Automating incidence and prevalence analysis in open cohorts

Neil Cockburn; Ben Hammond; Illin Gani; Samuel Cusworth; Aditya Acharya; Krishna Gokhale; Rasiah Thayakaran; Francesca Crowe; Sonica Minhas; William Parry Smith; Beck Taylor; Krishnarajah Nirantharakumar; Joht Singh Chandan

doi:10.1186/s12874-024-02266-7

Automating incidence and prevalence analysis in open cohorts

Neil Cockburn^*, Ben Hammond, Illin Gani, Samuel Cusworth, Aditya Acharya, Krishna Gokhale, Rasiah Thayakaran, Francesca Crowe, Sonica Minhas, William Parry Smith, Beck Taylor, Krishnarajah Nirantharakumar, Joht Singh Chandan

^*Corresponding author for this work

Applied Health Sciences

Research output: Contribution to journal › Article › peer-review

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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.

Original language	English
Article number	144
Journal	BMC Medical Research Methodology
Volume	24
Issue number	1
DOIs	https://doi.org/10.1186/s12874-024-02266-7
Publication status	Published - 4 Jul 2024

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Cite this

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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.",

author = "Neil Cockburn and Ben Hammond and Illin Gani and Samuel Cusworth and Aditya Acharya and Krishna Gokhale and Rasiah Thayakaran and Francesca Crowe and Sonica Minhas and Smith, {William Parry} and Beck Taylor and Krishnarajah Nirantharakumar and Chandan, {Joht Singh}",

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T1 - Automating incidence and prevalence analysis in open cohorts

AU - Cockburn, Neil

AU - Hammond, Ben

AU - Gani, Illin

AU - Cusworth, Samuel

AU - Acharya, Aditya

AU - Gokhale, Krishna

AU - Thayakaran, Rasiah

AU - Crowe, Francesca

AU - Minhas, Sonica

AU - Smith, William Parry

AU - Taylor, Beck

AU - Nirantharakumar, Krishnarajah

AU - Chandan, Joht Singh

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N2 - 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.

AB - 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.

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Automating incidence and prevalence analysis in open cohorts

Abstract

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