An automation framework for clinical codelist development validated with UK data from patients with multiple long-term conditions

Abstract Background Codelists play a crucial role in ensuring accurate and standardized communication within healthcare. However, preparation of high-quality codelists is a rigorous and time-consuming process. The literature focuses on transparency of clinical codelists and overlooks the utility of...

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Auteurs principaux:	A. Aslam, L. Walker, M. Abaho, H. Cant, M. O’Connell, A. S. Abuzour, L. Hama, P. Schofield, F. S. Mair, R. A. Ruddle, O. Popoola, M. Sperrin, J. Y. Tsang, E. Shantsila, M. Gabbay, A. Clegg, A. A. Woodall, I. Buchan, S. D. Relton
Format:	Artigo
Langue:	Inglês
Publié:	BMC 2025-05-01
Collection:	BMC Medical Research Methodology
Sujets:	Codelist Automation Multiple long term conditions (MLTC) SNOMEDs DynAIRx
Accès en ligne:	https://doi.org/10.1186/s12874-025-02541-1
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