Syndromic Surveillance

Preface

Effective public health surveillance is essential for detecting and responding to emerging public health threats, including terrorism and emerging infectious diseases. New surveillance methods are being developed and tested to improve the timeliness and completeness of detection of disease outbreaks. One promising set of approaches is syndromic surveillance, in which information about health events that precede a firm clinical diagnosis is captured early and rapidly from existing, usually electronic, data sources, and analyzed frequently to detect signals that might indicate an outbreak requiring investigation.

To provide a forum for scientists and practitioners to report on progress in developing and evaluating syndromic surveillance systems, the New York City Department of Health and Mental Hygiene, the New York Academy of Medicine, and CDC convened the second annual National Syndromic Surveillance Conference in New York City during October 23--24, 2003. The conference, supported by the Alfred P. Sloan Foundation, was attended by more than 460 public health practitioners and researchers, who had the opportunity to hear 41 oral presentations and view 50 poster presentations.

The original papers and posters for this conference were chosen by a scientific program committee after a review of submitted abstracts. Senior researchers in the field were also invited to address key concerns in surveillance for early detection of outbreaks. All participants who presented papers or posters at either the conference or at a preconference workshop were invited to submit manuscripts based on their presentations for publication in this Morbidity and Mortality Weekly Report Supplement. Each manuscript was then reviewed by at least two peer reviewers and final publication decisions were made by an editorial committee. Many of the articles are considerably different from the material originally presented at the conference. Certain authors updated their findings, and others were asked to revise their papers into descriptions of syndromic surveillance systems. Other presenters chose to submit only abstracts. Papers are presented here in the following order: system descriptions, research methods, evaluation, and public health practice.

In addition to these reports, other resources on syndromic surveillance are available. The proceedings of the 2002 National Syndromic Surveillance Conference were published in the Journal of Urban Health (accessible at http://jurban.oup journals.org/content/suppl_1/index.shtml). In May 2004, a revisedFramework for Evaluating Public Health Surveillance Systems for Early Detection of Outbreaks was published (MMWR 2004;53[No. RR-5]). An annotated bibliography of published papers and other Internet-accessible materials has been developed and is maintained monthly on a CDC website (http://www.cdc.gov/epo/dphsi/syndromic/index.htm). An Internet-based forum (http://syndromic.forum.cdc.gov) was established for discussion of topics related to syndromic surveillance and was used to distribute answers to audience questions raised at the conference. A related forum (http://surveval.forum.cdc. gov) has been maintained for discussion of topics related to surveillance system evaluation. Finally, the website of the Annual Syndromic Surveillance Conferences (http://www. syndromic.org) includes links to recent news and scientific articles about syndromic surveillance, oral and poster presentations and workshop materials from past conferences, and notices of upcoming conferences. The third National Syndromic Surveillance Conference is planned for November 3--4, 2004, in Boston, Massachusetts.

The editorial committee acknowledges the work of the scientific planning committee: Dennis Cochrane, Christine Hahn, Patrick Kelley, Martin Kulldorff, John Loonsk, David Madigan, Richard Platt, and Don Weiss. The committee is also grateful for the support and efforts of the following staff members in conducting this conference and developing this Supplement: Alan Fleischman, Irv Gertner, and Jessica Hartman, New York Academy of Medicine; Rick Heffernan, New York Department of Health and Mental Hygiene; and Alan Davis, Division of Public Health Surveillance and Informatics, Epidemiology Program Office, CDC; Valerie Kokor, Division of International Health, Epidemiology Program Office; and Stephanie Malloy, Jeffrey Sokolow, and Malbea LaPete, MMWR, Epidemiology Program Office, CDC. Special thanks are given to JoEllen DeThomasis, Division of Applied Public Health Training and Division of Public Health Surveillance and Informatics, Epidemiology Program Office, CDC, who coordinated the preparation of these reports.

--- The Editorial Committee

Patients’ chief complaints (CCs) as a common data source, has been widely used in syndromic surveillance due to its timeliness, accuracy and availability. For automated syndromic surveillance, CCs always classified into predefined syndromic categories to facilitate subsequent data aggregation and analysis. However, in rural China, most outpatient doctors recorded the information of patients (e.g. CCs) into clinic logs manually rather than computers. Thus, more convenient surveillance method is needed in the syndromic surveillance project (ISSC). And the first and important thing is to select the targeted symptoms/syndromes.

Objective

To select the potential targeted symptoms/syndromes as early warning indicators for epidemics or outbreaks detection in rural China

In 2010, there were 4,796 snake bite exposures reported to Poison Centers nationwide (1). Health care providers frequently request help from poison centers regarding snake envenomations due to the unpredictability and complexity of prognosis and treatment. The Missouri Poison Center (MoPC) maintains a surveillance database keeping track of every phone call received. ESSENCE, a syndromic surveillance system used in Missouri, enables surveillance by chief complaint of 84 different emergency departments (ED) in Missouri (accounting for approximately 90% of all ED visits statewide). Since calling a poison center is voluntary for health care providers, poison center data is most likely an underestimation of the true frequency of snake envenomations. Comparing MoPC and ESSENCE data for snake envenomations would enable the MoPC to have a more accurate depiction of snake bite frequency in Missouri and to see where future outreach of poison center awareness should be focused.

Objective

This study intends to use two different surveillance systems available in Missouri to explore snake bite frequency and geographic distribution.

