Addressing Data Quality Challenges in Lung Cancer Data Within the Observational Medical Outcomes Partnership Common Data Model: Observational Study
Jens Declerck, Mieke Deschepper, Kirsten Colpaert, Dipak Kalra, Pascal Coorevits, Matthew Balcarras · 2026
Read Addressing Data Quality Challenges in Lung Cancer Data Within the Observational Medical Outcomes Partnership Common Data Model: Observational Study by Jens Declerck, Mieke Deschepper, Kirsten Colpaert, Dipak Kalra, Pascal Coorevits, Matthew Balcarras (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13245838.txt.
Description
Declerck, Deschepper, and Colpaert documented what gets lost when hospital data are translated into a common research format, in this 2026 Journal of Medical Internet Research study. Large multicenter studies rely on the OMOP Common Data Model, which requires mapping each hospital's records into shared concepts. The team mapped lung cancer data from Ghent University Hospital and audited consistency and completeness against the source.
Structured variables mapped consistently and nearly completely. The losses clustered in unstructured information: smoking status, recorded as free text, had to be dropped entirely for lack of a fitting concept. Diagnostic codes differed in granularity between institutions. An evolving reference dictionary added friction throughout. The authors conclude that reliable multicenter datasets require sustained collaboration between clinicians and data engineers, not a one-off technical conversion.
Catalog record
| CREATOR | Jens Declerck, Mieke Deschepper, Kirsten Colpaert, Dipak Kalra, Pascal Coorevits, Matthew Balcarras |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 38 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |