Promoting the use of R in the NHS

NHS-R Conference 2021 – Workshop Week

NHS-R Conference 2021 – Workshop Week

‘1st to 5th November 2021’

Learn how to take advantage of the huge benefits of R.

With workshops for R beginners to more advanced subjects for those wanting to build on their R knowledge this is a great opportunity to learn some new skills.

R is a powerful, free open source data science and statistics environment.

We are delighted to be offering the following workshops as part of the NHS-R Conference 2021.

The demand for places on the Workshops has been very high. If you would like to be added to the waiting list for any of the below, please contact nhs.rcommunity@nhs.net

Please note places are limited. Registration is open only to NHS and UK Public Sector employees .

A big thankyou to all the workshop Facilitators for giving their time and sharing their expertise in R!

Download a pdf of the Workshop Programme.

Date: Monday 1st November 2021
Time: 9.30 am to 4.30 pm

One day Workshop

Facilitator: Zoë Turner, Senior Information Analyst, Nottinghamshire Healthcare NHS Foundation Trust

Summary: An Introduction to R workshop covering R/RStudio, manipulation of data (dplyr), creating charts (ggplot2) and reports (R Markdown). This is a great opportunity for anyone who is interested in data analysis using Excel, SQL, Access or uses statistical programmes like SPSS to get started with R and R Studio. Pre-requisites: Assumes no prior experience with R. Pre-installation of key software is essential. Further details on how to complete this will be sent to you on registration.

Pre-requisites: Assumes no prior experience with R. However, pre-installation of key software is essential. Further details on how to complete this will be sent to you on registration.

Title: PHM ExploreR – An open source tool for Population Health Management
Date: Monday 1st November
Time: 10.00 am – 12.00 pm

Facilitator: Andras Varady with Dr Richard Wood and Dr Anna Powell, Bristol, North Somerset and South Gloucestershire CCG

Summary: The workshop will introduce delegates to the PHM ExploreR: a versatile R Shiny tool created for exploring Population Health and facilitating Population Health Management (PHM) in healthcare systems.

PHM is of increasingly high interest within the NHS, but many Business Intelligence departments lack the appropriate tools to keep pace with this rapidly growing field. For NHS analysts, the PHM ExploreR aims to reduce reliance on Excel solutions and management consultancies offering bespoke pieces of work, and enable users to independently and interactively explore the key areas of PHM, such as Population Segmentation and Risk Stratification.

Pre-requisites: Some introductory experience with R

Date: Monday 1st November
Time: 2.00 pm – 3.30 pm

Facilitator: Dr Sean Manzi Research Fellow in Applied Healthcare Modelling and Analysis, University of Exeter College of Medicine and Health

Summary: This session will begin by introducing probability distributions, the different types of distribution and why we use them in data science. We will then move on to an overview of the distribution fitting process and how to implement this in R using the ‘fitdistrplus’ and ‘actuar’ packages. As we proceed through the distribution fitting process, we will discuss some of the theory around the techniques used to fit a distribution to a data set. There will be the opportunity to practice generating data from and fitting data to different distributions. Finally, we will explore the use of a shiny based app to help streamline your day-to-day distribution fitting activities.

Pre-requisites: A basic understanding of how to use R

Date: Monday 1st November 2021
Time: 3.00 pm to 6.00 pm

Facilitator: Rich Iannone, Software Engineer at RStudio

The gt workshop will teach you virtually everything there is to know about making beautiful tables in gt. We’ll learn how to:

  • Prepare tabular data for gt with functions from dplyr and tidyr
  • Add component parts to a table, like a header and a stub
  • Format data to make it appear just as you need it
  • Rearrange columns, combine them, and remove them from view

By the time you’re done with this workshop, you’ll be making fantastic tables that’ll impress and inform in equal measure. 

Pre-requisites: Some introductory experience with R

Date: Tuesday 2nd November 2021
Time: 9.30 am to 4.30 pm

One day Workshop

Facilitator: Josephine Browning, Senior Business Intelligence Manager, Analytics, NHS Gloucestershire CCG

Summary: An Introduction to R workshop covering R/RStudio, manipulation of data (dplyr), creating charts (ggplot2) and reports (R Markdown). This is a great opportunity for anyone who is interested in data analysis using Excel, SQL, Access or uses statistical programmes like SPSS to get started with R and R Studio. Pre-requisites: Assumes no prior experience with R. Pre-installation of key software is essential. Further details on how to complete this will be sent to you on registration.

