title: A system to build distributed multivariate models and manage disparate data sharing policies: implementation in the scalable national network for effectiveness research.
abstract: BACKGROUND
  Centralized and federated models for sharing data in research networks currently exist. To build multivariate data analysis for centralized networks, transfer of patient-level data to a central computation resource is necessary. The authors implemented distributed multivariate models for federated networks in which patient-level data is kept at each site and data exchange policies are managed in a study-centric manner.
  
  
  OBJECTIVE
  The objective was to implement infrastructure that supports the functionality of some existing research networks (e.g., cohort discovery, workflow management, and estimation of multivariate analytic models on centralized data) while adding additional important new features, such as algorithms for distributed iterative multivariate models, a graphical interface for multivariate model specification, synchronous and asynchronous response to network queries, investigator-initiated studies, and study-based control of staff, protocols, and data sharing policies.
  
  
  METHODS
  Based on the requirements gathered from statisticians, administrators, and investigators from multiple institutions, the authors developed infrastructure and tools to support multisite comparative effectiveness studies using web services for multivariate statistical estimation in the SCANNER federated network.
  
  
  RESULTS
  The authors implemented massively parallel (map-reduce) computation methods and a new policy management system to enable each study initiated by network participants to define the ways in which data may be processed, managed, queried, and shared. The authors illustrated the use of these systems among institutions with highly different policies and operating under different state laws.
  
  
  CONCLUSIONS
  Federated research networks need not limit distributed query functionality to count queries, cohort discovery, or independently estimated analytic models. Multivariate analyses can be efficiently and securely conducted without patient-level data transport, allowing institutions with strict local data storage requirements to participate in sophisticated analyses based on federated research networks.
authors.affiliation: Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA Information Sciences Institute, University of Southern California, Marina Del Rey, CA dmeeker@usc.edu.
authors.forename: Daniella
authors.initials: D
authors.lastname: Meeker
authors.affiliation: Department of Biomedical Informatics, University of California San Diego, La Jolla, CA 92093.
authors.forename: Xiaoqian
authors.initials: X
authors.lastname: Jiang
authors.affiliation: Geriatrics Research, Education, and Clinical Care Service Department of Biomedical Informatics, Division of General Internal Medicine, Department of Biostatistics.
authors.forename: Michael E
authors.initials: ME
authors.lastname: Matheny
authors.affiliation: Department of Biomedical Informatics, University of California San Diego, La Jolla, CA 92093.
authors.forename: Claudiu
authors.initials: C
authors.lastname: Farcas
authors.affiliation: Information Sciences Institute, University of Southern California, Marina Del Rey, CA.
authors.forename: Michel
authors.initials: M
authors.lastname: D'Arcy
authors.affiliation: Information Sciences Institute, University of Southern California, Marina Del Rey, CA.
authors.forename: Laura
authors.initials: L
authors.lastname: Pearlman
authors.affiliation: Geriatrics Research, Education, and Clinical Care Service.
authors.forename: Lavanya
authors.initials: L
authors.lastname: Nookala
authors.affiliation: Department of Biomedical Informatics, University of California San Diego, La Jolla, CA 92093.
authors.forename: Michele E
authors.initials: ME
authors.lastname: Day
authors.affiliation: Department of Pathology and Laboratory Medicine and Department of Internal Medicine, University of California Davis, Sacramento, CA.
authors.forename: Katherine K
authors.initials: KK
authors.lastname: Kim
authors.affiliation: Department of Biomedical Informatics, University of California San Diego, La Jolla, CA 92093.
authors.forename: Hyeoneui
authors.initials: H
authors.lastname: Kim
authors.affiliation: Department of Biomedical Informatics, University of California San Diego, La Jolla, CA 92093.
authors.forename: Aziz
authors.initials: A
authors.lastname: Boxwala
authors.affiliation: Department of Biomedical Informatics, University of California San Diego, La Jolla, CA 92093.
authors.forename: Robert
authors.initials: R
authors.lastname: El-Kareh
authors.affiliation: Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego.
authors.forename: Grace M
authors.initials: GM
authors.lastname: Kuo
authors.affiliation: Lahey Hospital and Medical Center, Burlington, MA, USA.
authors.forename: Frederic S
authors.initials: FS
authors.lastname: Resnic
authors.affiliation: Information Sciences Institute, University of Southern California, Marina Del Rey, CA.
authors.forename: Carl
authors.initials: C
authors.lastname: Kesselman
authors.affiliation: Department of Biomedical Informatics, University of California San Diego, La Jolla, CA 92093.
authors.forename: Lucila
authors.initials: L
authors.lastname: Ohno-Machado
mesh_terms: D035843:Biomedical Research; D057186:Comparative Effectiveness Research / Q000458:organization & administration*; D003195:Computer Communication Networks; D019992:Databases as Topic; D033181:Information Dissemination; D016247:Information Storage and Retrieval; D020407:Internet; D015233:Models, Statistical; D015999:Multivariate Analysis; D012984:Software
keywords: comparative effectiveness research; distributed analytics; federated research network; privacy-preserving network infrastructure