• We need you: share your COVID-19 work on NHSE/I’s regular mini-huddle series

    COVID-19 has placed the value of data and analytics at the fore. This has meant an unprecedented focus on the work of health and care analysts, but also huge demand for local analytical services. The need to share and share alike is paramount.  To support this, NHSE/I are holding a series of huddles and mini-huddles to allow analysts to share their COVID-19 work with a wider community.

    Weekly huddles showcase work on a specific topic, and the back catalogue of recordings can be found here. The mini-huddles are a spin off series where speakers get into the detail behind a single topic, like geo-mapping or a dashboard. The team curating these huddles are keen to have a mini-huddle on COVID-19 analysis in R. If you are interested in sharing your analysis relating to COVID-19 using R, please get in touch with Sophie Hodges via email sophie.hodges5@nhs.net

     If you haven’t already, please sign up to the COVID-19 data and analytics workspace here. The community is currently 6500-strong with members across the NHS, public health, local authorities, charities and commercial organisations. Mini-huddles usually draw an audience between 30 and 80 attendees so it’s a great opportunity to share your work, discuss findings and network with others working on similar issues.

    Please get in touch if this sounds of interest. And a huge thank you from NHSE/I. The work being done by the analytical community is a key plank of the COVID-19 effort.

  • How NHS-R Community do The Apprentice…

    By Zoe Turner

    One of the tasks on the Apprentice a number of years ago was for the contestants to put on a corporate event, at no small cost to the people attending I might add. It’s a tale often told because one of the contestants was gluten free and no one had accounted for dietary needs amongst the contestants so the poor ‘gluten free lady’, as she was known, was served a fruit salad.

    The reason I’m apparently going off tangent so early in a blog, is that it struck me that the Apprentice is all about throwing people in at the deep end and seeing how they cope. It’s entertainment but clashes with the premise that these are potential apprentices to a ‘British business magnate’ (as Wikipedia calls him). Contrast this with NHS-R and how I came to be attending the Train the Trainer event at the end of 2019 and then helped to run the first of 3 local courses this January, having only just started learning R around 2 years ago.

    Analysts have many expectations made of them. They have to be technical, able to interpret data and communicate themselves clearly to non-analysts. Very rarely though will an analyst be expected to train others. Some may produce or present some training to support or mentor fellow analysts, and even then my experience has always been on the receiving end. Coupled with the fact that I’ve never really had a burning desire to teach, it was a surprise to find myself on a course on how to deliver the NHS-R ‘Introduction to R’ workshop.

    The reason I did it is that my involvement with NHS-R has led to this natural consequence of training others. I started with attending the course myself, then presented at the conference and facilitated an Introduction Course run by NHS-R but hosted by my Trust. I then didn’t hesitate in agreeing to taking on the training.

    NHS-R Community held their first two-day Train the Trainer event in Birmingham organised through AphA (Association of Professional Healthcare Analysts). I was supported to go on this by my manager, Chris Beeley, who is a huge advocate of R and Shiny. Whilst he himself has run several workshops over the years I, notably, have run zero!

    At the TtT (got to get an acronym in there) I had the opportunity to meet lots of motivated people from around the British Isles who were as keen as I was, not only to learn how to teach R but also to talk about data – that happened quite a bit in the breaks. We had an opportunity to present to each other, and that was useful as I learn especially from watching others. Everyone has their own style and it gets perfected over time but I was hugely impressed by how engaging people were and how quickly they could read about a subject that was new to them (we looked at the RStudio presentation slides https://education.rstudio.com/teach/materials/) and then go on to express clearly what they’d just learned.

    I could go on about what I learned at the course, but the proof of its value is in what I did with it. And so on 17th January, Chris and I held a workshop for 15 people from various organisations; some had travelled as far as London and Portsmouth, such is the commitment to learn R. Chris led the workshop and I did the live coding/support role which took the edge off that ‘first time’ feeling.

