Toward Automatic Reporting of Infectious Diseases

Stud Health Technol Inform. 2017:245:808-812.

Abstract

Accurate, complete, and timely disease surveillance data are vital for disease control. We report a national scale effort to automatically extract information from electronic medical records as well as electronic laboratory systems. The extracted information is then transferred to the centers of disease control after a proper confirmation process. The coverage rates of the automated reporting systems are over 50%. Not only is the workload of surveillance greatly reduced, but also reporting is completed in near real-time. From our experiences, a system sustainable strategy, well-defined working plan, and multifaceted team coordination work effectively. Knowledge management reduces the cost to maintain the system. Training courses with hands-on practice and reference documents are useful for LOINC adoption.

Keywords: Electronic Health Records; Logical Observation Identifiers Names and Codes; Public Health Surveillance.

MeSH terms

  • Clinical Laboratory Information Systems*
  • Communicable Diseases*
  • Electronic Health Records*
  • Humans
  • Laboratories
  • Logical Observation Identifiers Names and Codes