ArticlePloS one2010
Signs of the 2009 influenza pandemic in the New York-Presbyterian Hospital electronic health records.
Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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.
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Who cites it
7 citing papers in PubMed, 17 citations in OpenAlex.
- Data-driven discovery of seasonally linked diseases from an Electronic Health Records system.BMC bioinformatics · 2014Article
- Envisioning sophisticated electronic health records through the lens of health care reform.American journal of respiratory and critical care medicine · 2013Article
- Age distribution of influenza like illness cases during post-pandemic A(H3N2): comparison with the twelve previous seasons, in France.PloS one · 2013Article
- Characterization of a porcine intestinal epithelial cell line for influenza virus production.The Journal of general virology · 2012Article
- Usefulness of school absenteeism data for predicting influenza outbreaks, United States.Emerging infectious diseases · 2012Article
- Discovering disease associations by integrating electronic clinical data and medical literature.PloS one · 2011Article
- Fractal-like distributions over the rational numbers in high-throughput biological and clinical data.Scientific reports · 2011Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
backgroundIn June of 2009, the World Health Organization declared the first influenza pandemic of the 21(st) century, and by July, New York City's New York-Presbyterian Hospital (NYPH) experienced a heavy burden of cases, attributable to a novel strain of the virus (H1N1pdm). METHODS AND
resultsWe present the signs in the NYPH electronic health records (EHR) that distinguished the 2009 pandemic from previous seasonal influenza outbreaks via various statistical analyses. These signs include (1) an increase in the number of patients diagnosed with influenza, (2) a preponderance of influenza diagnoses outside of the normal flu season, and (3) marked vaccine failure. The NYPH EHR also reveals distinct age distributions of patients affected by seasonal influenza and the pandemic strain, and via available longitudinal data, suggests that the two may be associated with distinct sets of comorbid conditions as well. In particular, we find significantly more pandemic flu patients with diagnoses associated with asthma and underlying lung disease. We further observe that the NYPH EHR is capable of tracking diseases at a resolution as high as particular zip codes in New York City.
conclusionThe NYPH EHR permits early detection of pandemic influenza and hypothesis generation via identification of those significantly associated illnesses. As data standards develop and databases expand, EHRs will contribute more and more to disease detection and the discovery of novel disease associations.
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