Hong Xinting, Liu Chang, Momotaz Hasina, Cassidy Kristin, Sajatovic Martha, Sahoo Satya S
Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH.
Department of Neurology, University Hospitals Cleveland Medical Center, Cleveland, OH.
AMIA Annu Symp Proc. 2020 Mar 4;2019:1071-1080. eCollection 2019.
Self-management techniques that assist patients with chronic conditions, such as epilepsy, diabetes, and arthritis, play an important role in managing and caring for their conditions. The US Center for Disease Control and Prevention (CDC)-funded Managing Epilepsy Well (MEW) Network consists of 11 study sites across the US that aims to develop and disseminate self-management techniques for epilepsy patients. Epilepsy affects more than 65 million patients worldwide with serious negative impact on their own as well as their family member's quality of life. Taking advantage of advances in biomedical informatics, the MEW Network has created an integrated database (MEW DB) using a common data model and two tiers of study variables. The MEW DB consists of 1680 patient data records covering a wide range of patient population nationwide. Therefore, there is growing interest in the use of the MEW DB for different cohort query analysis. To address the challenges in: (1) selecting appropriate MEW research studies based on inclusion/exclusion criteria; (2) creating a patient cohort for given research hypothesis; and (3) performing appropriate statistical tests; we have developed an integrated data query and statistical analysis informatics tool called Insight. The Insight platform features an intuitive user interface to support the three phases of study selection, patient cohort creation, and statistical testing with the use of an epilepsy domain ontology to support ontology-driven query expansion. We evaluate the Insight platform using two user evaluation methods of "first click testing" and "user satisfaction survey". In addition, we performed a time performance test of the Insight platform using four patient datasets and three statistical test. The results of the user evaluation show that Insight platform is strongly approved by the users and the results of the time performance show that there is marginal difference in performance as the volume of patient data increases in the MEW DB.
自我管理技巧有助于患有慢性疾病(如癫痫、糖尿病和关节炎)的患者管理和护理自身病情,发挥着重要作用。由美国疾病控制与预防中心(CDC)资助的癫痫良好管理(MEW)网络由美国各地的11个研究站点组成,旨在为癫痫患者开发和推广自我管理技巧。癫痫影响着全球超过6500万患者,对他们自身以及家庭成员的生活质量产生严重负面影响。利用生物医学信息学的进展,MEW网络使用通用数据模型和两层研究变量创建了一个综合数据库(MEW DB)。MEW DB包含1680条患者数据记录,覆盖了全国广泛的患者群体。因此,人们越来越有兴趣将MEW DB用于不同的队列查询分析。为应对以下挑战:(1)根据纳入/排除标准选择合适的MEW研究;(2)为给定的研究假设创建患者队列;(3)进行适当的统计测试;我们开发了一种名为Insight的综合数据查询和统计分析信息工具。Insight平台具有直观的用户界面,以支持研究选择、患者队列创建和统计测试这三个阶段,并使用癫痫领域本体来支持本体驱动的查询扩展。我们使用“首次点击测试”和“用户满意度调查”这两种用户评估方法对Insight平台进行评估。此外,我们使用四个患者数据集和三种统计测试对Insight平台进行了时间性能测试。用户评估结果表明,Insight平台得到了用户的高度认可,时间性能测试结果表明,随着MEW DB中患者数据量的增加,性能仅有微小差异。