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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 621-626 |
| Number of pages | 6 |
| Journal | Journal of the American Medical Informatics Association |
| Volume | 21 |
| Issue number | 4 |
| DOIs | |
| State | Published - 2014 |
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ASJC Scopus subject areas
- Health Informatics
Cite this
pSCANNER : Patient-centered scalable national network for effectiveness research. / Ohno-Machado, Lucila; Agha, Zia; Bell, Douglas S.; Dahm, Lisa; Day, Michele E.; Doctor, Jason N.; Gabriel, Davera; Kahlon, Maninder K.; Kim, Katherine K; Hogarth, Michael; Matheny, Michael E.; Meeker, Daniella; Nebeker, Jonathan R.
In: Journal of the American Medical Informatics Association, Vol. 21, No. 4, 2014, p. 621-626.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - pSCANNER
T2 - Patient-centered scalable national network for effectiveness research
AU - Ohno-Machado, Lucila
AU - Agha, Zia
AU - Bell, Douglas S.
AU - Dahm, Lisa
AU - Day, Michele E.
AU - Doctor, Jason N.
AU - Gabriel, Davera
AU - Kahlon, Maninder K.
AU - Kim, Katherine K
AU - Hogarth, Michael
AU - Matheny, Michael E.
AU - Meeker, Daniella
AU - Nebeker, Jonathan R.
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84902383973&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84902383973&partnerID=8YFLogxK
U2 - 10.1136/amiajnl-2014-002751
DO - 10.1136/amiajnl-2014-002751
M3 - Article
C2 - 24780722
AN - SCOPUS:84902383973
VL - 21
SP - 621
EP - 626
JO - Journal of the American Medical Informatics Association : JAMIA
JF - Journal of the American Medical Informatics Association : JAMIA
SN - 1067-5027
IS - 4
ER -