Implementation of a Clostridioides difficile prevention bundle: Understanding common, unique, and conflicting work system barriers and facilitators for subprocess design

Abstract

Objective:Clostridioides difficile (C. difficile) poses a major challenge to the healthcare system. We assessed factors that should be considered when designing subprocesses of a C. difficile infection (CDI) prevention bundle.Design:Phenomenological qualitative study.Methods:We conducted 3 focus groups of environmental services (EVS) staff, physicians, and nurses to assess their perspectives on a CDI prevention bundle. We used the Systems Engineering Initiative for Patient Safety (SEIPS) model to examine 5 subprocesses of the CDI bundle: diagnostic testing, empiric isolation, contact isolation, hand hygiene, and environmental disinfection. We coded transcripts to the 5 SEIPS elements and ensured scientific rigor. We sought to determine common, unique, and conflicting factors across stakeholder groups and subprocesses of the CDI bundle.Results:Each focus group lasted 1.5 hours on average. Common work-system barriers included inconsistencies in knowledge and practice of CDI management procedures; increased workload; poor setup of aspects of the physical environment (eg, inconvenient location of sinks); and inconsistencies in CDI documentation. Unique barriers and facilitators were related to specific activities performed by the stakeholder group. For instance, algorithmic approaches used by physicians facilitated timely diagnosis of CDI. Conflicting barriers or facilitators were related to opposing objectives; for example, clinicians needed rapid placement of a patient in a room while EVS staff needed time to disinfect the room.Conclusions:A systems engineering approach can help to holistically identify factors that influence successful implementation of subprocesses of infection prevention bundles.

Wisconsin dairy farm worker perceptions and practices related to antibiotic use, resistance, and infection prevention using a systems engineering framework

“…The SEIPS model allows researchers to identify known barriers and facilitators to organizational outcomes which can contribute to the development of well-informed and targeted interventions to reduce exposure and other risk factors. Although SEIPS has been extensively used to examine healthcare work systems [ 17 , 18 ], to our knowledge, the SEIPS model has not previously been used to examine agricultural work systems nor has it been used to specifically examine dairy operations. Using a systems engineering approach such as SEIPS allows for a comprehensive assessment of the work-system including interactions among workers, between workers and animals, and workers and the environment and equipment.…”

Use of a systems engineering framework to assess perceptions and practices about antimicrobial resistance of workers on large dairy farms in Wisconsin

“…The SEIPS model allows researchers to identify known barriers and facilitators to organizational outcomes which can contribute to the development of well-informed and targeted interventions to reduce exposure and other risk factors. Although SEIPS has been extensively used to examine healthcare work systems (8, 9), to our knowledge, the SEIPS model has not previously been used to examine agricultural work systems nor has it been used to specifically examine dairy operations. Figure 1 illustrates how the SEIPS model was adapted for the use on dairy farms in this study.…”

Characterizing barriers to antibiotic stewardship for skin and soft-tissue infections in the emergency department using a systems engineering framework

“…SEIPS has been successfully applied to characterize various quality of care and patient safety challenges (eg, antibiotic stewardship and diagnostic errors). [15][16][17] The element at the center of the model is the person (provider or patient) with surrounding elements (ie, physical environment, tasks, organization, and tools and technology) that operate within an external environment. The elements of the work system interact when preforming healthcare processes, which produce outcomes that feed back into the work system.…”