BACKGROUND: New York City (NYC) is one of many jurisdictions (e.g., CT, MA, MN, SD, NC) using the Maven disease surveillance and case management system. Although core Maven functionality is the same across jurisdictions, the system is flexible. The NYC Department of Health and Mental Hygiene (NYC DOHMH) has leveraged Maven’s many capabilities to support routine surveillance and emergency response to recent communicable disease outbreaks including Ebola, Legionella, and Zika.
METHODS: NYC DOHMH implemented the Maven system for communicable disease surveillance and outbreak data management in 2012. Two full-time and several other program staff (with minimal or no assistance from the vendor or information technology resources) configure the system and make changes to the data model, workflows (lists of cases meeting defined criteria and requiring attention or action), print templates (predefined document templates including elements populated with database values), import processes, and denormalized table structures (SQL tables providing data for analysis).
RESULTS: Maven was configured to support 1) an automated daily process to calculate case-level etiology data or current laboratory diagnostic status from raw laboratory data available in denormalized tables and reimport the calculated value (e.g., Salmonella serotype, influenza subtype, or Zika lab status) into the case for use in analyses, including for SaTScan cluster detection, 2) rapid development of forms for data entry of situation-specific data for outbreaks including Legionella in the South Bronx, Mycobacterium marinum among fish market patrons and workers, and influenza H7N2 among sheltered cats (e.g., questions regarding exposures to places, particular stores or types of fish handled, or sick cats), 3) a call center for active monitoring for Ebola symptoms among thousands of returning travelers (this required multiple workflows to identify persons needing to be called daily during the 21 days post-exposure, or persons requiring interjurisdictional notification), 4) importation of hepatitis C RNA-negative electronic laboratory reports, restricting to only those reports matching to an existing hepatitis C case, 5) rapid generation of letters in multiple languages advising of a communicable disease in a congregate setting, and 6) weekly or daily data cleaning (e.g., of addresses to improve geocoding and cluster detection) using automated processes.
CONCLUSIONS: Using a system that is flexible and configurable by program-level staff increases the efficiency of surveillance and outbreak response. The Maven system has proven useful to NYC DOHMH for both routine surveillance and emergency response. Sharing best practices and innovative uses with other jurisdictions can maximize the gains in efficiency.