An area of CHIP pioneering innovation is federated networks, a practice which enables decentralized approaches to data distributed across sites. From our faculty’s earliest forays into the field with the Shared Pathology Information Network (The NCI funded “Napster for pathology samples”) to the first demonstration of federated research networks for biosurveillance, to development of the Shared Health Research Innovation Network (SHRINE) network.

Our program has worked with sister academic medical institutions to establish globally scalable technology, policies and procedures for sharing genomic, phenotypic and biospecimen data on broadly consented cohorts, across sites of care. We have, in partnership with our sister sites, developed two federated data sharing commons, the Genomic Research and Innovation Network (GRIN) and the Genomic Information Commons (GIC). Our faculty have developed the first query portal in the world that provides a uniform interface that enables users to retrieve genomic data, phenotypic data and biospecimen metadata in a single query. The technology, policies, and procedures that we have developed enable us to acquire additional partners and scale our federated data sharing globally.

Projects

Publications

Kohane IS, Aronow BJ, Avillach P, Beaulieu-Jones BK, Bellazzi R, Bradford RL, Brat GA, Cannataro M, Cimino JJ, García-Barrio N, Gehlenborg N, Ghassemi M, Gutiérrez-Sacristán A, Hanauer DA, Holmes JH, Hong C, Klann JG, Loh NHW, Luo Y, Mandl KD, Mohamad D, Moore JH, Murphy SN, Neuraz A, Ngiam KY, Omenn GS, Palmer N, Patel LP, Pedrera-Jiménez M, Sliz P, South AM, Tan ALM, Taylor DM, Taylor BW, Torti C, Vallejos AK, Wagholikar KB, Weber GM, Cai T. What Every Reader Should Know About Studies Using Electronic Health Record Data but May be Afraid to Ask. Journal of medical Internet research 2021.

Cutillo CM, Sharma KR, Foschini L, Kundu S, Mackintosh M, Mandl KD, . Machine intelligence in healthcare-perspectives on trustworthiness, explainability, usability, and transparency. NPJ digital medicine 2020.

Brat GA, Weber GM, Gehlenborg N, Avillach P, Palmer NP, Chiovato L, Cimino J, Waitman LR, Omenn GS, Malovini A, Moore JH, Beaulieu-Jones BK, Tibollo V, Murphy SN, Yi SL, Keller MS, Bellazzi R, Hanauer DA, Serret-Larmande A, Gutierrez-Sacristan A, Holmes JJ, Bell DS, Mandl KD, Follett RW, Klann JG, Murad DA, Scudeller L, Bucalo M, Kirchoff K, Craig J, Obeid J, Jouhet V, Griffier R, Cossin S, Moal B, Patel LP, Bellasi A, Prokosch HU, Kraska D, Sliz P, Tan ALM, Ngiam KY, Zambelli A, Mowery DL, Schiver E, Devkota B, Bradford RL, Daniar M, Daniel C, Benoit V, Bey R, Paris N, Serre P, Orlova N, Dubiel J, Hilka M, Jannot AS, Breant S, Leblanc J, Griffon N, Burgun A, Bernaux M, Sandrin A, Salamanca E, Cormont S, Ganslandt T, Gradinger T, Champ J, Boeker M, Martel P, Esteve L, Gramfort A, Grisel O, Leprovost D, Moreau T, Varoquaux G, Vie JJ, Wassermann D, Mensch A, Caucheteux C, Haverkamp C, Lemaitre G, Bosari S, Krantz ID, South A, Cai T, Kohane IS. International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium. NPJ digital medicine 2020.

Yuan W, Beaulieu-Jones BK, Yu KH, Lipnick SL, Palmer N, Loscalzo J, Cai T, Kohane IS. Temporal bias in case-control design: preventing reliable predictions of the future. Nature communications 2021.