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This Article Figures Only Full Text Full Text (PDF) All Versions of this Article: AJPH.2006.092700v1 98/2/344    most recent Submit a response Purchase Article View Shopping Cart Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Overhage, J. M. Articles by McDonald, C. J. Search for Related Content PubMed PubMed Citation Articles by Overhage, J. M. Articles by McDonald, C. J. Related Collections Public Health Practice Surveillance Other Statistics/Evaluation/Research

J. Marc Overhage, MD, PhD, Shaun Grannis, MD, MS and Clement J. McDonald, MD

At the time of the study, the authors were with the Regenstrief Institute, Indianapolis, Ind.

Correspondence: Requests for reprints should be sent to J. Marc Overhage, MD, PhD, Regenstrief Institute, 410 W 10th St, Suite 2000, Indianapolis, IN 46202-3012 (e-mail: moverhage{at}regenstrief.org).

Objectives. We examined whether automated electronic laboratory reporting of notifiable-diseases results in information being delivered to public health departments more completely and quickly than is the case with spontaneous, paper-based reporting.

Methods. We used data from a local public health department, hospital infection control departments, and a community-wide health information exchange to identify all potential cases of notifiable conditions that occurred in Marion County, Ind, during the first quarter of 2001. We compared traditional spontaneous reporting to the health department with automated electronic laboratory reporting through the health information exchange.

Results. After reports obtained using the 2 methods had been matched, there were 4785 unique reports for 53 different conditions during the study period. Chlamydia was the most common condition, followed by hepatitis B, hepatitis C, and gonorrhea. Automated electronic laboratory reporting identified 4.4 times as many cases as traditional spontaneous, paper-based methods and identified those cases 7.9 days earlier than spontaneous reporting.

Conclusions. Automated electronic laboratory reporting improves the completeness and timeliness of disease surveillance, which will enhance public health awareness and reporting efficiency.