Multicenter Data Standardization Protocol for Invasive Candidemia Surveillance in Infectious Disease Research Networks
Keywords:
invasive candidemia, data standardization, multicenter surveillance, infectious disease research networks, epidemiology, HL7 FHIR, SNOMED CT, antifungal resistance, laboratory harmonization, fungal infection surveillanceAbstract
Invasive candidemia, a severe bloodstream infection caused predominantly by Candida species, remains a significant contributor to morbidity and mortality in healthcare settings worldwide. Variability in diagnostic methodologies, data collection practices, and reporting standards across institutions presents a critical barrier to effective multicenter surveillance and comparative epidemiological analysis. This study proposes a Multicenter Data Standardization Protocol (MDSP) designed to harmonize data acquisition, management, and reporting within infectious disease research networks focused on candidemia surveillance. The protocol was developed through a consensus-driven approach involving microbiologists, infectious disease specialists, epidemiologists, and data scientists from diverse geographic and clinical settings. It establishes uniform case definitions, standardized microbiological testing algorithms, and harmonized metadata fields to capture clinical, laboratory, and outcome variables. A core feature of the MDSP is the integration of interoperable data formats and controlled vocabularies aligned with international standards such as HL7 FHIR and SNOMED CT, enabling seamless data exchange and aggregation across centers. Quality assurance measures, including cross-site proficiency testing and periodic data audits, ensure reliability and comparability of surveillance data. A pilot implementation across five tertiary-care hospitals demonstrated improved data completeness (increase from 78% to 96%) and inter-laboratory concordance in species identification and antifungal susceptibility testing. The MDSP also facilitated advanced analytics, including temporal trend modeling and geospatial mapping of candidemia incidence, thereby enhancing outbreak detection capabilities and informing targeted infection prevention strategies. By addressing heterogeneity in data sources and promoting adherence to shared operational definitions, the MDSP strengthens the foundation for collaborative research, real-time surveillance, and global burden estimation of invasive candidemia. Broader adoption of this protocol within infectious disease research networks is expected to accelerate translational research, improve patient outcomes, and contribute to coordinated public health responses against fungal pathogens of high clinical significance.
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