Surveillance of influenza in the US, UK and other countries is based primarily on measures of influenza-like illness (ILI), through a combination of syndromic surveillance systems, however, this method may not capture the full spectrum of illness or the total burden of disease. Care seeking behaviour may change due to public beliefs, for example more people in the UK sought care for pH1N1 in the summer of 2009 than the winters of 2009/2010 and 2010/2011, resulting in potential inaccurate estimates from ILI. There may also be underreporting of or delays in reporting ILI in the community, for example in the UK those with mild illness are less likely to see a GP, and visits generally occur two or more days after onset of symptoms. Work absences, if the reason is known, could fill these gaps in detection.

Objective

To address the feasibility and efficiency of a novel syndromic surveillance method, monitoring influenza-like absence (ILA) among hospital staff, to improve national ILI surveillance and inform local hospital preparedness.

The final rules released by the Centers for Medicare and Medicaid Services specified the initial criteria for eligible hospitals to qualify for an incentive payment by demonstrating meaningful use of certified Electronic Health Record (EHR) technology. Syndromic surveillance reporting is one of three public health objectives that eligible hospitals can choose for stage 1. The PHIN messaging guide for syndromic surveillance was published for hospitals to construct emergency department data using Admit Discharge Transfer (ADT) messages, with the minimum dataset that is standard among hospitals and public health agencies. Currently New York hospitals are reporting emergency department (ED) visit data to the NY syndromic surveillance (SS) system. Patient chief complaint data are monitored for trends of illness at the community level in order to detect possible outbreaks and situational awareness.

Objective: 

To evaluate the readiness and timeliness of ED data submitted by hospitals following PHIN syndromic surveillance messaging guide and to evaluate the availability of minimum data elements. To validate the accuracy and completeness of data from ADT messages compared with data currently reported to the NY syndromic surveillance system.

 

In November of 2011 BioSense 2.0 went live to provide tools for public health departments to process, store, and analyze meaningful use syndromic surveillance data. In February of 2012 ESSENCE was adapted to support meaningful use syndromic surveillance data and was installed on the Amazon GovCloud. Tarrant County Public Health Department agreed to pilot the ESSENCE system and evaluate its performance compared to a local version ESSENCE they currently used. The project determined the technical feasibility of utilizing the Internet cloud to perform detailed public health analysis, necessary changes needed to support meaningful use syndromic surveillance data, and any public health benefits that could be gained from the technology or data.

Objective:

This project represents collaboration among CDC’s BioSense Program, Tarrant County Public Health and the ESSENCE Team at the Johns Hopkins University APL. For over six months the Tarrant County Public Health Department has been sending data through the BioSense 2.0 application to a pilot version of ESSENCE on the Amazon GovCloud. This project has demonstrated the ability for local hospitals to send meaningful use syndromic surveillance data to the Internet cloud and provide public health officials tools to analyze the data both using BioSense 2.0 and ESSENCE. The presentation will describe the tools and techniques used to accomplish this, an evaluation of how the system has performed, and lessons learned for future health departments attempting similar projects.

 

Syndromic surveillance data has predominantly been used for surveillance of infectious disease and for broad symptom types that could be associated with bioterrorism. There has been a growing interest to expand the uses of syndromic data beyond infectious disease. Because many of these conditions are specific and can be swiftly diagnosed (as opposed to infectious agents that require a lab test for confirmation) there could be added value in using the ICD9 ED discharge diagnosis field collected by SS. However, SS discharge diagnosis data is not complete or as timely as chief complaint data. Therefore, for the time being SS chief complaint data is relied on for non-infectious disease surveillance. SPARCS data are based on clinical diagnoses and include information on final diagnosis, providing a means for comparing the chief complaint (from SS) to a diagnosis code (from SPARCS), for evaluating how well the syndrome is captured by SS and for assessing if it would be advantageous to get SS ED diagnosis codes in a more timely and complete manner.

Objective:

To evaluate several non-infectious disease related syndromes that are based on chief complaint (cc) emergency department (ED) syndromic surveillance (SS) data by comparing these with the New York Statewide Planning and Research Cooperative System (SPARCS) clinical diagnosis data. In particular, this work compares SS and SPARCS data for total ED visits and visits associated with three noninfectious disease syndromes, namely asthma, oral health and hypothermia.

 

ASPR deploys clinical assets, including an EMR system, to the ground per state requests during planned and no-notice events. The analysis of patient data collected by deployed federal personnel is an integral part of ASPR and FDOH’s surveillance efforts. However, this surveillance can be hampered by the logistical issues of field work in a post-disaster environment leading to delayed analysis and interpretation of these data to inform decision makers at the federal, state, and local levels. FDOH operates ESSENCE-FL, a multi-tiered, automated, and secure web-based application for analysis and visualization of clinical data. The system is accessible statewide by FDOH staff as well as by hospitals that participate in the system. To improve surveillance ASPR and FDOH engaged in a pilot project whereby EMR data from ASPR would be sent to FDOH in near realtime during the 2012 hurricane season and the 2012 RNC. This project is in direct support of Healthcare Preparedness Capability 6, Information Sharing, and Public Health Preparedness Capability 13, Public Health Surveillance and Epidemiological Investigation.

Objective:

U.S. Department of Health and Human Services (HHS) Office of the Assistant Secretary for Preparedness and Response (ASPR) partnered with the Florida Department of Health (FDOH), Bureau of Epidemiology, to implement a new process for the unidirectional exchange of electronic medical record (EMR) data when ASPR clinical assets are operational in the state following a disaster or other response event. The purpose of the current work was to automate the exchange of data from the ASPR electronic medical record system EMR-S into the FDOH Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE-FL) system during the 2012 Republican National Convention (RNC).