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Mapping clinical procedures to the ICD-10-PCS: The German operation and procedure classification system use case
A Millan-Fernandez-Montes1, D Perez-Rey1, G Hernandez-Ibarburu1
1Biomedical Informatics Group, Departamento de Inteligencia Artificial, ETSI Informáticos, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain.
This study introduces a novel method for mapping healthcare data to the International Classification of Diseases 10th Revision Procedure Classification System (ICD-10-PCS). The approach enhances semantic interoperability for clinical research by leveraging ICD-10-PCS structure.
Area of Science:
- Health Informatics
- Medical Terminology
- Data Science
Background:
- Semantic interoperability is crucial for analyzing diverse healthcare data sources.
- Mapping to the International Classification of Diseases 10th Revision Procedure Classification System (ICD-10-PCS) is challenging due to its complexity and limited clinical terms.
- Real-world data (RWD) terminologies often prioritize reimbursement over clinical utility.
Purpose of the Study:
- To propose a novel theoretical methodology for mapping healthcare data to ICD-10-PCS.
- To address the challenges posed by ICD-10-PCS's multiaxial structure and physician terminology.
- To facilitate the integration of heterogeneous data sources for clinical research.
Main Methods:
- Exploiting the multiaxial structure of ICD-10-PCS to reduce concept search spaces.
- Leveraging dependencies between ICD-10-PCS axes to infer additional relevant information.
- Testing the methodology using a subset of the German Operation and Procedure Classification System (OPS).
Main Results:
- The proposed methodology effectively maps healthcare data to ICD-10-PCS.
- The approach enhances the integration of heterogeneous data sources.
- Demonstrated feasibility using the German Operation and Procedure Classification System (OPS).
Conclusions:
- The developed methodology offers a promising solution for semantic interoperability with ICD-10-PCS.
- This work contributes to more homogeneous analysis of diverse clinical research data.
- The approach addresses key challenges in mapping clinical data to structured procedure classifications.
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