Automated methods for surveillance of surgical site infections

A tree-based scan statistic for database disease surveillance

Many databases exist with which it is possible to study the relationship between health events and various potential risk factors. Among these databases, some have variables that naturally form a hierarchical tree structure, such as pharmaceutical drugs and occupations. It is of great interest to use such databases for surveillance purposes in order to detect unsuspected relationships to disease risk. We propose a tree-based scan statistic, by which the surveillance can be conducted with a minimum of prior assumptions about the group of occupations/drugs that increase risk, and which adjusts for the multiple testing inherent in the many potential combinations. The method is illustrated using data from the National Center for Health Statistics Multiple Cause of Death Database, looking at the relationship between occupation and death from silicosis.

Surveillance in infection control: are we making progress?

PURPOSE OF THE REVIEW

Surveillance of nosocomial infections is an indispensable tool in infection control, and is used for detecting problem areas, defining patients who are at risk and evaluating intervention strategies. Surveillance techniques are continuously being evaluated and improved.

RECENT FINDINGS

Problems with definitions, risk stratification and case finding render development of (inter)national surveillance systems difficult with respect to the comparability of data between different hospitals. These problems also influence surveillance in specific areas of nosocomial infections, such as urinary tract infections, ventilator-associated pneumonia and surgical site infections. Examples of such problem areas are discussed in the present review.

SUMMARY

Despite continuing efforts made to improve quality of (inter)national and local surveillance systems, issues of infection definition and risk stratification are still under debate and need further research.