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首页> 外文期刊>Supportive care in cancer: official journal of the Multinational Association of Supportive Care in Cancer >Evaluation of an automated pediatric malnutrition screen using anthropometric measurements in the electronic health record: a quality improvement initiative
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Evaluation of an automated pediatric malnutrition screen using anthropometric measurements in the electronic health record: a quality improvement initiative

机译：使用电子健康记录中的人体测量测量评价自动儿科营养不良屏幕：质量改进倡议

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Purpose Malnutrition related to undernutrition in pediatric oncology patients is associated with worse outcomes including increased morbidity and mortality. At a tertiary pediatric center, traditional malnutrition screening practices were ineffective at identifying cancer patients at risk for undernutrition and needing nutrition consultation. Methods To efficiently identify undernourished patients, an automated malnutrition screen using anthropometric data in the electronic health record (EHR) was implemented. The screen utilized pediatric malnutrition (undernutrition) indicators from the 2014 Consensus Statement of the Academy of Nutrition and Dietetics/American Society for Parenteral and Enteral Nutrition with corresponding structured EHR elements. The time periods before (January 2016-August 2017) and after (September 2017-August 2018) screen implementation were compared. Process metrics including nutrition consults, timeliness of nutrition assessments, and malnutrition diagnoses documentation were assessed using statistical process control charts. Outcome metrics including change in nutritional status at least 3 months after positive malnutrition screen were assessed with the Cochran-Armitage trend test. Results After automated malnutrition screen implementation, all process metrics demonstrated center line shifts indicating special cause variation. For patient admissions with a positive screen for malnutrition of any severity level, no significant improvement in status of malnutrition was observed after 3 months (P = .13). Sub-analysis of patient admissions with screen-identified severe malnutrition noted improvement in degree of malnutrition after 3 months (P = .02). Conclusions Select 2014 Consensus Statement indicators for pediatric malnutrition can be implemented as an automated screen using structured EHR data. The automated screen efficiently identifies oncology patients at risk of malnutrition and may improve clinical outcomes.
机译：与儿科肿瘤学患者的营养不良相关的目的营养不良与较差的结果有关，包括发病率和死亡率增加。在第三节儿科中心，传统的营养不良筛查实践在鉴定癌症患者的癌症患者患有营养不良和需要营养咨询的风险上是无效的。实施方法，有效地识别营养不良患者，实施了在电子健康记录（EHR）中使用人体测量数据的自动营养不良屏幕。该屏幕利用2014年营养和营养学院/美国社会课堂委员会委托的儿科营养不良（营养不良）指标进行肠胃外和肠内营养，具有相应的结构化EHR元素。在比较屏幕实施之前（2016年1月至2017年8月）和（2017年8月）的时间段进行了比较。使用统计过程控制图表评估了包括营养咨询，营养评估及营养性评估及营养性诊断文件的过程指标。结果指标，包括在Cochran-Armitage趋势试验中评估阳性营养不良筛选后至少3个月的营养状况的变化。结果在自动营养不良屏幕实施后，所有流程度量都显示了中心线移位，指示特殊原因变化。对于患者培养患者营养不良的患者进行任何严重程度水平，3个月后未观察到营养不良状态的显着提高（P = .13）。筛选筛选严重营养不良的患者录取的分析，注意到3个月后营养不良程度（p = .02）。结论选择2014年度营养不良的共识声明指标可以使用结构化EHR数据作为自动化屏幕实施。自动化屏幕有效地识别营养不良风险的肿瘤患者，可以改善临床结果。

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