During the onset of 2009 pandemic influenza A (H1N1) (pH1N1), the New York City Department of Health and Mental Hygiene implemented a pilot respiratory virus surveillance system.
We evaluated the performance of this pilot system, which linked electronic health record (EHR) clinical, epidemiologic, and diagnostic data to monitor influenza-like illness (ILI) in the community.
Surveillance was conducted at 9 community health centers with EHRs. Clinical decision support system alerts encouraged diagnostic testing of patients. Rapid influenza diagnostic testing (RIDT) and multiplex polymerase chain reaction assay (MassTag PCR) were performed sequentially.
Nine Institute for Family Health (IFH) clinics in Manhattan and the Bronx during May 26 to June 30, 2009, the pH1N1 outbreak peak.
Adult and pediatric patients presenting to IFH clinics during May 26 to June 30, 2009.
By using Centers for Disease Control and Prevention guidelines, we evaluated the system's completeness, sensitivity, timeliness, and epidemiologic usefulness.
Of 537 ILI visits (5.7% of all visits), 17% underwent diagnostic testing. Of the 132 specimens with both a RIDT and MassTag PCR result, 90 (68%) had a MassTag PCR-identified respiratory virus, most commonly pH1N1 (n = 69; 77%). Of the 81 specimens that met the ILI case definition, 58 (72%) were positive for a respiratory virus tested for by MassTag PCR; 48 (59%) were positive for pH1N1. Ninety-four percent of ILI patients positive for pH1N1 were 45 years or younger. Sensitivity and specificity of RIDT (29% and 94%) and ILI case definition (70% and 48%) for pH1N1 were calculated using MassTag PCR as the standard. Results of RIDT took a median of 6 days.
Despite low RIDT sensitivity for pH1N1 and limited timeliness, integration of EHR and diagnostic data has potential to provide valuable epidemiologic information, guide public health response, and represents a new model for community surveillance for influenza and respiratory viruses.
During the onset of 2009 pandemic H1N1, the New York City Department of Health and Mental Hygiene implemented a pilot respiratory virus surveillance system that linked electronic health record clinical, epidemiologic, and diagnostic data to monitor influenza-like illness in the community. Despite low rapid influenza diagnostic test sensitivity and limited timeliness, this integration can provide valuable epidemiologic information and guide public health response.
Division of Epidemiology (Drs Al-Samarrai, Begier, and Greene) and Division of Health Care Access and Improvement (Dr Wu and Ms Plagianos), New York City Department of Health and Mental Hygiene, New York, NY; Epidemic Intelligence Service Field Assignments Branch, Centers for Disease Control and Prevention, Atlanta, GA (Dr Al-Samarrai); Institute for Family Health, New York, NY (Drs Lurio and Calman); Center for Infection and Immunity, Mailman School of Public Health, Columbia University, New York, NY (Drs Tokarz, Briese, and Lipkin); and Office of the National Coordinator for Health Information Technology, United States Department of Health and Human Services, Washington, DC (Dr Mostashari).
Correspondence: Teeb Al-Samarrai, MD, MS, Santa Clara County Public Health Department, Tuberculosis Control Program, 976 Lenzen Ave, San Jose, CA 95126 (email@example.com) Or Thomas Briese, PhD, Center for Infection and Immunity, Mailman School of Public Health, Columbia University, 722 W 168th St, 17th floor, New York, NY 10032 (firstname.lastname@example.org).
At the time this study was conducted, F.M. was at the post of Assistant Commissioner in the Division of Health Care Access and Improvement, New York City Department of Health and Mental Hygiene, New York.
The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention, the United States Department of Health and Human Services, or the authors' affiliated institutions. Use of trade names is for identification only and does not imply endorsement by any of the groups named here.
The authors extend their gratitude to Julie Magri for providing critical input and reviewing the manuscript and Margaret Millstone, Rhoda Schlamm, and Darian White for their assistance in manuscript preparation. This work was partially supported by the US Department of Defense and Department of Homeland Security grant no 2009-OH-091-ES0001.
The authors declare no conflicts of interest.