Pre-requisites: Assumes no prior experience with R. Please use R-Studio Cloud for this workshop, further details will be sent to you on registration.

Date: Tuesday 2nd November 2021
Time: 9.30 am to 12.00 pm

Facilitator: Mango Solutions

Details to follow

Pre-requisites: Some introductory experience with R

Date: Tuesday 2nd November 2021
Time: 9.30 am to 13.30 pm

Facilitator: Tom Jemmett ,Senior Healthcare Analyst, The Strategy Unit

Summary: Functional Programming is a form of programming which is ideally suited to data analysis, and understanding some of the key concepts can help you solve problems in a much cleaner and concise way.

In this workshop we will start off covering some of the theory of FP, such as pure functions, avoiding side effects, and functional composition. We will see how following some simple rules can make our code significantly easier to test, debug, and use in practice.

We will then look at the purrr package, and cover some of the functions that this package provides, such as map, reduce, compose, and partial.

Pre-requisites: A basic knowledge of R is essential (e.g. the topics covered in the NHS-R intro to R course). Knowing how to write functions is helpful, see chapter 19 of R4DS 1. We will touch on vectors, but for a more complete understanding see chapter 20 of R4DS 2.

Date: Tuesday 2nd November 2021
Time: 2.00 pm – 4.30 pm

Facilitator: John McIntyre, Data Scientist, Jumping Rivers

Summary: One reason to learn R is that it can be used to produce publication quality graphics. In this tutorial we’ll introduce you to the fantasticggplot2 package and help you create many different types of plots. This workshop will be very hands-on and no previous knowledge of ggplot2 is necessary.

Pre-requisites: Some introductory experience with R

Date: Tuesday 2nd November 2021
Time: 3.00 pm – 6.00 pm

Facilitator: Emil Hvitfeldt, Clinical data analyst, package developer, and educator.

Details to follow.

Pre-requisites: Some introductory experience with R

Date: Wednesday 3rd November 2021
Time: 9.30 am to 4.30 pm

One day Workshop

Facilitator: Hansel Palencia, Devon Partnership NHS Trust

Further details: To follow

Pre-requisites: Some introductory experience with R

Title: NHSdataDictionaRy – using the package to retrieve common NHS lookups and to perform custom web scraping of other sites

Date: Wednesday 3rd November 2021
Time: 9.30 am to 12.00 pm

Facilitator: Gary Hutson, Lead for Data and Analytics

Summary: This workshop will look at how to get the most out of the NHSDataDictionaRy package. The workshop will include:
• Getting familiar with the NHSDataDictionaRy package
• Understanding the nhs_data_elements() elements function and how to filter on this
• Gather text from any website and perform some text cleaning operations on the text, using a combination of functions contained in the package
• Using the TableR function to retrieve HTML tables from the data dictionary site and then extending this to other websites
• Tutorial on how to get the XPath from a website and use inbuilt functions in the package to work with this
• How to use the package for the quick retrieval of the most up to date lookups from the NHS Data Dictionary site
• Generally learning more about the package and web scraping

Pre-requisites: Some introductory experience with R and familiarity with loading packages

Date: Wednesday 3rd November 2021
Time: 2.00 pm to 4.30 pm

Facilitator: Annie Yu, Epidemiological Programmer, Hertfordshire County Council

Summary: The workshop will go through creating a range of interactive graphs using plotly and echarts4r packages and why we would want to include interactive graphs in reports and apps. It will go through the basic syntax of each package and how to create basic bar, scatter, and line graphs while customising the hover labels, legends, and themes. I will introduce further capabilities of each package, such as adding buttons, additional layers, and grouping/linkage between graphs. The session will have some basic exercises and end with a challenge to create a more complex plot and render it using Rmarkdown.

Pre-requisites: Some introductory experience with R

Date: Wednesday 3rd November 2021
Time: 3.00 pm to 5.00 pm

Facilitator: Jeremy Allen, Software Engineer at RStudio

Summary: R and RStudio tips and tricks for working in the RStudio IDE, data wrangling and reporting with the Tidyverse and data.table, Shiny apps, and publishing in RStudio Connect.

