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

Fuente: arXiv
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Autori principali: Khatib, Hassan S. Al, Neupane, Subash, Mittal, Sudip, Rahimi, Shahram, Marhamati, Nina, Bozorgzad, Sean
Natura: Preprint
Pubblicazione: 2025
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author Khatib, Hassan S. Al
Neupane, Subash
Mittal, Sudip
Rahimi, Shahram
Marhamati, Nina
Bozorgzad, Sean
author_facet Khatib, Hassan S. Al
Neupane, Subash
Mittal, Sudip
Rahimi, Shahram
Marhamati, Nina
Bozorgzad, Sean
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2506_18772
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Patient Journey Ontology: Representing Medical Encounters for Enhanced Patient-Centric Applications
Khatib, Hassan S. Al
Neupane, Subash
Mittal, Sudip
Rahimi, Shahram
Marhamati, Nina
Bozorgzad, Sean
Databases
Computers and Society
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.
title Patient Journey Ontology: Representing Medical Encounters for Enhanced Patient-Centric Applications
topic Databases
Computers and Society
url https://arxiv.org/abs/2506.18772