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A Semantic Web Technology Based Approach to Identify Hypertensive Patients for Follow-Up/Recall

机译:基于语义的网络技术识别高血压患者的后续/召回

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We present an ontology based approach to identify hypertensive patients who show non-adherence to prescribed medication. Using the Web Ontology Language (OWL), we have developed an ontology that includes patient prescription details, medication possession ratios (MPRs) and blood pressure measurements (together with other patient related information) that has been populated with production electronic medical record (EMR) data from a General Medical Practice in New Zealand. We have written queries using the Semantic Query-enhanced Web Rule Language (SQWRL) to query this ontology to determine patients who have lapsed medication while having a low MPR. We also discuss some practical issues related to patient recall based on EMR data, as well as the suitability of the proposed scheme.
机译:我们提出了一种基于本体的方法来鉴定表现出不遵守规定药物的高血压患者。使用Web本体语言(猫头鹰),我们开发了一种本体论,其中包括患者处方细节,药物占有率(MPRS)和血压测量(以及其他患者相关信息),这些患者已填充了生产电子医疗记录(EMR)来自新西兰一般医疗实践的数据。我们使用了语义查询增强的Web规则语言(SQWRL)来查询该本体的疑问,以确定具有低MPR的药物的患者。我们还讨论了根据EMR数据的患者召回相关的一些实际问题,以及所提出的计划的适用性。

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