AEGIS: A Robust and Scalable Real-time Public Health Surveillance System

Reis, Ben Y.; Kirby, Christopher; L, Hadden; Olson, Karen L.; McMurry, Andrew; Daniel, James; Mandl, Kenneth D.

doi:10.1197/jamia.m2342

Cited by 38 publications

(26 citation statements)

References 26 publications

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“…SHRINE is designed to reuse information captured during patient care[30], [31], to protect patient privacy[32], to query heterogeneous health systems simultaneously, and to scale to nation-wide participation[33]. SHRINE aims to serve multiple study needs such as cohort discovery[34] and population scale measurements[35], [36].…”

Section: Methodsmentioning

confidence: 99%

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SHRINE: Enabling Nationally Scalable Multi-Site Disease Studies

et al. 2013

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Results of medical research studies are often contradictory or cannot be reproduced. One reason is that there may not be enough patient subjects available for observation for a long enough time period. Another reason is that patient populations may vary considerably with respect to geographic and demographic boundaries thus limiting how broadly the results apply. Even when similar patient populations are pooled together from multiple locations, differences in medical treatment and record systems can limit which outcome measures can be commonly analyzed. In total, these differences in medical research settings can lead to differing conclusions or can even prevent some studies from starting. We thus sought to create a patient research system that could aggregate as many patient observations as possible from a large number of hospitals in a uniform way. We call this system the ‘Shared Health Research Information Network’, with the following properties: (1) reuse electronic health data from everyday clinical care for research purposes, (2) respect patient privacy and hospital autonomy, (3) aggregate patient populations across many hospitals to achieve statistically significant sample sizes that can be validated independently of a single research setting, (4) harmonize the observation facts recorded at each institution such that queries can be made across many hospitals in parallel, (5) scale to regional and national collaborations. The purpose of this report is to provide open source software for multi-site clinical studies and to report on early uses of this application. At this time SHRINE implementations have been used for multi-site studies of autism co-morbidity, juvenile idiopathic arthritis, peripartum cardiomyopathy, colorectal cancer, diabetes, and others. The wide range of study objectives and growing adoption suggest that SHRINE may be applicable beyond the research uses and participating hospitals named in this report.

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Section: Methodsmentioning

confidence: 99%

“…For example, a European public-private partnership is evaluating the SHRINE platform to locate patient cohorts for clinical trials. There is also a strong potential for using SHRINE to locate human biospecimens for genomic studies[31], [52], [53], monitor population health [35], [54], and detect adverse medication events [36], [55], [56].…”

Section: Methodsmentioning

confidence: 99%

SHRINE: Enabling Nationally Scalable Multi-Site Disease Studies

et al. 2013

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“…The focus was on realtime systems that could take daily Health Level 7 feeds (i.e., directly from clinical information systems) of free text patient chief complaints from emergency departments, in a process called syndromic surveillance [ 22 ]. These systems, established as CDC-funded Public Health Informatics Centers of Excellence, were the Electronic Surveillance System for the Early Notifi cation of Community-based Epidemics, or ESSENCE [ 26 ], Real-Time Outbreak and Disease Surveillance, or RODS [ 42 ], and Automated Epidemiological Geotemporal Integrated Surveillance, or AEGIS [ 35 ]. The success of these systems in multiple localities stimulated the CDC's meaningful use (MU) program to include syndromic surveillance as one of its optional criteria in Stage 1 and a required criterion for Stage 2 for eligible professionals, eligible hospitals, and critical access hospitals in order to participate in incentive programs for the Medicare and Medicaid Electronic Health Record (EHR).…”

