Evidence map›Paper›PMID 38965539›Full record

ArticleBMC medical research methodology2024

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 and 3 more

Abstract read
In one paragraph

Article in BMC medical research methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Neil CockburnInstitute of Applied Health Research, University of Birmingham, Birmingham, West Midlands, UK. n.cockburn@bham.ac.uk.
Ben HammondInstitute of Applied Health Research, University of Birmingham, Birmingham, West Midlands, UK.
Illin GaniInstitute of Applied Health Research, University of Birmingham, Birmingham, West Midlands, UK.
Samuel CusworthInstitute of Applied Health Research, University of Birmingham, Birmingham, West Midlands, UK.
Aditya AcharyaInstitute of Applied Health Research, University of Birmingham, Birmingham, West Midlands, UK.
Krishna GokhaleInstitute of Applied Health Research, University of Birmingham, Birmingham, West Midlands, UK.
Rasiah ThayakaranInstitute of Applied Health Research, University of Birmingham, Birmingham, West Midlands, UK.
Francesca CroweInstitute of Applied Health Research, University of Birmingham, Birmingham, West Midlands, UK.
Sonica MinhasInstitute of Applied Health Research, University of Birmingham, Birmingham, West Midlands, UK.
William Parry SmithDepartment of Obstetrics and Gynaecology, Shrewsbury and Telford Hospitals NHS Trust, Telford, Shropshire, UK.
Beck TaylorWarwick Medical School, Warwick University, Coventry, Warwickshire, UK.
Krishnarajah NirantharakumarInstitute of Applied Health Research, University of Birmingham, Birmingham, West Midlands, UK.
Joht Singh ChandanInstitute of Applied Health Research, University of Birmingham, Birmingham, West Midlands, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationData 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 .

Indexed as

Electronic Health RecordsCohort StudiesHumansIncidencePrevalenceReproducibility of ResultsSoftware

Identifiers

PMID38965539
PMCPMC11223317

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.