Acceptance, Barriers, and Facilitators to Implementing Artificial Intelligence–Based Decision Support Systems in Emergency Departments: Quantitative and Qualitative Evaluation

Background: Despite the increasing availability of clinical decision support systems (CDSSs) and rising expectation for CDSSs based on artificial intelligence (AI), little is known about the acceptance of AI-based CDSS by physicians and its barriers and facilitators in emergency care settings. Objective: We aimed to evaluate the acceptance, barriers, and facilitators to implementing AI-based CDSSs in the emergency care setting through the opinions of physicians on our newly developed, real-time AI-based CDSS, which alerts ED physicians by predicting aortic dissection based on numeric and text information from medical charts, by using the Unified Theory of Acceptance and Use of Technology (UTAUT; for quantitative evaluation) and the Consolidated Framework for Implementation Research (CFIR; for qualitative evaluation) frameworks. Methods: This mixed methods study was performed from March to April 2021. Transitional year residents (n=6), emergency medicine residents (n=5), and emergency physicians (n=3) from two community, tertiary care hospitals in Japan were included. We first developed a real-time CDSS for predicting aortic dissection based on numeric and text information from medical charts (eg, chief complaints, medical history, vital signs) with natural language processing. This system was deployed on the internet, and the participants used the system with clinical vignettes of model cases. Participants were then involved in a mixed methods evaluation consisting of a UTAUT-based questionnaire with a 5-point Likert scale (quantitative) and a CFIR-based semistructured interview (qualitative). Cronbach α was calculated as a reliability estimate for UTAUT subconstructs. Interviews were sampled, transcribed, and analyzed using the MaxQDA software. The framework analysis approach was used during the study to determine the relevance of the CFIR constructs. Results: All 14 participants completed the questionnaires and interviews. Quantitative analysis revealed generally positive responses for user acceptance with all scores above the neutral score of 3.0. In addition, the mixed methods analysis identified two significant barriers (System Performance, Compatibility) and two major facilitators (Evidence Strength, Design Quality) for implementation of AI-based CDSSs in emergency care settings. Conclusions: Our mixed methods evaluation based on theoretically grounded frameworks revealed the acceptance, barriers, and facilitators of implementation of AI-based CDSS. Although the concern of system failure and overtrusting of the system could be barriers to implementation, the locality of the system and designing an intuitive user interface could likely facilitate the use of optimal AI-based CDSS. Alleviating and resolving these factors should be key to achieving good user acceptance of AI-based CDSS. © Ryo Fujimori, Keibun Liu, Shoko Soeno, Hiromu Naraba, Kentaro Ogura, Konan Hara, Tomohiro Sonoo, Takayuki Ogura, Kensuke Nakamura, Tadahiro Goto. OriginallyOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Significance of Brain Tissue Oxygenation and the Arachidonic Acid Cascade in Stroke

The significance of the hypoxia component of stroke injury is highlighted by hypermetabolic brain tissue enriched with arachidonic acid (AA), a 22:6n-3 polyunsaturated fatty acid. In an ischemic stroke environment in which cerebral blood flow is arrested, oxygen-starved brain tissue initiates the rapid cleavage of AA from the membrane phospholipid bilayer. Once free, AA undergoes both enzyme-independent and enzyme-mediated oxidative metabolism, resulting in the formation of number of biologically active metabolites which themselves contribute to pathological stroke outcomes. This review is intended to examine two divergent roles of molecular dioxygen in brain tissue as (1) a substrate for life-sustaining homeostatic metabolism of glucose and (2) a substrate for pathogenic metabolism of AA under conditions of stroke. Recent developments in research concerning supplemental oxygen therapy as an intervention to correct the hypoxic component of stroke injury are discussed. Antioxid. Redox Signal. 14, 1889–1903

Autocatalytic nitration of prostaglandin endoperoxide synthase-2 by nitrite inhibits prostanoid formation in rat alveolar macrophages

Aims: Prostaglandin endoperoxide H2 synthase (PGHS) is a well-known target for peroxynitrite-mediated nitration. In several experimental macrophage models, however, the relatively late onset of nitration failed to coincide with the early peak of endogenous peroxynitrite formation. In the present work,weaimed to identify an alternative, peroxynitrite-independent mechanism, responsible for the observed nitration and inactivation of PGHS-2 in an inflammatory cell model. Results: In primary rat alveolar macrophages stimulated with lipopolysaccharide (LPS), PGHS-2 activity was suppressed after 12 h, although the prostaglandin endoperoxide H2 synthase (PGHS-2) protein was still present. This coincided with a nitration of the enzyme. Coincubation with a nitric oxide synthase-2 (NOS - 2) inhibitor preserved PGHS-2 nitration and at the same time restored thromboxane A 2 (TxA 2) synthesis in the cells. Formation of reactive oxygen species (ROS) was maximal at 4 h and then returned to baseline levels. Nitrite (NO 2 -) production occurred later than ROS generation. This rendered generation of peroxynitrite and the nitration of PGHS-2 unlikely. We found that the nitrating agent was formed from NO2-, independent from superoxide (•O 2 - ). Purified PGHS-2 treated with NO 2 - was selectively nitrated on the active site Tyr371, as identified by mass spectrometry (MS). Exposure to peroxynitrite resulted in the nitration not only of Tyr 371, but also of other tyrosines (Tyr). Innovation and Conclusion: The data presented here point to an autocatalytic nitration of PGHS-2 byNO 2 - , catalyzed by the enzyme's endogenous peroxidase activity and indicate a potential involvement of this mechanism in the termination of prostanoid formation under inflammatory conditions. © 2012 Mary Ann Liebert, Inc