OBJECTIVE: This study sought to define a scalable architecture to support the National Health Information Network (NHIN). This architecture must concurrently support a wide range of public health, research, and clinical care activities. STUDY DESIGN: The architecture fulfils five desiderata: (1) adopt a distributed approach to data storage to protect privacy, (2) enable strong institutional autonomy to engender participation, (3) provide oversight and transparency to ensure patient trust, (4) allow variable levels of access according to investigator needs and institutional policies, (5) define a self-scaling architecture that encourages voluntary regional collaborations that coalesce to form a nationwide network. RESULTS: Our model has been validated by a large-scale, multi-institution study involving seven medical centers for cancer research. It is the basis of one of four open architectures developed under funding from the Office of the National Coordinator of Health Information Technology, fulfilling the biosurveillance use case defined by the American Health Information Community. The model supports broad applicability for regional and national clinical information exchanges. CONCLUSIONS: This model shows the feasibility of an architecture wherein the requirements of care providers, investigators, and public health authorities are served by a distributed model that grants autonomy, protects privacy, and promotes participation.
OBJECTIVE: This study sought to define a scalable architecture to support the National Health Information Network (NHIN). This architecture must concurrently support a wide range of public health, research, and clinical care activities. STUDY DESIGN: The architecture fulfils five desiderata: (1) adopt a distributed approach to data storage to protect privacy, (2) enable strong institutional autonomy to engender participation, (3) provide oversight and transparency to ensure patient trust, (4) allow variable levels of access according to investigator needs and institutional policies, (5) define a self-scaling architecture that encourages voluntary regional collaborations that coalesce to form a nationwide network. RESULTS: Our model has been validated by a large-scale, multi-institution study involving seven medical centers for cancer research. It is the basis of one of four open architectures developed under funding from the Office of the National Coordinator of Health Information Technology, fulfilling the biosurveillance use case defined by the American Health Information Community. The model supports broad applicability for regional and national clinical information exchanges. CONCLUSIONS: This model shows the feasibility of an architecture wherein the requirements of care providers, investigators, and public health authorities are served by a distributed model that grants autonomy, protects privacy, and promotes participation.
Authors: Kenneth D Mandl; J Marc Overhage; Michael M Wagner; William B Lober; Paola Sebastiani; Farzad Mostashari; Julie A Pavlin; Per H Gesteland; Tracee Treadwell; Eileen Koski; Lori Hutwagner; David L Buckeridge; Raymond D Aller; Shaun Grannis Journal: J Am Med Inform Assoc Date: 2003-11-21 Impact factor: 4.497
Authors: Fu-Chiang Tsui; Jeremy U Espino; Virginia M Dato; Per H Gesteland; Judith Hutman; Michael M Wagner Journal: J Am Med Inform Assoc Date: 2003-06-04 Impact factor: 4.497
Authors: Ben Y Reis; Chaim Kirby; Lucy E Hadden; Karen Olson; Andrew J McMurry; James B Daniel; Kenneth D Mandl Journal: J Am Med Inform Assoc Date: 2007-06-28 Impact factor: 4.497
Authors: Griffin M Weber; Shawn N Murphy; Andrew J McMurry; Douglas Macfadden; Daniel J Nigrin; Susanne Churchill; Isaac S Kohane Journal: J Am Med Inform Assoc Date: 2009-06-30 Impact factor: 4.497
Authors: John H Holmes; Thomas E Elliott; Jeffrey S Brown; Marsha A Raebel; Arthur Davidson; Andrew F Nelson; Annie Chung; Pierre La Chance; John F Steiner Journal: J Am Med Inform Assoc Date: 2014-03-28 Impact factor: 4.497
Authors: Stephen B Johnson; Glen Whitney; Matthew McAuliffe; Hailong Wang; Evan McCreedy; Leon Rozenblit; Clark C Evans Journal: J Am Med Inform Assoc Date: 2010 Nov-Dec Impact factor: 4.497
Authors: Rebecca S Jacobson; Michael J Becich; Roni J Bollag; Girish Chavan; Julia Corrigan; Rajiv Dhir; Michael D Feldman; Carmelo Gaudioso; Elizabeth Legowski; Nita J Maihle; Kevin Mitchell; Monica Murphy; Mayurapriyan Sakthivel; Eugene Tseytlin; JoEllen Weaver Journal: Cancer Res Date: 2015-12-15 Impact factor: 12.701