Abstract
Background
Academic and public health partnerships are a critical component of the Ending the HIV Epidemic: A Plan for America (EHE). The Enhanced HIV/AIDS Reporting System (eHARS) is a standardized document-based surveillance database used by state health departments to collect and manage case reports, lab reports, and other documentation on persons living with HIV. Innovative analysis of this data can inform targeted, evidence-based interventions to achieve EHE objectives. We describe the development of a distributed data network strategy at an academic institution in partnership with public health departments to identify geographic differences in time to HIV viral suppression after HIV diagnosis using eHARS data.
Figure 1. Distributed Data Network
Methods
This project was an outgrowth of work developed at the University of Alabama at Birmingham Center for AIDS Research (UAB CFAR) and existing relationships with the state health departments of Alabama, Louisiana, and Mississippi. At a project start-up meeting which included study investigators and state epidemiologists, core objectives and outcome measures were established, key eHARS variables were identified, and regulatory and confidentiality procedures were examined. The study methods were approved by the UAB Institutional Review Board (IRB) and all three state health department IRBs.
Results
A common data structure and data dictionary across the three states were developed. Detailed analysis protocols and statistical code were developed by investigators in collaboration with state health departments. Over the course of multiple in-person and virtual meetings, the program code was successfully piloted with one state health department. This generated initial summary statistics, including measures of central tendency, dispersion, and preliminary survival analysis.
Conclusion
We developed a successful academic and public health partnership creating a distributed data network that allows for innovative research using eHARS surveillance data while protecting sensitive health information. Next, state health departments will transmit summary statistics to UAB for combination using meta-analytic techniques. This approach can be adapted to inform delivery of targeted interventions at a regional and national level.
Disclosures
All Authors: No reported disclosures
Development and Application of Two Semi-Automated Tools for Targeted Medical Product Surveillance in a Distributed Data Network