Reengineering the BioSense Data Feed to Support State Notifiable Conditions Reporting Requirements in Texas

The BioSense integration engine includes a stepwise approach to filter, map, translate, and send to CDC de-identified electronic health data necessary for biosurveillance.  In a collaborative effort, the BioSense integration engine installed in a large multi-hospital data center was modified to provide secure health information, including microbiology laboratory test results, to the authorized Texas state public health surveillance system.  Transparency was a critical step forward for integration, interoperability, and sustainability.  We present this ongoing work, articulating the internal mechanics within the integrator and examine the quantitative and qualitative attributes of electronic laboratory result reporting (ELR).     

The first phase required a feasibility analysis to determine the extent of ELR information offered from the hospital’s BioSense through to CDC.  This led to a newly proposed route within the integrator to re-identify the data to support Texas state public health reporting.  As part of quality assurance process, we evaluated the anticipated data feed to the state-based National Electronic Disease Surveillance System (NEDSS).  The process included analyses of the integration engine’s performance, data quality, and timeliness of reporting state notifiable conditions.

The degree of adoption of ELR varies from jurisdiction to jurisdiction.  As such, these findings will contribute to the information science and technology required to build an interoperable digital workspace among public health partners (including Health Information Exchanges) and to establish ELR capacity where it does not currently exist.  The outcomes of this project have lead to documentation of the lessons learned, procedures to modify the existing biosurveillance infrastructure in BioSense, and experience working with the hospital system and state health department to establish this ELR feed.  Further, the findings may support other aspects of reporting, such as provision of case-report information using the same infrastructure.