TY - GEN
T1 - Surveying a new multi-institution clinical data research network
AU - Rosenman, Marc
AU - Madden, Margaret
AU - Oh, Elissa
AU - Goel, Satyender
AU - Kho, Abel
N1 - Publisher Copyright:
© 2017 International Medical Informatics Association (IMIA) and IOS Press.
PY - 2017
Y1 - 2017
N2 - Cultivated by the Patient-Centered Outcomes Research Network (PCORnet), thirteen regional clinical data research networks (CDRNs) are taking shape across the U.S. The PCORnet common data model was carefully planned, and the data marts assembled by the more than 80 data-contributing institutions (nodes) are undergoing, in 2016-2017, a series of data characterization cycles. PCORnet will adjudge each node's - and thereby, in a significant way, each CDRN's - readiness or unreadiness for multi-institution research. Certifying each node's quality and fidelity is of course essential. But in understanding network readiness there is an additional, vital dimension - one that has received too little attention. It is the development of knowledge about the nature of a CDRN's data, in its federated sense. With visualizations, how might one grasp the meta-data of a CDRN? We outline an approach that builds upon the HealthLNK Data Repository, a forerunner to the Chicago Area Patient-Centered Outcomes Research Network (CAPriCORN) CDRN.
AB - Cultivated by the Patient-Centered Outcomes Research Network (PCORnet), thirteen regional clinical data research networks (CDRNs) are taking shape across the U.S. The PCORnet common data model was carefully planned, and the data marts assembled by the more than 80 data-contributing institutions (nodes) are undergoing, in 2016-2017, a series of data characterization cycles. PCORnet will adjudge each node's - and thereby, in a significant way, each CDRN's - readiness or unreadiness for multi-institution research. Certifying each node's quality and fidelity is of course essential. But in understanding network readiness there is an additional, vital dimension - one that has received too little attention. It is the development of knowledge about the nature of a CDRN's data, in its federated sense. With visualizations, how might one grasp the meta-data of a CDRN? We outline an approach that builds upon the HealthLNK Data Repository, a forerunner to the Chicago Area Patient-Centered Outcomes Research Network (CAPriCORN) CDRN.
KW - Electronic health records
KW - Metadata
KW - Patient outcome assessment
UR - http://www.scopus.com/inward/record.url?scp=85040516463&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85040516463&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-830-3-935
DO - 10.3233/978-1-61499-830-3-935
M3 - Conference contribution
C2 - 29295237
AN - SCOPUS:85040516463
T3 - Studies in Health Technology and Informatics
SP - 935
EP - 939
BT - MEDINFO 2017
A2 - Dongsheng, Zhao
A2 - Gundlapalli, Adi V.
A2 - Marie-Christine, Jaulent
PB - IOS Press
T2 - 16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017
Y2 - 21 August 2017 through 25 August 2017
ER -