Syndromic surveillance requires reliable, accurate, and complete healthcare encounter data. To address the need for quality assessment of ED data, we developed an R script to assess and produce reports on data quality in the BioSense locker database. The script examines identifying variables in the HL7 messages from the locker, aggregates messages into ED visits based on these identifiers, processes the aggregated data to calculate metadata for each visit, and computes various data quality metrics. Facility-level reports are written to HTML files, which can then be shared with hospitals and vendors to support ongoing data quality improvements.