The “engine room” of a multicentre geriatric otolaryngology network: data curation, quality assurance, and research readiness of the ENT Geriatric Database

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Abstract
Introduction: Multi-centre datasets are becoming essential for evidence-based decision-making in geriatric otolaryngology, yet their reliability depends on a transparent and reproducible process of data preparation.Aim: To present the complete “engine-room” workflow of the ENT Geriatric Database – a harmonised, anonymised multi-centre dataset – and to demonstrate how systematic data curation supports trustworthy analyses of perioperative risk and outcomes in elderly patients.Methods: The study integrated 16 Excel files from eight tertiary ENT centres into a unified dataset of 888 patients aged 65 years and older. The scripted pipeline standardised 97 canonical variables using positional and keyword-based mapping, removed personally identifiable information, harmonised heterogeneous coding schemes across 44 variables, and performed a multilevel data-quality audit.Results: The workflow revealed major structural and clinical data-quality issues: five variables exceeded 50% overall missingness, 44 had coded-missing categories, and 99 potential duplicates were detected. Five centre-specific block patterns indicated how procedural differences influence data completeness. All cleaned data, missingness matrices, and anomaly logs were exported for independent review.Conclusions: A scripted, auditable curation pipeline can transform heterogeneous spreadsheets into a more reliable multicentre dataset. Investing in this “engine-room” infrastructure strengthens data validity and provides a more robust basis for perioperative risk estimation and meaningful inter-centre comparisons in geriatric otolaryngology.

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