Section: Public Health Biosurveillance Systemsmentioning

confidence: 99%

Public and Personal Health Testing Systems

Collen¹,

Lehmann

2015

Health Informatics

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The explicit relationship between the clinical environment and public health dates from the 1878 Act of Congress, which authorized the U.S. Public Health Service to collect morbidity reports for quarantinable diseases. In the 1970s, hospital infection surveillance programs began to employ computer databases; in the 1980s, state health departments developed computer-based systems to monitor communicable diseases. Subsequent developments of databases and techniques such as data mining improved detection and facilitated alerts; compliance with reporting accelerated once direct connections were instituted between clinical laboratories and public health agencies. Personal health testing systems (HTS) also evolved, with the use of multiple tests in what became known as multiphasic screening. By 1965, Kaiser Permanente was using automated multiphasic health testing (AMHT) systems in two clinics in Northern California to provide systemized personal health checkups, including features described later as clinical decision support. By the early 1970s, AMHT systems had spread into many health care facilities, for a range of uses that included pre-admission screening of hospital patients and online records of outpatient encounters, both nationally and internationally. In the 1980s funding and reimbursement issues led to the termination of most AMHT programs; at Kaiser Permanente, AMHT was integrated into its larger systems. Since 2001, the CDC has funded the development of real time surveillance systems that take daily Health Level 7 feeds directly from clinical information systems as part of syndromic surveillance, a criterion in CDC's meaningful use program.

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“…Our efforts are based on two highly diffusible, open source technologies: the i2b2 informatics framework3 4 17 18 and the Shared Health Research Information Network (SHRINE) 56 18 These platforms provide a well-tested foundation for cross-institutional data aggregation within the health information sector and have been used for multi-municipality syndromic biosurveillance ( AEGIS ),7 19 cohort identification across the Harvard-affiliated hospitals ( SHRINE ),8 18 and multi-institutional neuroscientific research ( Biomedical Informatics Research Network ( BIRN )) 920 21 …”

Section: Background and Significancementioning

confidence: 99%

An i2b2-based, generalizable, open source, self-scaling chronic disease registry

Natter

Quan

Ortiz

et al. 2013

Journal of the American Medical Informatics Association

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ObjectiveRegistries are a well-established mechanism for obtaining high quality, disease-specific data, but are often highly project-specific in their design, implementation, and policies for data use. In contrast to the conventional model of centralized data contribution, warehousing, and control, we design a self-scaling registry technology for collaborative data sharing, based upon the widely adopted Integrating Biology & the Bedside (i2b2) data warehousing framework and the Shared Health Research Information Network (SHRINE) peer-to-peer networking software.Materials and methodsFocusing our design around creation of a scalable solution for collaboration within multi-site disease registries, we leverage the i2b2 and SHRINE open source software to create a modular, ontology-based, federated infrastructure that provides research investigators full ownership and access to their contributed data while supporting permissioned yet robust data sharing. We accomplish these objectives via web services supporting peer-group overlays, group-aware data aggregation, and administrative functions.ResultsThe 56-site Childhood Arthritis & Rheumatology Research Alliance (CARRA) Registry and 3-site Harvard Inflammatory Bowel Diseases Longitudinal Data Repository now utilize i2b2 self-scaling registry technology (i2b2-SSR). This platform, extensible to federation of multiple projects within and between research networks, encompasses >6000 subjects at sites throughout the USA.DiscussionWe utilize the i2b2-SSR platform to minimize technical barriers to collaboration while enabling fine-grained control over data sharing.ConclusionsThe implementation of i2b2-SSR for the multi-site, multi-stakeholder CARRA Registry has established a digital infrastructure for community-driven research data sharing in pediatric rheumatology in the USA. We envision i2b2-SSR as a scalable, reusable solution facilitating interdisciplinary research across diseases.

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AEGIS: A Robust and Scalable Real-time Public Health Surveillance System

Cited by 38 publications

References 26 publications

SHRINE: Enabling Nationally Scalable Multi-Site Disease Studies

SHRINE: Enabling Nationally Scalable Multi-Site Disease Studies

Public and Personal Health Testing Systems

An i2b2-based, generalizable, open source, self-scaling chronic disease registry

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