Oppenheimer Julia, Ojo Oluwafemi, Antonetty Annalee, Chiujdea Madeline, Garcia Stephanie, Weas Sarah, Loddenkemper Tobias, Fleegler Eric, Chan Eugenia
Department of Neurology, Boston Children's Hospital, Boston, MA 02115, USA.
Division of Developmental Medicine, Boston Children's Hospital, Boston, MA 02115, USA.
Diseases. 2019 Feb 7;7(1):20. doi: 10.3390/diseases7010020.
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 [ < 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.
本研究的目的是评估一种自动触发算法，该算法旨在检测注意缺陷多动障碍（ADHD）患儿在就诊间隔期间进行远程监测时的潜在不良事件。我们将源自家长报告的ADHD评定量表的触发算法嵌入电子患者监测系统中。我们对临床医生的警报解决结果进行分类，并比较触发警报和未触发警报的患者之间的范德比尔特ADHD评定量表得分。在1738份家长报告中，共有146份（8%）为98名患者触发了警报。111份警报（76%）需要临床医生立即审查。护士成功联系了68份（61%）可采取行动的警报的家长；46%（31/68）的警报导致在下一次预定预约前护理计划发生改变。与未触发警报的患者相比，触发警报的患者在警报前90天内ADHD严重程度恶化（β = 5.8，95% CI：3.5⁻8.1 [ < 0.001]）。触发算法有助于在面对面就诊之间及时改变护理计划。
