OTHER FUNDED PHI RESEARCH BY PHI CENTER INVESTIGATORS

Many of the PHI Center Investigators are principal investigators of research projects highy pertinent to to the mission of the Center.

AEGIS

Biosense

Midas

National Bioterrorism Syndromic Surveillance Demonstration Program

Surgical site infection surveillance

 

 

National Bioterrorism Syndromic Surveillance Demonstration Program

The National Bioterrorism Syndromic Surveillance Demonstration Program (NDP) identifies new cases of illness from electronic ambulatory patient records in order to detect and notify public health departments of localized outbreaks of acute illness early.  Data come from seven health-care organizations in five states (CA, CO, MA, MN, and TX).  Six health departments in the five states (three at the county level and three at the state level) collaborate in investigating the automated alerts generated by the system and in evaluating its performance. 
The surveillance system’s software, distributed to the data-providing sites, was designed to allow patient-level information to stay at the originating health-care organization unless required by public health authorities.  At the sites, data are extracted nightly on encounters occurring in the previous 24 hours.  Visits or calls with diagnostic codes corresponding to syndromes of interest are counted; repeat encounters are excluded.  Daily counts of syndromes by zip code go to a central data repository, where they are statistically analyzed for unusual clustering, using a model-adjusted SaTScan approach.  The results and raw data are displayed on a restricted website.  If a cluster surpasses a threshold of statistical aberration chosen by the respective public health department, an electronic alert goes to that department.  The health department may then call a clinical responder at the site in question, who has electronic access to records of cases contributing to clusters. 
The system is flexible, allowing changes in participating organizations, syndrome definitions, and alert thresholds.  It is transparent to clinicians and has been accepted by the health-care organizations that provide the data.  The system’s data are usable by local and national health agencies.  Its software is compatible with commonly used systems and software, and most of it is open source.  Currently, the utility of the system in routine public health practice is being evaluated.