Romao Patricia, Neuenschwander Stefanie, Zbinden Chantal, Seidel Kathleen, Sariyar Murat
Bern University of Applied Sciences, Bern, Switzerland.
Department of Neurosurgery, Inselspital, University Hospital, Bern, Switzerland.
BMC Med Inform Decis Mak. 2024 Jul 31;24(1):216. doi: 10.1186/s12911-024-02615-y.
Intraoperative neurophysiological monitoring (IOM) plays a pivotal role in enhancing patient safety during neurosurgical procedures. This vital technique involves the continuous measurement of evoked potentials to provide early warnings and ensure the preservation of critical neural structures. One of the primary challenges has been the effective documentation of IOM events with semantically enriched characterizations. This study aimed to address this challenge by developing an ontology-based tool.
We structured the development of the IOM Documentation Ontology (IOMDO) and the associated tool into three distinct phases. The initial phase focused on the ontology's creation, drawing from the OBO (Open Biological and Biomedical Ontology) principles. The subsequent phase involved agile software development, a flexible approach to encapsulate the diverse requirements and swiftly produce a prototype. The last phase entailed practical evaluation within real-world documentation settings. This crucial stage enabled us to gather firsthand insights, assessing the tool's functionality and efficacy. The observations made during this phase formed the basis for essential adjustments to ensure the tool's productive utilization.
The core entities of the ontology revolve around central aspects of IOM, including measurements characterized by timestamp, type, values, and location. Concepts and terms of several ontologies were integrated into IOMDO, e.g., the Foundation Model of Anatomy (FMA), the Human Phenotype Ontology (HPO) and the ontology for surgical process models (OntoSPM) related to general surgical terms. The software tool developed for extending the ontology and the associated knowledge base was built with JavaFX for the user-friendly frontend and Apache Jena for the robust backend. The tool's evaluation involved test users who unanimously found the interface accessible and usable, even for those without extensive technical expertise.
Through the establishment of a structured and standardized framework for characterizing IOM events, our ontology-based tool holds the potential to enhance the quality of documentation, benefiting patient care by improving the foundation for informed decision-making. Furthermore, researchers can leverage the semantically enriched data to identify trends, patterns, and areas for surgical practice enhancement. To optimize documentation through ontology-based approaches, it's crucial to address potential modeling issues that are associated with the Ontology of Adverse Events.
术中神经生理监测（IOM）在提高神经外科手术患者安全性方面发挥着关键作用。这项重要技术涉及对诱发电位的持续测量，以提供早期预警并确保关键神经结构的保留。主要挑战之一是有效地记录具有语义丰富特征的IOM事件。本研究旨在通过开发一种基于本体的工具来应对这一挑战。
我们将IOM文档本体（IOMDO）及相关工具的开发分为三个不同阶段。初始阶段专注于本体的创建，借鉴了开放生物医学本体（OBO）原则。随后阶段涉及敏捷软件开发，这是一种灵活的方法，用于封装各种需求并迅速生成原型。最后阶段需要在实际文档环境中进行实际评估。这个关键阶段使我们能够收集第一手见解，评估工具的功能和功效。在此阶段所做的观察为进行必要调整提供了依据，以确保工具的有效利用。
本体的核心实体围绕IOM的核心方面展开，包括以时间戳、类型、值和位置为特征的测量。多个本体的概念和术语被整合到IOMDO中，例如，解剖学基础模型（FMA）、人类表型本体（HPO）以及与一般外科术语相关的手术过程模型本体（OntoSPM）。为扩展本体和相关知识库而开发的软件工具，其用户友好的前端使用JavaFX构建，强大的后端使用Apache Jena构建。该工具的评估涉及测试用户，他们一致认为该界面易于访问和使用，即使对于那些没有广泛技术专长的用户也是如此。
通过建立一个用于描述IOM事件的结构化和标准化框架，我们基于本体的工具有可能提高文档质量，通过改善明智决策的基础使患者护理受益。此外，研究人员可以利用语义丰富的数据来识别趋势、模式以及手术实践改进的领域。为了通过基于本体的方法优化文档，解决与不良事件本体相关的潜在建模问题至关重要。
