Bonino Angela Yarnell, Mood Deborah
Department of Speech, Language, and Hearing Sciences, University of Colorado Boulder, Boulder, CO, United States.
Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, United States.
Front Psychol. 2023 Mar 15;14:1134034. doi: 10.3389/fpsyg.2023.1134034. eCollection 2023.
Recent advancements in big data analytics and the formation of large-scale clinical data repositories provide a unique opportunity to determine the current state of pediatric hearing health care for children who have developmental disabilities. Before answering unresolved questions about diagnostic practice, it is paramount to determine a standard and reliable method for identifying children who have reduced hearing because clinical management is affected by hearing status. The purpose of this study was to compare 5 different methods for identifying cases of reduced hearing from pure-tone thresholds based on developmental disability status.
Using retrospective clinical data from 100,960 children (0-18 years), hearing status was determined for a total of 226,580 encounters from three clinical sites. 9% of the children had a diagnosis of intellectual disability, autism spectrum disorder, Down syndrome, or cerebral palsy.
Results revealed that encounters from children who have developmental disabilities were more likely to have insufficient data to allow hearing status to be determined. Moreover, methods with higher data demands (i.e., number of thresholds and ear-specific thresholds) resulted in fewer classifiable encounters. The average child age when hearing status was classified for the first time was older for children who have developmental disabilities than for children in the comparison group. Allowing thresholds to build up over multiple test sessions did result in more children who have developmental disabilities being classified than for single-encounter methods, but a meaningful decrease in child age at the time of classification was not seen for this strategy. Compared to the comparison group, children who have developmental disabilities were more likely to have reduced hearing that was stable over time, yet their hearing status was determined at older ages.
Results provide key guidance to researchers for how to determine hearing status in children for big data applications using electronic health records. Furthermore, several assessment disparities are spotlighted for children who have developmental disabilities that warrant further investigation.
大数据分析的最新进展以及大规模临床数据存储库的形成,为确定发育障碍儿童的儿科听力保健现状提供了独特的机会。在回答有关诊断实践的未解决问题之前,确定一种标准且可靠的方法来识别听力减退的儿童至关重要,因为临床管理会受到听力状况的影响。本研究的目的是比较5种基于发育障碍状态从纯音阈值识别听力减退病例的不同方法。
利用来自100960名儿童(0至18岁)的回顾性临床数据,确定了来自三个临床地点的总共226580次就诊的听力状况。9%的儿童被诊断患有智力残疾、自闭症谱系障碍、唐氏综合征或脑瘫。
结果显示,发育障碍儿童的就诊更有可能没有足够的数据来确定听力状况。此外,数据要求较高的方法(即阈值数量和特定耳朵的阈值)导致可分类的就诊次数较少。首次对听力状况进行分类时,发育障碍儿童的平均年龄比对照组儿童大。允许在多个测试阶段积累阈值确实比单次就诊方法能使更多发育障碍儿童被分类,但该策略并未使分类时儿童的年龄有显著降低。与对照组相比,发育障碍儿童更有可能出现随时间稳定的听力减退,然而他们的听力状况是在较大年龄时才得以确定。
研究结果为研究人员如何利用电子健康记录在大数据应用中确定儿童听力状况提供了关键指导。此外,还突出了发育障碍儿童存在的几个评估差异,值得进一步研究。