Information technologies for supporting prevention, diagnosis and management of surgical site infections in trauma and orthopedic patients

Abstract

BACKGROUND: Surgical site infections (SSIs) are among the most common preventable healthcare-associated infections and represent a significant socioeconomic burden. Digital technologies, particularly clinical decision support systems, are proved to be effective in enhancing patient safety, but there is limited evidence of their implementation for SSIs prevention and management. AIM: Development of a multifunctional intelligent system on patient safety (ISPS) in traumatology and orthopedic area, particularly for SSI prevention, diagnosis and treatment. MATERIALS AND METHODS: The ISPS for traumatology and orthopedists was implemented at the Federal State Budgetary Institution N.N.Priorov National Medical Research Center of Traumatology and Orthopedics in late 2023— early 2024. The ISPS includes two end-user systems: 1)analytical and authoring (ISPS-Manager), designed for knowledge base experts who generate scenarios; 2)clinical, designed to enter patient data and view recommendations. RESULTS: The scenario for SSI prevention has been developed based on the guidelines of the National Association of Healthcare Associated Infection Control Professionals. It includes 11recommendations for the preoperative stage, 30 for the peri- and intraoperative stages, 33recommendations for the prevention of SSI in the operating room and 7 for the postoperative period. The surgical antimicrobial prophylaxis scenario has 24recommendations. Decision making algorithms for the SSI management are based on the recommendations of the American Association of Orthopaedic Surgeons (AAOS) and take into account 6 factors, giving 264different clinical situations, for which 9 decision options are provided. CONCLUSIONS: The generated protocols can serve not only to support decision-making on the patient management, but also as a tool for monitoring compliance with recommendations for the SSI prevention and treatment. Further prospects for the development of the ISPS in part of the diagnosis and treatment of SSI are associated with the use of artificial intelligence technologies to support the processes of wound infection diagnosing and treatment.