software PopMedNet in a horizontally partitioned distributed data network. Methods We executed the SAS-based DRA package to perform distributed linear, logistic, and Cox proportional hazards regression analysis on a real-world test case with 3 data partners. We used PopMedNet to iteratively and automatically transfer highly summarized information between the data partners and the analysis center. We compared the DRA results with the results from standard SAS procedures executed on the pooled individual-level dataset to evaluate the precision of the SAS-based DRA package. We computed the execution time of each step in the workflow to evaluate the operational performance of the PopMedNet-driven file transfer workflow. Results All DRA results were precise ( Conclusions We integrated a SAS-based DRA package with PopMedNet and successfully tested the new capability within an active distributed data network. The study demonstrated the validity and feasibility of using DRA to enable more privacy-protecting analysis in multicenter studies.

Presented at the National data integrity conference: data sharing: the how, why, when and when not to share held on June 2-3, 2016 at University of Colorado, Denver, Colorado. The National Data Integrity Conference is a gathering of people sharing new challenges and solutions regarding research data and integrity. This conference aims to provide attendees with both an understanding of data integrity issues and impart practical tools and skills to deal with them. Topics addressed will include data privacy, openness, policy, education and the impacts of sharing data, how to do it, when to do it, and when not to. Speakers and audience members come from diverse fields such as: Academic Research; Information Technology; Quality Assurance; Regulatory Compliance; Private Industry; Grant Funding; Government., PowerPoint presentation during Lightning Talks given on June 3, 2016., Rachel is affiliated with the University of Colorado - Anschutz Medical Campus., This talk will describe the software underlying CHORDS, the concept of a federated query, the methods CHORDS uses to enable site participation, and the formal agreements required to contribute to the network or query distributed data. Finally, we will discuss growth of this technology platform and anticipated needs and challenges as CHORDS serves new use cases to enable clinical health research studies and other research activities. A key challenge is the need for patient record linkage to unduplicate an individual's medical records across systems. A solution underway seeks to transfer data to an external partner to leverage an existing master patient index tool used for clinical care.