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arXiv:2506.18772 (cs)
[Submitted on 4 Mar 2025 ]

Title: Patient Journey Ontology: Representing Medical Encounters for Enhanced Patient-Centric Applications

Title: 患者旅程本体:为增强以患者为中心的应用程序表示医疗会诊

Authors:Hassan S. Al Khatib, Subash Neupane, Sudip Mittal, Shahram Rahimi, Nina Marhamati, Sean Bozorgzad
Abstract: The healthcare industry is moving towards a patient-centric paradigm that requires advanced methods for managing and representing patient data. This paper presents a Patient Journey Ontology (PJO), a framework that aims to capture the entirety of a patient's healthcare encounters. Utilizing ontologies, the PJO integrates different patient data sources like medical histories, diagnoses, treatment pathways, and outcomes; it enables semantic interoperability and enhances clinical reasoning. By capturing temporal, sequential, and causal relationships between medical encounters, the PJO supports predictive analytics, enabling earlier interventions and optimized treatment plans. The ontology's structure, including its main classes, subclasses, properties, and relationships, as detailed in the paper, demonstrates its ability to provide a holistic view of patient care. Quantitative and qualitative evaluations by Subject Matter Experts (SMEs) demonstrate strong capabilities in patient history retrieval, symptom tracking, and provider interaction representation, while identifying opportunities for enhanced diagnosis-symptom linking. These evaluations reveal the PJO's reliability and practical applicability, demonstrating its potential to enhance patient outcomes and healthcare efficiency. This work contributes to the ongoing efforts of knowledge representation in healthcare, offering a reliable tool for personalized medicine, patient journey analysis and advancing the capabilities of Generative AI in healthcare applications.
Abstract: 医疗行业正朝着以患者为中心的模式发展,这需要先进的方法来管理和表示患者数据。 本文提出了一个患者旅程本体(PJO),这是一个旨在捕捉患者全部医疗经历的框架。 利用本体,PJO整合了如病史、诊断、治疗路径和结果等不同的患者数据来源;它实现了语义互操作性并增强了临床推理。 通过捕捉医疗经历之间的时空、顺序和因果关系,PJO支持预测分析,使早期干预和优化治疗方案成为可能。 本体的结构,包括其主要类、子类、属性和关系,如论文中所述,展示了其提供患者护理整体视图的能力。 领域专家(SMEs)进行的定量和定性评估表明,在患者病史检索、症状跟踪和提供者互动表示方面具有强大的能力,同时指出了增强诊断与症状关联的机会。 这些评估揭示了PJO的可靠性和实际应用价值,证明了其在提高患者结果和医疗效率方面的潜力。 这项工作为医疗保健中的知识表示持续努力做出了贡献,为个性化医学、患者旅程分析以及推动生成式人工智能在医疗应用中的能力提供了可靠的工具。
Subjects: Databases (cs.DB)
Cite as: arXiv:2506.18772 [cs.DB]
  (or arXiv:2506.18772v1 [cs.DB] for this version)
  https://doi.org/10.48550/arXiv.2506.18772
arXiv-issued DOI via DataCite

Submission history

From: Hassan Al Khatib [view email]
[v1] Tue, 4 Mar 2025 13:05:47 UTC (2,834 KB)
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