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EBMT 'eGVHD App' to support GvHD assessment according to NIH criteria-a proof of concept

机译:EBMT'eGVHD App'支持根据NIH标准进行GvHD评估-概念证明

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The EBMT Complications and Quality of Life Working Party has developed a computer-based algorithm, the 'eGVHD App', using a user-centered design process. Accuracy was tested using a quasi-experimental crossover design with four expert-reviewed case vignettes in a convenience sample of 28 clinical professionals. Perceived usefulness was evaluated by the technology acceptance model (TAM) and User satisfaction by the Post-Study System Usability Questionnaire (PSSUQ). User experience was positive, with a median of 6 TAM points (interquartile range: 1) and beneficial median total, and subscale PSSUQ scores. The initial standard practice assessment of the vignettes yielded 65% correct results for diagnosis and 45% for scoring. The 'eGVHD App' significantly increased diagnostic and scoring accuracy to 93% (+ 28%) and 88% (+ 43%), respectively (both P < 0.05). The same trend was observed in the repeated analysis of case 2: accuracy improved by using the App (+ 31% for diagnosis and + 39% for scoring), whereas performance tended to decrease once the App was taken away. The 'eGVHD App' could dramatically improve the quality of care and research as it increased the performance of the whole user group by about 30% at the first assessment and showed a trend for improvement of individual performance on repeated case evaluation.
机译:EBMT并发症和生活质量工作组使用以用户为中心的设计流程开发了一种基于计算机的算法'eGVHD App'。使用准实验交叉设计和28位临床专业人员的便利样本中的四个经过专家评审的病例插图对准确性进行了测试。通过技术接受模型(TAM)评估感知的有用性,并通过研究后系统可用性问卷(PSSUQ)评估用户满意度。用户体验是积极的,中位数为6个TAM点(四分位数范围:1),有益中位数是总和次级量表PSSUQ得分。对小插图的初始标准实践评估得出诊断的正确结果为65%,得分为45%。 “ eGVHD应用程序”显着提高了诊断和评分准确性,分别达到93%(+ 28%)和88%(+ 43%)(均P <0.05)。在案例2的重复分析中观察到了相同的趋势:使用App提高了准确性(诊断为+ 31%,评分为+ 39%),而一旦移除App,性能往往会下降。 “ eGVHD应用程序”可以极大地提高护理和研究的质量,因为它在初次评估时将整个用户群的绩效提高了约30%,并且在反复病例评估中显示出了提高个人绩效的趋势。

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