Aberration Detection

The Veterans Health Administration (VHA) uses the Electronic Surveillance System for the Early Notification of Community-based Epidemics to detect disease outbreaks and other health-related events earlier than other forms of surveillance. Although Veterans may use any VHA facility in the world, the strongest predictor of which health care facility is accessed is geographic proximity to the patient's residence. A number of outbreaks have occurred in the Veteran population when geographically separate groups convened in a single location for professional or social events. One classic example was the initial Legionnaire's disease outbreak, identified among participants at the Legionnaire's convention in Philadelphia in the late 1970s. Numerous events involving travel by large Veteran (and employee) populations are scheduled each year.

Objective

To develop an algorithm to identify disease outbreaks by detecting aberrantly large proportions of patient residential ZIP codes outside a health care facility catchment area.

Influenza is a serious disease that seasonality causes substantial but varying morbidity and mortality. In Taiwan, estimates of the influenza mortality burden were based on post-hoc analyses of national mortality statistics and not available until at least six months after the corresponding epidemic. Timely monitoring and early detection of influenza-associated excess mortality can guide antiviral or vaccine interventions and help healthcare capacity planning. Beginning April 2009, Taiwan Centers for Disease Control has been collaborating with the Department of Health Office of Statistics to develop an automated system for real-time pneumonia and influenza (P&I) mortality surveillance.

Objective 

To develop and evaluate a nationwide automated system for early detection of aberrations and real-time monitoring of P&I mortality in Taiwan.

Adverse drug events (ADEs) are a significant source of morbidity and mortality. The majority of post-marketing surveillance for ADEs is passive. Information regarding ADEs is reported to the medical community in peer-reviewed journals. However, in most cases there is significant lag in the publication of peer-reviewed articles concerning ADEs. Within medical journals, our intuition is that letters to the editor may provide the earliest reports of ADEs. They often report single case reports or a collection of cases and usually precede more formal investigations and reports. Although these letters may contain useful and timely information, the challenge is that letters to the editor may be "buried" inside print journals. Furthermore, they may be more difficult to find and access even when using electronic searches because unlike other published reports, there is no corresponding abstract to view. Due to the lack of an abstract, detection depends almost exclusively upon words in a title, or manually applied Medical Subject Headings (MeSH). We propose that searching the full text of letters to the editor can provide a faster and perhaps more complete detection of ADEs compared to searches based on MeSH terms or titles alone.

Objective

Our objective was to explore the intuition that letters to the editor in leading medical journals contain early signals about adverse drug events. We explored this with letters in two leading journals.

Recent health events in France, such as the dramatic excess of mortality occurred during the 2003 heat wave showed the need for a better provision of information to health authorities. A new syndromic surveillance system based on the recording of general practitioner’s visits by SOS Médecins has been developed by the Aquitaine Regional Epidemiology unit (Cire).

Objective

To describe the surveillance system based on SOS Medecins data, the first GP emergency and healthcare network in France and to show the utility and validity of this data source as a real-time syndromic surveillance system.

Many syndromic surveillance systems have been developed and are operational, yet lack concise guidelines for investigating and conducting followups on daily alarms. Daily emergency department visits from six reporting hospitals in the Duval County area are assessed and classified into a BioDefend (BD) system entry by triage personnel. Alarms are categorized into alerts, 3 SD above a 30 day rolling mean, or warnings, 2-3 SD above the mean. Signals are monitored and in response, public health investigations and recommended interventions are initiated.

Objective

To evaluate the protocol that the Duval County Health Department (DCHD) epidemiology staff uses to respond to BD syndromic surveillance system alarms. The response protocol utilizes all signals detected by BD and its secondary resources, within the DCHD jurisdiction.

One of the first county-wide syndromic surveillance systems in the nation, the Syndromic Tracking and Reporting System (STARS) has been in operation since 11/01/2001, and now covers Hillsborough, Pinellas and Collier counties. STARS uses hospital emergency department visit data to detect aberrations of non-specific syndromes and serves as an earlier warning system for public health threats. Patient’s syndrome is collected upon arrival, separately from routine collection of clinical and administrative data; but in some hospitals the process is being streamlined with routine data collection. Aberration detection is done twice daily using the statistical system EARS developed by the CDC. Upon flagging of an aberration, follow-up investigation is conducted to verify cases, and identify source of exposure following a sequence of decision procedure. After several years of operation and some instituted enhancements, a systematic evaluation was called to (1) assess if STARS has met the operation specifications and (2) characterize system efficacy and effectiveness.

Objective

To evaluate STARS with respect to quality of syndrome diagnoses, timeliness and completeness of data collection and processing, performance of aberration detection methods, and aberration investigation.

Use of robust and broadly applicable statistical alerting methods is essential for a public health Biosurveillance system. We compared several algorithms related to the Early Aberration Reporting System C2 (adaptive control chart) method for practical detection sensitivity and timeliness using a realistic but stochastic signal inject strategy with a variety of data streams. The comparison allowed detail examination of strategies for adjusting daily syndromic counts for day-of-week effects and the total daily volume of facility visits. Adjustment for the total visit volume allows monitoring of surrogate rates instead of just counts, and the use of real data with both syndromic and total visit counts enables this adjustment.

Objective

We compared several aberration detection algorithms using a set of syndromic data streams from a large number of treatment facilities in the CDC Biosense 1.0 system. A realistic signal injection strategy was devised to compare different ways of adjusting for total facility visits and background day-of-week effects.