    This idea of having at least two people in a workshop is a good one, even when the trainer is very experienced. Chris, for example, is very used to running workshops alone, but inevitably people get stuck or things don’t work as they should and so I did the helping while Chris moved between training and coding. It felt, to me at least, like the burden was shared. It helped to ensure that no-one in the group was allowed to fall behind so far that they just gave up.

    Chris and I had gone through the slides beforehand as he’d not gone on the TtT course, and having not written them himself, I wanted to make sure he’d know what was covered. What reassured me was that, as he presented the course, there wasn’t a part of it that I didn’t understand myself and couldn’t cover if I had to take over at that moment. And so the day wasn’t as nerve-racking as I anticipated, and I had fun – which must have been noticeable to the group, as I had an email commenting on how we are clearly a happy team!

    Whilst I haven’t actually run a workshop, I think the process I’ve gone through to get to this point has certainly built up my confidence to do it. I’ve taken every opportunity NHS-R community has offered, from doing the introduction to presenting at the conference, and so this next thing – to run the training myself – hasn’t been so scary after all. I feel like a happy and well-supported apprentice of NHS-R, and the great thing about NHS-R in this is that everyone can be an apprentice too – you just have to get involved.

    Being open-source, all the slides for the trainer course and the introduction course are available on GitHub:

    Train the Trainer course materials can be found at:


    Course materials for the underlying Intro to R course are found at:


    Zoë Turner, Senior Information Analyst, Nottinghamshire Healthcare NHS Foundation Trust.

    @Letxuga007 and curator of @DataScienceNotts (formerly known as @AppliedInfoNotts)

  • Forecasting R

    By Bahman Rostrami-Tabar

    Democratising forecasting project

    The initiative sponsored by the International Institute of Forecasters provides cutting-edge training in the use of forecasting with R software in developing countries. There is no doubt that many people in developing countries cannot afford high fees to attend forecasting workshops. The project aims to make such a training accessible to those people and provide up-to-date training on the principles of forecasting and create a network of forecasters to conduct research on forecasting with social impact for less developed countries. The training has been delivered in Tunisia, Iraq, Senegal, Uganda, Nigeria, Turkey, Indonesia so far.

    We expand the “Democratising Forecasting” initiative to deliver four forecasting workshops per year for the National Health Service (NHS), UK, in collaboration with NHS-R community. We give our time for free despite the debate that such organisations may afford to pay such trainings.

    Why forecasting for NHS

    Ensuring life-saving services are delivered to those who need them require far more than money, infrastructure and scientific progress. Accurate modelling and forecasting systems can assist critical decisions that drive policy making, funding, research, and development in the NHS. Decision makers are making decisions every day with or without forecasts. However, they are more robust and well-informed in the light of what could happen in the future, and that is where forecasting becomes crucial. However, implementing forecasting principles to support decision-making process requires significant technical expertise. To that end, we aim to organize a two-day workshop on forecasting to teach participants how to apply principles of accurate forecasting using real data in healthcare.

    We are offering four workshops in 2020 as per below:

    • Monday 24th & Tuesday 25th February 2020 – Nottinghamshire – Workshop fully booked
    • Monday 22nd June 2020 – Huddersfield – Online https://www.eventbrite.co.ukworkshop is fully booked
    • Thursday 13th & Friday 14th August 2020 – Gloucestershire
    • Wednesday 13th & Thursday 14th October 2020 – West Midlands
    • Thursday 12th & Friday 13th November 2020 – Cardiff

    Workshop instructor

    Dr. Bahman Rostami-Tabar is the main instructor for the workshops. Colleagues from other Universities in the UK might join him occasionally. Bahman is a Senior Lecturer (Associate Professor) in management science at Cardiff Business School, Cardiff University, UK. He is interested in the use and the Implication of forecasting in social good areas such as health and humanitarian. He has been involved in various forecasting related projects with NHS Wales, Welsh Ambulance Service Trust and the International Committee of the Red Cross. He is currently working on projects that focus on developing innovative forecasting methodologies and their links to decision making in health and humanitarian operations.

