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Comparative Study of ETL Tools for Transforming Healthcare Data to the OMOP Common Data Model (CDM)

Year: 2025

Type: book-chapter

Abstract: Healthcare data is often complex, sparse, and frequently updated, which makes standardization essential. The OMOP Common Data Model (CDM) is gaining increasing attention because of its ability to standardize healthcare data and enable consistent and reproducible research outputs. This paper evaluates three ETL (Extract, Transform, Load) tools: Pentaho, Apache NiFi, and a custom-built tool to transform healthcare data into the OMOP CDM. The evaluation criteria, based on a literature review, include connectivity and interoperability, user interface and ease of use, performance, and technical flexibility. Results indicate that while minor differences in the tools' features exist, all tools are adequate for basic transformation tasks. Pentaho is noted for its ease of use, particularly helpful for non-expert users, while Apache NiFi is better suited for more advanced users. A custom-built tool, though often offering user-friendly interfaces and more flexibility, comes at the cost of additional development efforts.

Source: Studies in health technology and informatics

DOI: 10.3233/shti250590

Authors: Adnan Jouned, Heike Düsseldorf, Florian Katsch, Maryam Jafarpour, Georg Duftschmid

Institutions: Medical University of Vienna, Ludwig Boltzmann Institute for Digital Health and Prevention

Language: English

Topic: Electronic Health Records Systems

Subfield: Health Information Management

Field: Health Professions

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

OpenAlex ID: W4410447698

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