Pre-requisites: Some introductory experience with R

Date: Thursday 4th November 2021
Time: 9.30 am to 4.30 pm

One day Workshop

Facilitators: Jacob Anhøj and Zoë Turner

Further details: To follow

Pre-requisites: Some introductory experience with R

Date: Thursday 4th November 2021
Time: 9.30 am to 12.00 pm

Facilitator: Mango Solutions

Further details to follow.

Pre-requisites: Some introductory experience with R

Date: Thursday 4th November 2021
Time: 1.00 pm to 4.30 pm

Facilitator: Ben Alcock, Data Scientist, NHS Fylde Coast CCGs

In this workshop, we will go through introductory mapping in R, learning to import spatial datasets, manipulate and work with different spatial data types (e.g. points, polygons), link them in with “standard” data frames to enrich the geo-dataset, and display mapped data using Leaflet.

Pre-requisites: Knowledge of tidyverse functions in this workshop is necessary (mostly dplyr for mutate/summarise/join). Some knowledge of SQL/PostgreSQL would be useful as I plan on loading some data from Postgres, but this is not 100% necessary as I’ll show how to just get data from static files as well.

Date: Thursday 4th November 2021
Time: 3.00 pm to 6.00 pm

Facilitator: Will Landau, Eli Lilly and Company – USA

Data science can be slow. A single round of statistical computation can take several minutes, hours, or even days to complete.

The targets R package keeps results up to date and reproducible while minimizing the number of expensive tasks that actually run. targets arranges the steps of your pipeline, skips costly runtime for steps that are already up to date, runs the rest with optional implicit parallel computing, abstracts files as R objects, and shows tangible evidence that the output matches the underlying code and data. In other words, the package saves time while increasing your ability to trust the results.

This hands-on workshop teaches targets using a realistic case study

Pre-requisites: Some introductory experience with R

Date: Friday 5th November
Time: 9.30 am to 1.30 pm

One day Workshop

Facilitator: Leon Eyrich Jessen

Summary: The aim of this workshop is an introduction to Artificial neural networks in R with Keras and TensorFlow. ANNs form the basic unit of deep learning and are immensely powerful in predictive modeling, but not without pitfalls.

In this workshop, we will be working with conceptually understanding what an ANN is, how we train an ANN and how predictions are subsequently made. We will also touch upon parameters, hyper-parameters and how to handle data all in context of model over-fitting.

Please note, the workshop is very hands-on oriented, so expect to get your fingers dirty!

Pre-requisites: The workshop assumes basic R/Data Science skills

Date: Friday 5th November 2021
Time: 9.30 am to 12.30 pm

Facilitator: Dr Rebecca Killick Associate Professor in the Mathematics & Statistics department at Lancaster University

Summary: This workshop introduces participants to the analysis of changepoint models (also known as time series segmentation or structural changes). The course is aimed at those with an interest in discovering methods for models that include changepoints. It will be interactive and use packages available on CRAN.

Following the course participants will be able to:

  • recognise datasets that potentially contain changepoints
  • identify appropriate changepoint methods dependent on the type of change suspected
  • perform changepoint analyses using a variety of techniques in R
  • summarise and evaluate results of a changepoint analysis

Pre-requisites: Basic working knowledge of R and statistical modelling is assumed

 A ‘Further changepoint analysis techniques’ workshop building upon the introduction to changepoint course will taking place as part of the Advanced R’ Workshop week’ on 3rd December 2021.

Date: Friday 5th November 2021
Time: 2.00 pm to 4.30 pm

Facilitator: Chris Mainey, Patient Safety Lead – System Analysis and Delivery, NHS Improvement

Pre-requisites: Some introductory experience with R

Summary: This session will focus on how to fit regression models in R, the most common form of statistical modelling. We will examine the essential theory underpinning these models, then fit linear models with a single predictor, then multiple predictors and look at how to interpret them

Date: Friday 5th November 2021
Time: 3.00 pm to 5.00 pm

Facilitator: Thomas Mock, Software Engineer at RStudio

Further details: To follow

Pre-requisites: Some introductory experience with R

And don’t forget to join us for the NHS-R Virtual Conference 2021 8th -10th November to hear from R experts from the UK and around the world.

We will also be holding an ‘Advanced R’ Workshop week on 29th November to 3rd December.

Please contact nhs.rcommunity@nhs.net with any queries.