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Query the 'NHS TRUD API' · Issue #689 · ropensci/software-review · GitHub

Submitting Author Name: Alasdair Warwick
Submitting Author Github Handle: @rmgpanw
Other Package Authors Github handles: (comma separated, delete if none) @abolvera, @cyu12, @rnluben
Repository: https://github.com/rmgpanw/trud/
Submission type: Pre-submission
Language: en

• Paste the full DESCRIPTION file inside a code block below:

Package: trud
Title: Query the 'NHS TRUD API'
Version: 0.1.0.9000
Authors@R: c(
    person(given = "Alasdair",
           family = "Warwick",
           role = c("aut", "cre", "cph"),
           email = "alasdair.warwick.19@ucl.ac.uk",
           comment = c(ORCID = "0000-0002-0800-2890")),
    person("Robert", "Luben", role = "aut",
           comment = c(ORCID = "0000-0002-5088-6343")),
    person("Abraham", "Olvera-Barrios", role = "aut",
           comment = c(ORCID = "0000-0002-3305-4465")),
    person("Chuin Ying", "Ung", role = "aut",
           comment = c(ORCID = "0000-0001-8487-4589"))
    )
Description: A convenient R interface to the 'National Health Service (NHS) 
    Technology Reference Update Distribution (TRUD) API'. Retrieve available
    releases for items that you are subscribed to and download these with ease.
    For more information on the API, see <https://isd.digital.nhs.uk/trud/users/guest/filters/0/api>.
License: MIT + file LICENSE
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
Imports: 
    cli,
    dplyr,
    httr2,
    magrittr,
    purrr,
    rlang,
    rvest,
    stringr,
    tibble,
    tidyselect
URL: https://rmgpanw.github.io/trud/,
    https://github.com/rmgpanw/trud
BugReports: https://github.com/rmgpanw/trud/issues
Suggests: 
    testthat (>= 3.0.0),
    withr
Config/testthat/edition: 3

• Please indicate which category or categories from our package fit policies or statistical package categories this package falls under. (Please check one or more appropriate boxes below):

  Data Lifecycle Packages

  • data retrieval
  • data extraction
  • data munging
  • data deposition
  • data validation and testing
  • workflow automation
  • version control
  • citation management and bibliometrics
  • scientific software wrappers
  • field and lab reproducibility tools
  • database software bindings
  • geospatial data
  • text analysis

  Statistical Packages

  • Bayesian and Monte Carlo Routines
  • Dimensionality Reduction, Clustering, and Unsupervised Learning
  • Machine Learning
  • Regression and Supervised Learning
  • Exploratory Data Analysis (EDA) and Summary Statistics
  • Spatial Analyses
  • Time Series Analyses
  • Probability Distributions

• Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:

trud wraps the NHS TRUD API, which account holders to automate the download of technology reference files from NHS England.

• If submitting a statistical package, have you already incorporated documentation of standards into your code via the srr package?

Not applicable

• Who is the target audience and what are scientific applications of this package?

The technology reference files from NHS England are widely used by researchers (both within and outside the UK) working with electronic health records data. The available items include various clinical coding terminologies such as ICD, Read, prescription codes and the SNOMED CT ontology (which is updated with new available releases every few months). While trud is a relatively small package, it provides a helpful aid to researchers working with these release items, greatly simplifying the process of automated updates to support downstream analyses.

• Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?

There are no other similar R packages that I am aware of.

• (If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research?

Not applicable

• Any other questions or issues we should be aware of?:

trud 0.1.0 is available on CRAN (accepted mid-2024)

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