6th Annual Public Health Information Network Conference: Implementing Content Validation Tool to Ensure Message Quality Assurance and Appropriate Classification Using the Tuberculosis Case Notifications to CDC: A Proof of Concept

Implementing Content Validation Tool to Ensure Message Quality Assurance and Appropriate Classification Using the Tuberculosis Case Notifications to CDC: A Proof of Concept

Tuesday, August 26, 2008: 4:10 PM
Atlanta BCD
John Abellera, MPH , National Center for Public Health Informatics, Centers for Disease Control and Prevention, Atlanta, GA
Sandy Price , Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, GA
Craig Cunningham , OntoReason, Midvale, UT
GB Kesarinath , National Center for Public Health Informatics, Centers for Disease Control and Prevention, Atlanta, GA
In August 2007, a PHIN message guide, in the form of HL7 v2.5 for Tuberculosis (TB) was posted on CDC’s PHIN website.  The new message guide, a national standard for case notifications, will allow states to send TB data to CDC and has prompted several states to use their existing NEDSS compliant state-based disease surveillance systems.  However, these systems may not include all the validations to minimize the amount of content error and do not include functionality to alert for drug resistant cases.  There are over 300 business rules in the legacy TB information system, which are not universally employed.  As states adhere to national standards for electronic messaging, this may require additional tools to help identify errors and ensure quality in the content of the message.

To address the validation issues, a TB content validation tool was implemented.  As part of the integration within CDC, the tool will reside in the data warehouse and process incoming case notifications to check for semantic integrity, illustrate how the errors are stored and presented for corrective action, and highlight aspects of the message utilized for the analysis.

Twenty TB case notification messages were processed.  Eight test messages passed, and the other twelve returned the expected errors based on the defined validations.  In some instances, the error messages were incomplete and needed to be refined.

These tools represent functionality intended for use by the CDC in its TB program, but also as a baseline for functionality that will be made available to state and local TB programs and ultimately expansion of the message validation methodology to other CDC Program Areas.  The results from the initial evaluation are indicative of the effectiveness of the alerting functions and the potential for expansion of the validation tool to provide additional feedback to the reporting jurisdictions.