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Effective communication is essential between health professionals during surgical procedures for delivery of safe patient care. The influence of noise on communication during critical moments of surgery and on communication failures is unclear.
To examine communication events among health professionals in the operating room and investigate the influence of noise on communication.
Non-participatory observations were undertaken of communication between health professionals during surgical procedures while simultaneously measuring sound pressure levels. Audio visual recording was used to document communication events, ensuring data accuracy. A generalised linear mixed model was used to examine relationships between various explanatory variables and the presence of at least one communication failure. The STROBE checklist guided the reporting of this paper.
A representative range of procedures was observed from diverse surgical specialties (N = 80). Observations comprised 2274 communication events; communication failures were observed in 24% and repeated communication was observed in 25% of all communication events. The mean maximum sound pressure levels were 64.9 dB[A] for communication events, 64.5 dB[A] for communication failures and 65.5 dB[A] for repeats. The type of surgical procedure, the emergence from anaesthesia compared to other phases of surgery, communication related to the surgical safety checklist, communication related to the surgical count, the presence of multitasking, and the use of surgical facemasks, were associated with the presence of at least one communication failure.
This research identified the inherent risks and occurrence of communication failure in noisy operating room environments where health professionals are undertaking complex cognitive tasks and where effective communication is essential to ensure patient safety.
This study did not include patient or public involvement in its design, conduct, or reporting.
Many researchers conduct a process evaluation alongside an effectiveness trial of a public health intervention to better understand mechanisms behind observed effects. Yet, there is no standardised, scientifically accepted guideline for reporting such process evaluations, which impedes interpretation and comparison of study results. The aim of this project was to develop a consensus-based and expert-based guideline for reporting process evaluations of public health interventions conducted alongside an effectiveness trial.
We conducted an e-Delphi study with a large panel of international experts.
Based on purposive sampling, we invited 137 international experts that had been involved in the design of process evaluations, researchers who published high-profile process evaluations or frameworks, editors of journals that publish process evaluations, and authors of other reporting guidelines.
Based on a literature search, a first draft of the reporting guideline included 32 items, which was proposed to panel members during the first round. Of the invited 137 invited international experts, 73 (53%) participated in at least one round of the e-Delphi study. Participants rated the inclusion and comprehensibility of the proposed items on a 5-point Likert scale and provided comments and suggestions for relevance and definitions of the items. Adjustments to the items and descriptions were proposed to the e-Delphi panel until consensus of ≥67% for each individual item was reached. In total, 64 (88% of 73) completed round 2, and 55 (76% of 73) completed round 3. This resulted in 19 items that are included in the consensus-based process evaluation reporting guideline for public health intervention studies (CONPHES) guideline. The items cover a detailed description of the intervention that is evaluated, the implementation strategies applied, and underlying causal pathways, and the role of the delivery and support team. The guideline also requires describing the evaluation framework and how evaluation outcomes were assessed. Lastly, the guideline includes items on providing a detailed description of applied analyses (both quantitative and qualitative) and measures for assuring quality. The guideline is accompanied by an Explanation and Elaboration document, with a more detailed explanation of each item.
We expect that the CONPHES reporting guideline for process evaluations of public health interventions can improve the reporting of process evaluations of interventions aimed at promoting public health. This can potentially facilitate more effective translation of public health research into practice and contribute to improving both individual and population health outcomes.
To investigate the experience with and progress of the implementation of a Family Support Intervention (FSI) into adult intensive care units (ICUs) as part of the cluster-randomised FICUS trial.
A mixed-methods process evaluation using a multiple case study approach guided by the normalisation process theory.
This study took place between June 2022 and July 2023 in eight Swiss ICUs randomised to the intervention arm. A tailored implementation strategy was used to introduce the multicomponent FSI, consisting of a new family nursing role and a family care pathway, into interprofessional ICU teams. Participants were 40 ICU key clinical partners. Qualitative data were collected twice, early (3–6 months) and mid-implementation (9–12 months), using small group interviews. A questionnaire with psychometric measures (Acceptability of Intervention Measure, Feasibility of Intervention Measure, Intervention Appropriateness Measure, Normalisation Measure Development Questionnaire) was administered at mid-implementation. RITA pragmatic rapid thematic analysis and descriptive statistics were used to analyse the data. Qualitative and quantitative results were then compared across ICUs (cases).
Findings indicated the desired progress of the FSI integration overall and across cases, with high acceptability and appropriateness ratings but only moderate to high feasibility scores. Study-related barriers were noted in all ICUs (i.e., FSI delivery as part of a clinical trial). Implementation barriers included family nurses' limited capacity and clinician's attitudes towards the FSI. Leadership support and interprofessional collaboration were identified as facilitators. Case-based, integrated findings yielded two implementation pathways, namely early and protracted adopters.
Implementation barriers were related to the feasibility of FSI delivery within the study context that required a high degree of standardisation and protocol adherence. Implementation progress was shaped by an interprofessional culture of family care, sufficient staff and time resources, and leadership support. The study's findings will inform future implementation of complex health interventions in ICUs.
Good reporting of a Mixed-Methods Study (GRAMMS).
Within the FICUS trial, a patient and family advisory board with a patient expert, three family members and a patient with own lived experience of critical care collaborate with the research team.
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