The rapid guide includes three diagnosis recommendations and four management recommendations covering patients with suspected or confirmed COVID-19 with different levels of disease severity, throughout the care pathway from outpatient facility or hospital entry, to home discharge. The rapid guide offers considerations about implementation, monitoring and evaluation, and identifies research needs. The guide will be relevant for clinicians, hospital managers and planners, policy-makers, hospital architects, biomedical engineers, medical physicists, logistics staff, and control officers involved in water/sanitation and infection prevention.
Objective:The aim of this study is to offer appropriate criteria to evaluate effective dashboards for healthcare organizations.Method:In a Delphi study, a team of information technology consultants were asked to determine a set of user interface requirements for evaluating, building or selecting the dashboard. In the first round, a list of main features or criteria to be used was determined based on the panel’s rating,.Results:In this study, it was revealed that a set of key criteria for evaluating the dashboards can be used for all types of dashboards. These criteria were classified into 7 main categories including user customization, knowledge discovery, security, information delivery, alerting, visual design, and integration and system connectivity.Conclusion:Choosing good criteria for selecting effective dashboards for healthcare organizations is very critical because these organizations follow a data-intensive and technology-driven environment. This study revealed the importance of key criteria which can guarantee development of an evaluation checklist.
A 63-year-old man, who underwent conventional coronary angiography, because of a finding of a confusing vascular structure, was referred for 64-multislice spiral computed tomography (MSCT). His MSCT showed bilateral coronary-pulmonary artery fistula from both right and left coronary arteries via a dilated fistulous vascular malformation. Considering its reasonably high spatial and temporal resolutions, MSCT is regarded as a valuable technique to clarify the diagnosis in incidentally found equivocal cases of coronary fistula in conventional coronary angiography.
Various studies have shown that medical professionals are prone to follow the incorrect suggestions offered by algorithms, especially when they have limited inputs to interrogate and interpret such suggestions and when they have an attitude of relying on them. We examine the effect of correct and incorrect algorithmic suggestions on the diagnosis performance of radiologists when (1) they have no, partial, and extensive informational inputs for explaining the suggestions (study 1) and (2) they are primed to hold a positive, negative, ambivalent, or neutral attitude towards AI (study 2). Our analysis of 2760 decisions made by 92 radiologists conducting 15 mammography examinations shows that radiologists’ diagnoses follow both incorrect and correct suggestions, despite variations in the explainability inputs and attitudinal priming interventions. We identify and explain various pathways through which radiologists navigate through the decision process and arrive at correct or incorrect decisions. Overall, the findings of both studies show the limited effect of using explainability inputs and attitudinal priming for overcoming the influence of (incorrect) algorithmic suggestions.
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