Evidence map›Paper›PMID 17600100›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA

AEGIS: a robust and scalable real-time public health surveillance system.

Ben Y Reis, Chaim Kirby, Lucy E Hadden, Karen Olson, Andrew J McMurry, James B Daniel, Kenneth D Mandl

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Observational
  4. Review
  5. Article
  6. An i2b2-based, generalizable, open source, self-scaling chronic disease registry.Journal of the American Medical Informatics Association : JAMIA · 2013
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review of methods for space-time disease surveillance.Spatial and spatio-temporal epidemiology · 2010
    Review
  12. Review of software for space-time disease surveillance.International journal of health geographics · 2010
    Review
  13. CASE: a framework for computer supported outbreak detection.BMC medical informatics and decision making · 2010
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Ben Y ReisChildren's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA. reis@mit.edu
Chaim Kirby
Lucy E Hadden
Karen Olson
Andrew J McMurry
James B Daniel
Kenneth D Mandl

Funding

Disease Surveillance in Real Time: Geotemporal MethodsR01LM007677 · NLM · CHILDREN'S HOSPITAL BOSTON · PI MANDL, KENNETH D. · 2003 to 2009
$2.9M
Scaling Biosense: Advanced Informatics Solution for Critical ProblemsR01PH000040 · PH · CHILDREN'S HOSPITAL BOSTON · PI REIS, BEN Y · 2005 to 2007
$928k
RESEARCH SUPPORT SERVICES FOR UMLS METATHESAURUSN01LM033515 · NLM · LEXICAL TECHNOLOGY, INC. · PI TUTTLE, MARK S. · 1993 to 1997
–
NLM NIH HHS 5 R01 LM007677-04NLM NIH HHS N01-LM-3-3515NLM NIH HHS R01 LM007677PHPPO CDC HHS 1 R01 PH000040-01PHPPO CDC HHS R01 PH000040
6 · The paper itself

Abstract

In this report, we describe the Automated Epidemiological Geotemporal Integrated Surveillance system (AEGIS), developed for real-time population health monitoring in the state of Massachusetts. AEGIS provides public health personnel with automated near-real-time situational awareness of utilization patterns at participating healthcare institutions, supporting surveillance of bioterrorism and naturally occurring outbreaks. As real-time public health surveillance systems become integrated into regional and national surveillance initiatives, the challenges of scalability, robustness, and data security become increasingly prominent. A modular and fault tolerant design helps AEGIS achieve scalability and robustness, while a distributed storage model with local autonomy helps to minimize risk of unauthorized disclosure. The report includes a description of the evolution of the design over time in response to the challenges of a regional and national integration environment.

Indexed as

BioterrorismDisease OutbreaksPublic Health InformaticsCommunicable DiseasesComputer SystemsHumansMassachusettsPopulation Surveillance

Identifiers

PMID17600100
PMCPMC1975800

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.