Surveillance Systems

On June 22, 2007 increases in over-the-counter (OTC) electrolyte and child anti-fever medication sales were detected through routine OTC surveillance. Increases in emergency department (ED) data for gastrointestinal (GI) illness among <5 year olds were observed on June 23 and 24. Further analyses indicated clustering within one borough of NYC, with three EDs having most of the visits. Because NYC has had limited success in detecting spatial outbreaks using syndromic surveillance in the past, an investigation was not immediately initiated.

DOHMH was notified of a multi-state outbreak of S. wandsworth suspected to be associated with the snack food Veggie Booty® on June 26. Cases were predominantly young children and included 8 confirmed cases among NYC residents with onset dates from March 4 – May 19.

Objective

To determine whether increases in GI illness detected through OTC drug sales and ED syndromic surveillance were linked to a multi-state outbreak of S. wandsworth associated with the consumption of Veggie Booty® snack food.

Centre for Health Protection (CHP) plans to conduct a pilot project in developing a syndromic surveillance system using data from Emergency Departments (ED) in Hong Kong. This is part of the Communicable Disease Information System initiative, which aims at enhancing the capability of Hong Kong in the control and prevention of communicable diseases.

Objective

This paper describes how the CHP of Hong Kong designed and deployed an online interactive system that uses the data from ED for syndromic surveillance.

While there has been some work to evaluate different data sources for syndromic surveillance of influenza, no one has yet assessed the utility of simultaneously restricting data to specific visit settings and patient age-groups using data drawn from a single source population. Furthermore, most studies have been limited to the emergency departments (ED), with few evaluating the timeliness of data from community-based primary care.

Objective

Using physician billing data from a single source population, we aimed to compare age-group and visit setting specific patterns in the timing of patients presenting to community-based healthcare settings and hospital ED for influenza-like-illnesses (ILI). We thus evaluate the utility of focusing on particular age-groups and care settings for syndromic surveillance of ILI in ambulatory care.

Syndromic surveillance systems can detect increases in respiratory and gastrointestinal illness, but diagnosis of etiologic agents can be delayed due to difficult, time-consuming identification and low rates of testing for viral pathogens. Rapid diagnostic (RD) assays may aid in early identification and characterization of large outbreaks by allowing decision makers to “rule in” or “rule out” potential etiologic agents.

Objective

This paper describes preliminary results and implementation lessons learned from a RD testing pilot project. The project’s purpose is to prospectively collect diagnostic data on common causes of community-wide illness in order to supplement syndromic surveillance in New York City.

Every public health monitoring operation faces important decisions in its design phase. These include information sources to be used, the aggregation of data in space and time, the filtering of data records for required sensitivity, and the design of content delivery for users. Some of these decisions are dictated by available data limitations, others by objectives and resources of the organization doing the

surveillance. Most such decisions involve three characteristic tradeoffs: how much to monitor for exceptional vs customary health threats, the level of aggregation of the monitoring, and the degree of automation to be used.

The first tradeoff results from heightened concern for bioterrorism and pandemics, while everyday threats involve endemic disease events such as seasonal outbreaks. A system focused on bioterrorist attacks is scenario-based, concerned with unusual diagnoses or patient distributions, and likely to include attack hypothesis testing and tracking tools. A system at the other end of this continuum has broader syndrome groupings and is more concerned with general anomalous levels at manageable alert rates. 

Major aggregation tradeoffs are temporal, spatial, and syndromic. Bioterrorism fears have shortened the time scale of health monitoring from monthly or weekly to near-real-time. The spatial scale of monitoring is a function of the spatial resolution of data recorded and allowable for use as well as the monitoring institution’s purview and its capacity to collect, analyze and investigate localized outbreaks.

Automation tradeoffs involve the use of data processing to collect information, analyze it for anomalies, and make investigation and response decisions. The first of these uses has widespread acceptance, while in the latter two the degree of automation is a subject of ongoing controversy and research. To what degree can human judgment in alerting/response decisions be automated? What are the level and frequency of human inspection and adjustment? Should monitoring frequency change during elevated threat conditions?

All of these decisions affect monitoring tools and practices as well as funding for related research.

Objective

This purpose of this effort is to show how the goals and capabilities of health monitoring institutions can shape the selection, design, and usage of tools for automated disease surveillance systems.

In the Northern part of Norway, all general practitioners (GPs) and hospitals use electronic health record systems. They are all connected via an independent secure IP-network called the Norwegian Health Network which enables electronic communication between all institutions involved in disease prevention and healthcare.

Objective

The Norwegian Centre for Telemedicine plans to establish a peer-to-peer based surveillance  network between all GPs, laboratories, accident and emergency units, and other relevant health providers and authorities in Northern Norway. This paper briefly describes the architecture and components of the system and the motivation for using this approach.

National Retail Data Monitor (NRDM) is a public health surveillance tool that collects and analyzes daily sales data for over-the-counter (OTC) health-care products from >15,000 retail stores nationwide. This is a system developed by Real-Time Outbreak and Disease Surveillance Laboratory. NRDM has been in continuous operation since December 2002. The Washoe County District Health Department implemented this system in November 2003. During initial phase of implementation, NRDM was used retrospectively on as-needed basis. Since September 2004, monitoring NRDM for volume of OTC sales for anti-diarrhea medications became a daily routine.

Objective

The objective of this paper is to evaluate the role of NRDM in gastrointestinal illness outbreak investigation in Washoe County, Nevada. The evaluation will focus on usefulness of system, sensitivity, positive predictive value, representativeness, and timeliness followed by updated CDC guidelines.

In 2004, the NSW Public Health Real-time Emergency Department Surveillance System operating in and around Sydney, Australia signalled a large-scale increase in Emergency Department (ED) visits for gastrointestinal illness (GI). A subsequent alarming state-wide rise in institutional gastroenteritis outbreaks was also seen through conventional outbreak surveillance.

Objectives

To examine the association between short-term variation in ED visits for GI with short-term variation in institutional gastroenteritis outbreaks and thus to evaluate whether syndromic surveillance of GI through EDs provides early warning for institutional gastroenteritis outbreaks.

Influenza is an important public health problem associated with considerable morbidity and mortality. A disease traditionally monitored via legally mandated reporting, researchers have identified alternative data sources for influenza surveillance. The hospital environment presents a unique opportunity for comparative studies of biosurveillance data with high quality and various level of clinical information ranging from provisional diagnoses to laboratory confirmed cases. This study investigated the alert times achievable from hospital-based sources relative to reporting of influenza cases. The earlier detection of influenza could potentially provide more advanced warning for the medical community and the early implementation of precautionary measures in vulnerable populations.

Objective

To determine the relative alert time of influenza surveillance based on hospital data sources compared to notifiable disease reporting.

The New York State Department of Health (NYSDOH) Syndromic Surveillance System consists of five components: 1. Emergency Department (ED) Phone Call System monitors unusual events or clusters of illnesses in the EDs of participating hospitals; 2. Electronic ED Surveillance System monitors ED chief complaint data; 3. Medicaid data system monitors Medicaid-paid over-the-counter and prescription medica-tions; 4. National Retail Data Monitor/Real-time Outbreak and Disease Surveillance System monitors OTC data; 5. CDC’s BioSense application monitors Department of Defense and Veterans Administration outpatient care clinical data (ICD-9-CM diag-noses and CPT procedure codes), and LabCorp test order data.

Objective

This poster presentation provides an overview of the NYSDOH Syndromic Surveillance System, including data sources, analytic algorithms, and resulting reports that are posted on the NYSDOH Secure Health Commerce System for access by state, regional, county, and hospital users.