Duke University Medical Center, Division of Clinical Informatics, 2200 West Main St., Suite 600, Durham, NC 27710, USA.
J Biomed Inform. 2012 Feb;45(1):120-8. doi: 10.1016/j.jbi.2011.10.001. Epub 2011 Oct 11.
To develop and apply formal ontology creation methods to the domain of antimicrobial prescribing and to formally evaluate the resulting ontology through intrinsic and extrinsic evaluation studies.
We extended existing ontology development methods to create the ontology and implemented the ontology using Protégé-OWL. Correctness of the ontology was assessed using a set of ontology design principles and domain expert review via the laddering technique. We created three artifacts to support the extrinsic evaluation (set of prescribing rules, alerts and an ontology-driven alert module, and a patient database) and evaluated the usefulness of the ontology for performing knowledge management tasks to maintain the ontology and for generating alerts to guide antibiotic prescribing.
The ontology includes 199 classes, 10 properties, and 1636 description logic restrictions. Twenty-three Semantic Web Rule Language rules were written to generate three prescribing alerts: (1) antibiotic-microorganism mismatch alert; (2) medication-allergy alert; and (3) non-recommended empiric antibiotic therapy alert. The evaluation studies confirmed the correctness of the ontology, usefulness of the ontology for representing and maintaining antimicrobial treatment knowledge rules, and usefulness of the ontology for generating alerts to provide feedback to clinicians during antibiotic prescribing.
This study contributes to the understanding of ontology development and evaluation methods and addresses one knowledge gap related to using ontologies as a clinical decision support system component-a need for formal ontology evaluation methods to measure their quality from the perspective of their intrinsic characteristics and their usefulness for specific tasks.
开发并应用正式本体创建方法来处理抗菌药物处方领域的问题，并通过内在和外在评估研究对生成的本体进行正式评估。
我们扩展了现有的本体开发方法来创建本体，并使用 Protégé-OWL 实现了本体。使用一组本体设计原则和通过阶梯技术进行的领域专家审查来评估本体的正确性。我们创建了三个用于支持外在评估的人工制品（一组处方规则、警报和本体驱动的警报模块以及患者数据库），并评估了该本体在执行知识管理任务（维护本体和生成警报以指导抗生素处方）方面的有用性。
该本体包括 199 个类、10 个属性和 1636 个描述逻辑限制。编写了 23 条语义 Web 规则语言规则来生成三个处方警报：（1）抗生素-微生物不匹配警报；（2）药物过敏警报；（3）不推荐的经验性抗生素治疗警报。评估研究证实了本体的正确性、本体在表示和维护抗菌治疗知识规则方面的有用性，以及本体在生成警报以在抗生素处方过程中为临床医生提供反馈方面的有用性。
本研究有助于理解本体开发和评估方法，并解决了一个与将本体用作临床决策支持系统组件相关的知识差距问题——需要正式的本体评估方法来从其内在特征和特定任务的有用性的角度衡量其质量。
