Neil Cockburn
Automating incidence and prevalence analysis in open cohorts
Cockburn, Neil; Hammond, Ben; Gani, Illin; Cusworth, Samuel; Acharya, Aditya; Gokhale, Krishna; Thayakaran, Rasiah; Crowe, Francesca; Minhas, Sonica; Parry-Smith, William; Taylor, Beck; Nirantharakumar, Krishnarajah; Chandan, Joht Singh
Authors
Ben Hammond
Illin Gani
Samuel Cusworth
Aditya Acharya
Krishna Gokhale
Rasiah Thayakaran
Francesca Crowe
Sonica Minhas
Professor William Parry-Smith w.r.parry-smith@keele.ac.uk
Beck Taylor
Krishnarajah Nirantharakumar
Joht Singh Chandan
Abstract
Motivation
Data is increasingly used for improvement and research in public health, especially administrative data such as that collected in electronic health records. Patients enter and exit these typically open-cohort datasets non-uniformly; this can render simple questions about incidence and prevalence time-consuming and with unnecessary variation between analyses. We therefore developed methods to automate analysis of incidence and prevalence in open cohort datasets, to improve transparency, productivity and reproducibility of analyses.
Implementation
We provide both a code-free set of rules for incidence and prevalence that can be applied to any open cohort, and a python Command Line Interface implementation of these rules requiring python 3.9 or later.
General features
The Command Line Interface is used to calculate incidence and point prevalence time series from open cohort data. The ruleset can be used in developing other implementations or can be rearranged to form other analytical questions such as period prevalence.
Availability
The command line interface is freely available from https://github.com/THINKINGGroup/analogy_publication.
Citation
Cockburn, N., Hammond, B., Gani, I., Cusworth, S., Acharya, A., Gokhale, K., …Chandan, J. S. (in press). Automating incidence and prevalence analysis in open cohorts. BMC medical research methodology, 24, Article 144. https://doi.org/10.1186/s12874-024-02266-7
Journal Article Type | Article |
---|---|
Acceptance Date | Jun 24, 2024 |
Online Publication Date | Jul 4, 2024 |
Deposit Date | Jul 8, 2024 |
Publicly Available Date | Jul 8, 2024 |
Journal | BMC Medical Research Methodology |
Print ISSN | 1471-2288 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 24 |
Article Number | 144 |
DOI | https://doi.org/10.1186/s12874-024-02266-7 |
Public URL | https://keele-repository.worktribe.com/output/872141 |
Publisher URL | https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-024-02266-7 |
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Automating incidence and prevalence analysis in open cohorts
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Licence
https://creativecommons.org/licenses/by/4.0/
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
Copyright Statement
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
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