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Timely Interventions for Children with ADHD through Web-Based Monitoring Algorithms

机译:通过基于Web的监视算法对多动症儿童进行及时干预

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摘要

The aim of this study was to evaluate an automated trigger algorithm designed to detect potentially adverse events in children with Attention-Deficit/Hyperactivity Disorder (ADHD), who were monitored remotely between visits. We embedded a trigger algorithm derived from parent-reported ADHD rating scales within an electronic patient monitoring system. We categorized clinicians’ alert resolution outcomes and compared Vanderbilt ADHD rating scale scores between patients who did or did not have triggered alerts. A total of 146 out of 1738 parent reports (8%) triggered alerts for 98 patients. One hundred and eleven alerts (76%) required immediate clinician review. Nurses successfully contacted parents for 68 (61%) of actionable alerts; 46% (31/68) led to a change in care plan prior to the next scheduled appointment. Compared to patients without alerts, patients with alerts demonstrated worsened ADHD severity (β = 5.8, 95% CI: 3.5–8.1 [p < 0.001] within 90 days prior to an alert. The trigger algorithm facilitated timely changes in the care plan in between face-to-face visits.
机译:这项研究的目的是评估一种自动触发算法,该算法旨在检测患有注意力缺陷/多动症(ADHD)的儿童的潜在不良事件,这些儿童在两次就诊之间进行远程监测。我们将触发算法从父母报告的ADHD评定量表中嵌入到电子患者监护系统中。我们对临床医生的警报解决结果进行了分类,并比较了触发警报或未触发警报的患者之间的范德比尔特ADHD评分量表得分。在1738份父母报告中,有146份(占8%)触发了98位患者的警报。一百一十一警报(76%)需要立即临床医生检查。护士成功联系了家长,获得了68(61%)条可行警报; 46%(31/68)的患者在下一次安排的约会之前就改变了护理计划。与没有警报的患者相比,有警报的患者在警报发生前90天内表现出ADHD严重程度恶化(β= 5.8,95%CI:3.5–8.1 [p <0.001]。触发算法有助于及时调整之间的护理计划面对面的访问。

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