Background:
STD Programs often prioritize syphilis positive results for investigation based on RPR titer using a reactor grid. Reverse sequence syphilis testing creates confusion for STD Programs in cases of discordant results, making it difficult to prioritize syphilis reactors for investigation. Local STD Programs lack a tool similar to a reactor grid with which to assign discordant results to Disease Intervention Specialists (DIS). The Indiana State Department of Health (ISDH) created a policy for follow up of discordant syphilis results to assist local programs in identifying high-priority reactors for investigation.Objectives: To test the effectiveness of the policy in identifying infectious cases of syphilis or unnecessary investigations.
Methods: A sample of discordant syphilis results from laboratories using the reverse sequence algorithm received by the Marion County Public Health Department (MCPHD) was assigned to DIS for additional testing including non-treponemal and treponemal testing . Record search for patient syphilis history was also conducted. Findings were interpreted using the conventional method to determine if the patient represented a new case, biologic false positive, or an old case of syphilis. Patient and provider characteristics were recorded to compare to ISDH policy.
Results: ISDH procedures for follow up were effective in identifying discordant results needing investigation from those that could be administratively closed. Among the sample assigned, none represented true, infectious cases that would not have been otherwise identified.
Conclusions: Indiana’s policy for assigning discordant syphilis reactors for investigation may allow local STD programs to prioritize those most likely to be infected while minimizing investigation of those least likely.
Implications for Programs, Policy, and Research: Other state STD Programs who have not yet developed procedures for assigning discordant reverse sequence syphilis reactors may want to consider adapting the ISDH policy for local use as a model to target DIS resources towards those most likely to be infected.