SSNAPInterface

Installation

# Install development version from GitHub
devtools::install_github("SSNAP/SSNAPInterface")

Note that at present this is a private repository; to log in from the command line you should set the GITHUB_PAT environment variable. Refer to Github PAT for more information on setting this up. You can alternatively download and build the package from the site.

What is SSNAPInterface?

SSNAPInterface is an R package to handle the onboarding of SSNAP data.

At present, SSNAP data comes in the form of Comma Separated Values files, which can be exported from the SSNAP website.

The SSNAP project aims to be eventually agnostic about where SSNAP data comes from - so that we can fetch data directly from the SSNAP database, or indeed from other sources such as HL7 FHIR.

The purpose of the design of SSNAPInterface is to try to keep any of the initial loading and tidying of data separate from subsequent analysis steps. It is not generally intended for external use as the common way to deal with data will be through the SSNAPStats package which outputs pre-processed cohorts and measures.

The main function, ssnapcsv, imports data from a CSV file for use. The file format must be specified - this allows us in future to add format conversions if needed. SSNAPStats, the sole intended recipient, usually calls this itself.

The CSV file format is documented within the resources section of the SSNAP website.

How is the source CSV data modified?

We do extensive remodelling of the data to optimise it for analysis:

• We remove any redundant fields.
• We convert "Y / N" fields into Booleans.
• We convert "Y / N / NK" fields into optional Booleans, where NA represents the "Not Known" / "Not Appropriate" option.
• We convert other fields with mutually exlusive options with only two or three possible answers to optional / non-optional booleans (such as S2StrokeType which could be either "I" or "PIH" to S2StrokeTypeIsInfarct which is either TRUE or FALSE).
• We have some fields such as the thrombolysis no but reasons, or thrombolysis complications field where we use a series of related TRUE / FALSE statements. We convert these into Bitfields where each item is allocated a binary bit number (decimal 1, 2, 4, 8 etc); and the answers are stored as a single integer. This keeps the package data smaller and allows us to use binary logic to work with the data which is significantly quicker and neater.
• We produce four new fields S1PatientClockStartDateTime, S1TeamClockStartDateTime, S7DeathDate and S7TeamClockStopDateTime. These four fields are essential for the cohort selection functions. These are priorities to be moved into the SSNAP dataset proper where they can be created upon record lock to allow us to fetch data using SQL queries from the SSNAP database without the need to fetch all records.

The functions output a tibble (ie. a data frame optimised for the Tidyverse R package suite).

Beware that this package is in early development and APIs and outputs may change.

Contributing to this package

Unit testing

Code should be checked in wherever possible with unit tests for proving that the given portion of code works. This packages uses the TestThat package to produce unit tests.

If you find a bug within this code, it is good practice to firstly write a unit test which proves the bug, add it to the unit tests, and then fix the bug before proving that all the other unit tests pass satisfactorily before checking it in.

Unit tests are run whenever you select Check. You can also run them independently of the full check using Cmd-Shift-T (Mac) or Ctrl-Shift-T (Windows).

Code style guide

This code is written using the Tidyverse style guide coding style. It is checked using lintr:

# Check your update meets the lintr style guide
lintr::lint_package

Check the output in the Markers tab of the Consule for any style errors and correct them. A unit test also runs lintr: so your code will fail the lintr unit test if a style error is found.

Documentation

Each key function (all external functions and major internal ones are documented using Roxygen2. In addition, a website for the package is created within the package using pkgdown. To update the web pages use:

# Update the package website documentation
pkgdown::build_site()