Rationale for Creating an Automated Epidemiologist Workstation in the Context of Implementing Medical Information Systems

Introduction: The growing threat of antimicrobial resistance of key pathogens of hospital-acquired infections leads to the necessity to create automated surveillance systems at the level of a health facility and a constituent entity of the Russian Federation. To build an effective epidemiological security system in an institution, it is essential to consider the whole aggregate of clinical, laboratory, instrumental, and epidemiological data. Nowadays, these data are dispersed across different, unrelated information systems (laboratory information systems and medical information systems).

Objective: To analyze medical information systems currently used and put into practice in inpatient hospitals of St. Petersburg and capable of supporting the tasks of epidemiological surveillance through the present-day Automated Epidemiologist Workstation.

Materials and Methods: We reviewed scientific publications, epidemiological reference publications, and electronic information resources for 2015–2025. We also compared the local medical information system (MIS) and the unified platform implemented in the facility based on manufacturers’ specifications and urgent tasks of securing epidemiological safety of high-quality medical care.

Results: The available MIS configuration lacks specialized tools and modules for epidemiological control. The main stages of data analysis are performed outside the system using various third-party resources, which increases labor costs and delays in obtaining management-relevant information and reduces comparability of results by period and department. The unified urban platform has a higher scaling potential, but the practical effect is feasible only with a separate module and regulation of the elements of infection control.

Conclusion: Transitioning from formal data access to reproducible control requires a digital epidemiologist workstation ensuring integration of clinical and microbiological data, strict sampling rules, quality control of stratified indicators, and an automated data analysis to organize a real-time epidemiological security system.

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