(P422) Living Off the Grid: Automating Syphilis Electronic Laboratory Processing to Align with Case Definition in Florida, USA

Background:

Many states, including Florida, use an automated reactor grid, based on age and non-treponemal titer, for processing serologic tests for syphilis (STS) via electronic laboratory reporting (ELR). As part of modernizing data approaches, in mid-2022 the Florida Department of Health replaced the automated reactor grid within their STD surveillance system (STDSS) with an algorithm that processes and assigns STS for investigation by assessing client STS history and treponemal/non-treponemal test concordancy to better align with the case definition. We evaluated the impact of this change following implementation for a one-week period.

Methods:

STS processed through the new algorithm were examined in the 9 (of 14) program areas from October 1 - October 7, 2022. STS were evaluated by number of results processed, number of persons (previously in STDSS or new), and assignment status of the processed ELR. Three program areas assessed the outcome of STS assignments on case outcomes for results either assigned for investigation or closed as inconsistent with a new syphilis infection.

Results:

The algorithm processed 3,970 unique STS from the STDSS for 1,658 persons (2.4 STS per person), 80% (n=1,331) of whom were previously listed in STDSS. Ultimately, 27% (1,056) STS were assigned for investigation; the remainder were not assigned as they were consistent with being serofast or biological false positive STS results (n=2,221; 56%); appended to previous investigations within 30 days (n=390; 10%); or treponemal results temporarily awaiting non-treponemal results (n=283; 7%). Within the 3 program area subset (707 STS from 303 persons), there were 101 potential infection records assigned for investigation and 141 records not needing investigation. Of the 101 potential infection records, 40 resulted in new infections, 49 were determined not to be new infections, and 12 were awaiting determination. Of the 141 records not investigated, only 1 resulted in a new case. The STS algorithm had 98% sensitivity, 74% specificity, 45% positive predictive value, 99% negative predictive value, and 78% accuracy.

Conclusions:

The algorithm accurately processed STS, while ensuring that nearly all infections were reported. Processing STS based on STS history and concordancy reduces staff time spent investigating persons not infected with syphilis.