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Our goal was to assess the impact of sentinel sample size and criteria for a signal on performance of daily prospective space-time permutation detection by comparing results in varying size random samples from a large health plan to results found in the full membership.

Content type: Abstract

We describe the development and implementation of a protocol for identifying syndromic signals and for assessing their value to public health departments for routine (non-bioterrorism) purposes. The specific objectives of the evaluation are to determine the predictive value positive, sensitivity... Read more

Content type: Abstract

Approximately one quarter of people treated for tuberculosis (TB) have no supporting microbiology, and thus are not detectable through laboratory reporting systems. Health departments depend upon clinicians to report these cases, but there is important underreporting. We previously described the... Read more

Content type: Abstract

To compare the ability to detect disease outbreaks of separate and combined data streams from ambulatory care and emergency department from Harvard Pilgrim Health Care.

Content type: Abstract

Electronic laboratory-based surveillance can significantly improve the diagnostic specificity and response time of traditional infectious disease surveillance. Under the project “Models of Infectious Disease Agent Study”, we wished to evaluate the application of space-time outbreak detection... Read more

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Clinician initiated reporting of notifiable conditions is often delayed, incomplete, and lacking in detail. We report on the deployment of Electronic medical record Support for Public health (ESP), a system we have created to automatically screen electronic medical record (EMR) systems for... Read more

Content type: Abstract

The utility of syndromic surveillance systems to augment health departments’ traditional surveillance for naturally occurring disease has not been prospectively evaluated.



In this interim report we describe the signals detected by a real-time ambulatory care-... Read more

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Professor Hripcsak rightly points out some of the challenges inherent in disseminating and sustaining robust information systems to automate the detection and reporting of notifiable diseases using data from electronic medical records (EMR). New York City'™s experience with automated... Read more

Content type: Abstract

Existing statistical methods can perform well in detecting simulated bioterrorism events. However, these methods have not been well-evaluated for detection of the type of respiratory and gastrointestinal events of greatest interest for routine public health practice. To assess whether a... Read more

Content type: Abstract

To implement a syndromic surveillance system on CDCís public health information grid, capable of securely distributing syndromic data streams ranging from aggregate case counts to individual case details, to appropriate personnel.

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