Desenvolvimento e avaliação inicial de usabilidade de um sistema de monitoramento de leitos para pacientes com bactérias multirresistentes no Hospital Universitário de Maringá - PR

Abstract

Healthcare-associated infections (HAIs) remain a major patient safety challenge, particularly when associated with multidrug-resistant (MDR) bacteria. Bed management for patients who are colonized or infected with MDR organisms requires accurate, up-to-date, traceable, and readily accessible information for Hospital Infection Control Services and related healthcare teams. However, this process is still frequently supported by manual records and spreadsheets, which may limit the efficiency and reliability of information management.This study aimed to develop a digital system to support hospital bed management for patients colonized or infected with MDR bacteria and to conduct an initial evaluation of its usability, applicability, perceived functionality, and acceptability among infection control professionals and related healthcare teams. This applied methodological study involved technological development through requirements elicitation, MoSCoW prioritization, prototyping, incremental implementation, user training, and controlled evaluation using simulated data.The evaluation instrument was based on the System Usability Scale (SUS) and the Technology Acceptance Model (TAM), supplemented by open-ended questions. The results indicated favorable perceptions regarding the system’s usefulness, organization and accessibility of information, and intention to use. The overall Cronbach’s alpha coefficient was 0.917, indicating high internal consistency. However, the response time and navigability dimension showed lower internal consistency, suggesting the need for further refinement.This study did not assess clinical outcomes, reductions in HAIs, or the prevention of cross-transmission. The developed system shows potential to support hospital bed management for patients colonized or infected with MDR bacteria. Further studies conducted in real-world settings, using clinical data, larger samples, and clinical and operational indicators, are recommended to assess its effectiveness and impact on healthcare practice.Healthcare-associated infections (HAIs) remain a major patient safety challenge, particularly when associated with multidrug-resistant (MDR) bacteria. Bed management for patients who are colonized or infected with MDR organisms requires accurate, up-to-date, traceable, and readily accessible information for Hospital Infection Control Services and related healthcare teams. However, this process is still frequently supported by manual records and spreadsheets, which may limit the efficiency and reliability of information management.This study aimed to develop a digital system to support hospital bed management for patients colonized or infected with MDR bacteria and to conduct an initial evaluation of its usability, applicability, perceived functionality, and acceptability among infection control professionals and related healthcare teams. This applied methodological study involved technological development through requirements elicitation, MoSCoW prioritization, prototyping, incremental implementation, user training, and controlled evaluation using simulated data.The evaluation instrument was based on the System Usability Scale (SUS) and the Technology Acceptance Model (TAM), supplemented by open-ended questions. The results indicated favorable perceptions regarding the system’s usefulness, organization and accessibility of information, and intention to use. The overall Cronbach’s alpha coefficient was 0.917, indicating high internal consistency. However, the response time and navigability dimension showed lower internal consistency, suggesting the need for further refinement.This study did not assess clinical outcomes, reductions in HAIs, or the prevention of cross-transmission. The developed system shows potential to support hospital bed management for patients colonized or infected with MDR bacteria. Further studies conducted in real-world settings, using clinical data, larger samples, and clinical and operational indicators, are recommended to assess its effectiveness and impact on healthcare practice.