These codelists are part of DynAIRx Project. DynAIRx has been funded by the National Institute for Health and Care Research (NIHR) Artificial Intelligence for Multiple Long-Term Conditions (AIM).
Collaboration This NIHR Funded project is collaboration of University of Manchester, University of Leeds, University of Liverpool, Merseycare NHS, Wales Powys Teaching Health Board, and University of Glasgow, UK.
About DynAIRx DynAIRx (Artificial Intelligence for dynamic prescribing optimisation and care integration in multimorbidity) aims to develop new, easy to use, artificial intelligence (AI) tools that support General Practitioners (GPs) and pharmacists to find patients living with multimorbidity (two or more long-term health conditions) who might be offered a better combination of medicines.
Pleaase use this link to know more about DynAIRx.
This repository contains codelists (consisting of SNOMEDs) of ~260 coditions. Mappings from SNOMEOs to ReadCode, MedCode or any other codes are avaliable in DynAIRx framework. These lists are compiled mainly with baseline codelists eFI, Caliber, and few other project specific codelists. Please find more details in paper.
These codelists are generated using Generalised Codelist Automation Framework (GCAF). This is generalized framework developed by Computer Scientists to generate codelists for any medical project with modifications in input. Please use this link to use this framework in your project.
If you use this work in your research or project, please cite the following paper:
Aslam, A., Walker, L., Abaho, M., Cant, H., O'Connell, M., Abuzour, A. S., Hama, L., Schofield, P., Mair, F.S., Ruddle, R.A., Popoola, O., Sperrin, M., Tsang, J.Y., Shantsila, E., Gabbay, M., Clegg, A., Woodall, A.A., Buchan, I., & Relton, S. D. (2024). An Automation Framework for Clinical Codelist Development Validated with UK Data from Patients with Multiple Long-term Conditions. medRxiv. https://doi.org/10.1101/2024.09.25.24314215
You can access the full paper here.
@article {Aslam2024.09.25.24314215,
author = {Aslam, A. and Walker, L. and Abaho, M. and Cant, H. and O Connell, M. and Abuzour, A. S. and Hama, L. and Schofield, P. and Mair, F.S. and Ruddle, R.A. and Popoola, O. and Sperrin, M. and Tsang, J.Y. and Shantsila, E. and Gabbay, M. and Clegg, A. and Woodall, A.A. and Buchan, I. and Relton, S. D.},
title = {An Automation Framework for Clinical Codelist Development Validated with UK Data from Patients with Multiple Long-term Conditions},
elocation-id = {2024.09.25.24314215},
year = {2024},
doi = {10.1101/2024.09.25.24314215},
publisher = {Cold Spring Harbor Laboratory Press},
URL = {https://www.medrxiv.org/content/early/2024/09/26/2024.09.25.24314215},
eprint = {https://www.medrxiv.org/content/early/2024/09/26/2024.09.25.24314215.full.pdf},
journal = {medRxiv}
}
- Dr Asra Aslam (onbehalf of DynAIRx)
- GitHub: [@AsraAslam7] GitHub, LinkedIn, HomePage
- Email: [email protected], [email protected]