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Signs of the 2009 Influenza Pandemic in the New York-Presbyterian Hospital Electronic Health Records
Authors:Hossein Khiabanian  Antony B. Holmes  Brendan J. Kelly  Mrinalini Gururaj  George Hripcsak  Raul Rabadan
Affiliation:1. Department of Biomedical Informatics, Columbia University College of Physicians and Surgeons, New York, New York, United States of America.; 2. Center for Computational Biology and Bioinformatics, Columbia University College of Physicians and Surgeons, New York, New York, United States of America.; 3. Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York, United States of America.;Tulane University, United States of America
Abstract:

Background

In June of 2009, the World Health Organization declared the first influenza pandemic of the 21st 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 Results

We 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.

Conclusion

The 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.
Keywords:
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