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Background <p>The geriatric population is a vulnerable population that has higher rate of chronic disease and represents the largest portion of healthcare delivered. This population is vulnerable to medication non-adherence. Patient medication non-adherence is a problem that can lead to increase morbidity and mortality and waste of resources. Reasons for this phenomenon are multifactorial and include poor health literacy.</p> Results <p>To address this issue, we created a patient-directed drug information knowledge graph using both patient-directed resources and the Vaccine Information Statement Ontology (VISO), and attempt to validate the knowledge graph with common patient questions. This knowledge graph model (Patient-centric Drug Knowledge Graph) includes a terminological size of 577 term nodes and 113 links. We also created five knowledge graphs using the Patient-centric Drug Knowledge Graph (PcDKG) framework that represent five top medications (<i>atorvastatin</i>, <i>levothyroxine</i>, <i>lisinopril</i>, <i>metformin</i>, and <i>amlodipine</i>) used by the geriatric population. The common patient questions were converted to SPARQL queries to assess the coverage the model.</p> Conclusion <p>This initial development of the PcDKG is first knowledge graph that synthesizes concepts relating to drug information needs of the consumer population, specifically the geriatric population. This work also evolves the previous work of the VISO knowledge graph to cover wider range of medication knowledge for patients. PcDKG aims to be integrated in patient-directed tools to leverage its knowledge base, and future direction is to integrate PcDKG for digital health tools directed to the geriatric population. Our work is publicly available on our GitHub repository along with the five instance knowledge graph models.</p>

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An application-based ontological knowledge base of medications to support health literacy and adherence for the consumer population: an aging population use case

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月29日

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  • Clifford Chen,
  • Muhammad Amith,
  • Kirk Roberts,
  • Rebecca Mauldin,
  • Renata Komalasari,
  • Cui Tao

摘要

Background

The geriatric population is a vulnerable population that has higher rate of chronic disease and represents the largest portion of healthcare delivered. This population is vulnerable to medication non-adherence. Patient medication non-adherence is a problem that can lead to increase morbidity and mortality and waste of resources. Reasons for this phenomenon are multifactorial and include poor health literacy.

Results

To address this issue, we created a patient-directed drug information knowledge graph using both patient-directed resources and the Vaccine Information Statement Ontology (VISO), and attempt to validate the knowledge graph with common patient questions. This knowledge graph model (Patient-centric Drug Knowledge Graph) includes a terminological size of 577 term nodes and 113 links. We also created five knowledge graphs using the Patient-centric Drug Knowledge Graph (PcDKG) framework that represent five top medications (atorvastatin, levothyroxine, lisinopril, metformin, and amlodipine) used by the geriatric population. The common patient questions were converted to SPARQL queries to assess the coverage the model.

Conclusion

This initial development of the PcDKG is first knowledge graph that synthesizes concepts relating to drug information needs of the consumer population, specifically the geriatric population. This work also evolves the previous work of the VISO knowledge graph to cover wider range of medication knowledge for patients. PcDKG aims to be integrated in patient-directed tools to leverage its knowledge base, and future direction is to integrate PcDKG for digital health tools directed to the geriatric population. Our work is publicly available on our GitHub repository along with the five instance knowledge graph models.