pSCANNER: patient-centered Scalable National Network for Effectiveness Research

Abstract

This article describes the patient-centered Scalable National Network for Effectiveness Research (pSCANNER), which is part of the recently formed PCORnet, a national network composed of learning healthcare systems and patient-powered research networks funded by the Patient Centered Outcomes Research Institute (PCORI). It is designed to be a stakeholder-governed federated network that uses a distributed architecture to integrate data from three existing networks covering over 21 million patients in all 50 states: (1) VA Informatics and Computing Infrastructure (VINCI), with data from Veteran Health Administration's 151 inpatient and 909 ambulatory care and community-based outpatient clinics; (2) the University of California Research exchange (UC-ReX) network, with data from UC Davis, Irvine, Los Angeles, San Francisco, and San Diego; and (3) SCANNER, a consortium of UCSD, Tennessee VA, and three federally qualified health systems in the Los Angeles area supplemented with claims and health information exchange data, led by the University of Southern California. Initial use cases will focus on three conditions: (1) congestive heart failure; (2) Kawasaki disease; (3) obesity. Stakeholders, such as patients, clinicians, and health service researchers, will be engaged to prioritize research questions to be answered through the network. We will use a privacy-preserving distributed computation model with synchronous and asynchronous modes. The distributed system will be based on a common data model that allows the construction and evaluation of distributed multivariate models for a variety of statistical analyses.

Keywords: clinical data research network; comparative effectiveness research; distributed analysis; patient-centered research.

Figure 1

Stakeholder engagement. Stakeholders from across patient-centered Scalable National Network for Effectiveness Research (pSCANNER) sites (360 total) will be recruited to participate in a three-round ExpertLens process, which will prioritize research questions that should be addressed by pSCANNER. In round 1, participants will rate different research priorities and research questions. In round 2, medians and quartiles of group responses to each question will be presented to the participants. In round 3, participants will be asked to modify their round 1 responses based on round 2 feedback and discussion.

Figure 2

Patient-centered Scalable National Network for Effectiveness Research (pSCANNER) architecture. pSCANNER is a clinical data research network that will integrate over 21 million patients. It will use privacy and security tools to enable distributed analysis of data while keeping data in their host institutions and adhering to all applicable federal, state, and institutional policies. k, thousand; m, million; OMOP, Observational Medical Outcomes Partnership; QueensCare, QueensCare Family Clinics; SFGH, San Francisco General Hospital; TCC, The Children's Clinic of Long Beach; UCD, University of California, Davis; UCI, University of California, Irvine; UCLA, University of California, Los Angeles; UCSD, University of California San Diego; UCSF, University of California, San Francisco; VA, Veterans Affair; VM, Virtual Machine.

Figure 3

Distributed computing. Patient-centered Scalable National Network for Effectiveness Research (pSCANNER) answers an end-user's scientific question by distributing the corresponding query to each participating site, processing the query locally while preserving each site's stringent data privacy and security requirements, then aggregating the responses into a coherent answer.