RESUMO
Artificial intelligence (AI) in the domain of healthcare is increasing in prominence. Acceptance is an indispensable prerequisite for the widespread implementation of AI. The aim of this integrative review is to explore barriers and facilitators influencing healthcare professionals' acceptance of AI in the hospital setting. Forty-two articles met the inclusion criteria for this review. Pertinent elements to the study such as the type of AI, factors influencing acceptance, and the participants' profession were extracted from the included studies, and the studies were appraised for their quality. The data extraction and results were presented according to the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The included studies revealed a variety of facilitating and hindering factors for AI acceptance in the hospital setting. Clinical decision support systems (CDSS) were the AI form included in most studies (n = 21). Heterogeneous results with regard to the perceptions of the effects of AI on error occurrence, alert sensitivity and timely resources were reported. In contrast, fear of a loss of (professional) autonomy and difficulties in integrating AI into clinical workflows were unanimously reported to be hindering factors. On the other hand, training for the use of AI facilitated acceptance. Heterogeneous results may be explained by differences in the application and functioning of the different AI systems as well as inter-professional and interdisciplinary disparities. To conclude, in order to facilitate acceptance of AI among healthcare professionals it is advisable to integrate end-users in the early stages of AI development as well as to offer needs-adjusted training for the use of AI in healthcare and providing adequate infrastructure.
RESUMO
Background: The status of Safety Management is highly relevant to evaluate an organization's ability to deal with unexpected events or errors, especially in times of crisis. However, it remains unclear to what extent Safety Management was developed and sufficiently implemented within the healthcare system during the COVID-19 pandemic. Providing insights of potential for improvement is expected to be directional for ongoing Safety Management efforts, in times of crisis and beyond. Method: A nationwide survey study was conducted among healthcare professionals and auxiliary staff on German Intensive Care Units (ICUs) evaluating their experiences during the first wave of the COVID-19 pandemic. Error Management and Patient Safety Culture (PSC) measures served to operationalize Safety Management. Data were analyzed descriptively and by using quantitative content analysis (QCA). Results: Results for n = 588 participants from 53 hospitals show that there is a gap between errors occurred, reported, documented, and addressed. QCA revealed that low quality of safety culture (27.8%) was the most mentioned reason for errors not being addressed. Overall, ratings of PSC ranged from 26.7 to 57.9% positive response with Staffing being the worst and Teamwork Within Units being the best rated dimension. While assessments showed a similar pattern, medical staff rated PSC on ICUs more positively in comparison to nursing staff. Conclusion: The status-analysis of Safety Management in times of crisis revealed relevant potential for improvement. Human Factor plays a crucial role in the occurrence and the way errors are dealt with on ICUs, but systemic factors should not be underestimated. Further intensified efforts specifically in the fields of staffing and error reporting, documentation and communication are needed to improve Safety Management on ICUs. These findings might also be applicable across nations and sectors beyond the medical field.
RESUMO
Background: Sustaining Basic Life Support (BLS) training during the COVID-19 pandemic bears substantial challenges. The limited availability of highly qualified instructors and tight economic conditions complicates the delivery of these life-saving trainings. Consequently, innovative and resource-efficient approaches are needed to minimize or eliminate contagion while maintaining high training standards and managing learner anxiety related to infection risk. Methods: In a non-inferiority trial 346 first-year medical, dentistry, and physiotherapy students underwent BLS training at AIXTRA-Competence Center for Training and Patient Safety at the University Hospital RWTH Aachen. Our objectives were (1) to examine whether peer feedback BLS training supported by tele-instructors matches the learning performance of standard instructor-guided BLS training for laypersons; and (2) to minimize infection risk during BLS training. Therefore, in a parallel group design, we compared arm (1) Standard Instructor Feedback (SIF) BLS training (Historical control group of 2019) with arm (2) a Tele-Instructor Supported Peer-Feedback (TPF) BLS training (Intervention group of 2020). Both study arms were based on Peyton's 4-step approach. Before and after each training session, objective data for BLS performance (compression depth and rate) were recorded using a resuscitation manikin. We also assessed overall BLS performance via standardized instructor evaluation and student self-reports of confidence via questionnaire. Non-inferiority margins for the outcome parameters and sample size calculation were based on previous studies with SIF. Two-sided 95% confidence intervals were employed to determine significance of non-inferiority. Results: The results confirmed non-inferiority of TPF to SIF for all tested outcome parameters. A follow-up after 2 weeks found no confirmed COVID-19 infections among the participants. Conclusion: Tele-instructor supported peer feedback is a powerful alternative to in-person instructor feedback on BLS skills during a pandemic, where infection risk needs to be minimized while maximizing the quality of BLS skill learning. Trial registration: https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00025199, Trial ID: DRKS00025199.
