This R package was developed as part of the Sheffield Tobacco and Alcohol Policy Modelling https://stapm.gitlab.io/ by the School of Health and Related Research at the University of Sheffield.
The aim of the research programme is to identify and evaluate approaches to reducing the harm from tobacco and alcohol, with the aim of improving commissioning in a public health policy context, i.e. providing knowledge to support benefits achieved by policymakers.
The two objectives of the research programme are:
- To evaluate the health and economic effects of past trends, policy changes or interventions that have affected alcohol consumption and/or tobacco smoking
- To appraise the health and economic outcomes of potential future trends, changes to alcohol and/or tobacco policy or new interventions
The STAPM modelling is not linked to the tobacco or alcohol industry and is conducted without industry funding or influence.
The code has been made open source for the following two reasons:
- Transparency. Open science, allowing review and feedback to the project team on the code and methods used.
- Methodology sharing. For people to understand the code and methods used so they might use aspects of it in their own work, e.g., because they are doing something partially related that isn’t exactly the same job and might like to ‘dip into’ elements of this code for inspiration.
The code is actively being used in project work. It is being reviewed and developed all the time; more tests and checks are being added.
The repository is not intended to be maintained by an open source community wider than the development team.
The list of diseases considered in the modelling is available here https://osf.io/v945r
Data checks are visualisations that show the results of data processing using the hesr package.
The code on Github (https://github.com/STAPM/hesr) is a mirror of the code in a private Gitlab repository where the actual development takes place (https://gitlab.com/stapm/r-packages/hesr). The code in the Github repository is linked to a repository on the Open Science Framework, which provides the doi for the package citation (https://osf.io/ad4vy/).
Gillespie D, Webster L, Angus C, Brennan A ([YEAR]). hesr: An R Package for Processing Hospital Episode Statistics Data. R package version [x.x.x]. University of Sheffield. https://stapm.gitlab.io/r-packages/hesr/. doi: https://doi.org/10.17605/OSF.IO/AD4VY
The motivation for hesr was to standardised the way that the Admitted
Patient Care (APC) portion of the English Hospital Episode Statistics
(HES) were processed to produce inputs to our decision-analytic models
(https://stapm.gitlab.io/hes_data_england.html). Functions have
subsequently been added to process equivalent Scottish Morbidity Record
(SMR01) data
(https://www.ndc.scot.nhs.uk/National-Datasets/data.asp?SubID=5) for
the Scottish version of the STAPM modelling
(https://stapm.gitlab.io/hes_data_scotland.html).
hesr was created as part of a programme of work on the health
economics of tobacco and alcohol at the School of Health and Related
Research (ScHARR), The University of Sheffield. This programme is based
around the construction of the Sheffield Tobacco and Alcohol Policy
Model (STAPM), which aims to use comparable methodologies to evaluate
the impacts of tobacco and alcohol policies, and investigate the
consequences of clustering and interactions between tobacco and alcohol
consumption behaviours.
The data contains details of all admissions to hospital. Each HES record contains a wide range of information about a patient including clinical information about diagnoses and operations, patient information such as age, sex, and socio-economic status, and administrative information such as dates of arrival.
In ScHARR, all data is stored and processed according to the ScHARR
Information Governance
Policy. The
HES data is stored on the University of Sheffield managed heta_study
virtual machine, which is accessible only to team members who are using
data. The working folder on the university networked X-drive is
PR_HES_data_TA. No individual-level data is included within this
package.
We have given a brief description of our use of the HES data in the privacy notice.
The suite of functions within hesr reads the data for each year,
renames, organises and processes the variables that we use for our
analyses.
The inputs are the raw data files for each year and the list of diseases attributable to tobacco and/or alcohol (defined by ICD-10 codes).
The processes applied by the functions in hesr give options to:
- Read each year of data.
- Define spells.
- Identify tobacco and alcohol related episodes and spells.
- Calculate rates of hospital admission for tobacco and/or alcohol related causes.
- Stratify rates by age, sex, socio-economic conditions (defined by Index of Multiple Deprivation) and geographical region.
- Calculate the unit costs of hospital admissions.
The output of these processes is a set of rates that describe admission to hospital, and a set of unit costs for use in health economic modelling of the effects of changes to tobacco and/or alcohol consumption.
hesr is publicly available via Github.
By default the user should install the latest tagged version of the package. Otherwise, if you want to reproduce project work and know the version of the package used, install that version.
If on a University of Sheffield managed computer, install the R, RStudio
and Rtools bundle from the Software Centre. Install Rtools - using the
installr
package can make this easier. Then install the latest or a specified
version of hesr from Github with:
#install.packages("devtools")
devtools::install_git(
"https://github.com/stapm/hesr.git",
ref = "x.x.x",
build_vignettes = FALSE)
# ref = "x.x.x" is the version to install - change to the version you want e.g. "1.2.3"Or clone the package repo locally and use the ‘install and restart’ button in the Build tab of RStudio. This option is more convenient when testing development versions.
Then load the package, and some other packages that are useful. Note
that the code within hesr uses the data.table::data.table() syntax.
# Load the package
library(hesr)
# Other useful packages
library(dplyr) # for data manipulation and summary
library(magrittr) # for pipes
library(ggplot2) # for plotting