A comparison of the completeness and timeliness of automated electronic laboratory reporting and spontaneous reporting of notifiable conditions

Am J Public Health. 2008 Feb;98(2):344-50. doi: 10.2105/AJPH.2006.092700. Epub 2008 Jan 2.


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.

Publication types

  • Comparative Study
  • Evaluation Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Chlamydia Infections / diagnosis
  • Chlamydia Infections / epidemiology
  • Disease Notification / standards
  • Disease Notification / statistics & numerical data*
  • Electronic Data Processing
  • Gonorrhea / diagnosis
  • Gonorrhea / epidemiology
  • Hepatitis B / diagnosis
  • Hepatitis B / epidemiology
  • Hepatitis C / diagnosis
  • Hepatitis C / epidemiology
  • Humans
  • Indiana / epidemiology
  • Laboratories / statistics & numerical data
  • Medical Records Systems, Computerized / statistics & numerical data*
  • Population Surveillance / methods*
  • Public Health Administration / statistics & numerical data