Background. Due to the global spread of antibiotic resistance, the problem of selecting an appropriate antibacterial agent for empirical therapy of healthcare-associated infections in hospital conditions has become particularly urgent.. Effective prevention and treatment of postoperative infectious and inflammatory complications rely on continuous local microbiological monitoring within each medical institution. Purpose To examine the microbiological profile of the urological department of a multidisciplinary hospital and to analyze the resistance patterns of the identified isolates to antibacterial drugs. Materials and methods. The analysis was conducted of urine cultures results from patients who received both conservative and surgical treatment for various urological condition. A total of 1230 urine samples from 856 patients were studied. The spectrum of pathogens responsible for nosocomial urological infection was determined, and their susceptibility to antimicrobial drugs was assessed. The presence of genes of the most common carbapenemases and beta-lactamases was identified using the real-time polymerase chain reaction method. Results. A total of 652 microbial strains were isolated from 502 positive samples. Monoculture was detected in 384 cases (76.5%) in the urine culture results. The analytical stage revealed the prevalence of gram-negative flora (69%) in the urology unit. The majority (54.1%) of the detected microorganisms belonged to the order Enterobacterales. The most common microorganism detected in hospital conditions was E. coli, found in 27.4% of the total number of strains. The second most common pathogen was gram-positive Enterococcus faecalis (23.9%).96 strains of K. pneumoniae(14.7%) were identified, and the detection of Pseudomonas aeruginosa reached 10.6%. Of the 652 isolated microorganisms, 479 (73.5%) were characterized by polyresistance. Conclusion. The high level of antibiotic resistance in a urological hospital requires a n individualized approach to the treatment of infectious and inflammatory processes. Incorporating local microbiological monitoring data helps to optimize the initial antibiotic therapy, the success of which determines the timing and results of inpatient treatment.