    Who should attend

    This workshop is for you if you are:-

    • A decision maker who wants to use forecasting tools and techniques using R to empower decision making;
    • A data analyst who wants to gain in depth understanding of forecasting process.
    • A Forecaster who wants to learn how to use R software for forecasting purpose.

    What participants will learn in the workshop

    Assuming basic knowledge of statistics, participants will be able to do the following tasks when using forecasting to support decision making process in real World:

    • Determine what to forecast according to a forecasting process framework;
    • Prepare and manipulate data using functions in basic R, tidyverse and lubridate packages in R;
    • Identify systematic patterns using time series toolbox in ggplot2 and forecasting related packages in R such as forecast package;
    • Produce point forecasts and prediction intervals using R functions in forecasting related packages such as forecast and fable and user defined functions;
    • Determine the accuracy of forecasting models using statistical accuracy performance measures for point and prediction intervals;
    • Visualize, export and report result for interpretation and insights using RMarkdown.


    • Basic knowledge in statistics is assumed, e.g. “I know what normal distribution is”;
    • Basic knowledge of R is assumed, e.g. “I know what data type and data structure is”, “I know how to use a function”;
    • No knowledge of forecasting is assumed;


    Start: 09:30 a.m.

    End: 04:30 p.m.

    Refreshment breaks:

    • Morning: 11:00 – 11:20
    • Afternoon: 03:00 – 03:20 p.m.

    Lunch: 12:30 p.m. – 01:30 p.m.


    Title: Essentials to do forecasting using R

    Date: Two weeks before the workshop (TBC)

    Day 1

    1.1.Forecasting and decision making: What is forecasting? How forecasting task is different from other modelling tasks? What is the link between forecasting and decision making, how to identify what to forecast?

    1.2. Data preparation, and manipulation: how to prepare data for the forecasting task, how to clean data? How to manipulate data to extract time series?

    1.3. Time series patterns and decomposition: what could be used in data for forecasting task? how to detect systematic pattern in the data? how to separate non-systematic pattern?

    1.4. Forecaster’s toolbox: How to use time series graphics to identify patterns?  what is a forecasting benchmark? What are the simple forecasting methods that could be used as benchmark? How to generate point forecasts and prediction interval using simple forecasting methods?

    1.5. Forecast accuracy evaluation: How do we know if the forecasting method captures systematic patterns available in data? How to judge whether a forecast is accurate or not? How to evaluate the accuracy of point forecasts and prediction interval? Why do we need to distinguish between fitting and forecast?

    1.6. Exponential smoothing models: What is the exponential smoothing family? what are available models in this family? What is captured by this family? how to generate point forecast and prediction intervals using exponential smoothing models?

    Day 2

    2.1. ARIMA models: This is another important family of forecasting models. What is the ARIMA framework? what are available models in this family? What is captured by this family? how to generate point forecast and prediction intervals using ARIMA models? 

    2.2. Regression: We also look at causal techniques that consider external variables. What is the difference between regression and exponential smoothing and ARIMA? How to build a simple regression model?

    2.3. Special events: In addition to using systematic patterns in time series, we discuss how to include deterministic future special events, such as holidays, festive days, etc in models.

    2.4. Forecasting by aggregation:  How to forecast in a situation where we have a high frequency time series, e.g. daily but we need a low frequency forecast, e.g. monthly?  How do we generate forecast for items with a hierarchical or grouped time series structure?

    2.5. Forecasting by combination:  how to use an ensemble of forecasting approaches? In which conditions ensemble forecasts are better than individual methods?

    2.6. Forecasting for many time series: what is the best approach to forecast many time series? How to classify items for forecasting? How to forecast them? How to report the accuracy?  


    Workshop Booklet:

    • Materials will be provided for the workshop in RMarkdown.


    Bahman Rostami-Tabar

    Associate Professor in Management Science, Cardiff University, UK


  • NHS-R Community Conference II

    My journey to work takes me about an hour and a half, and I catch a couple of buses with Wi-Fi which means I can browse Twitter and invariably end up with hundreds of tabs open as I flit between articles and blogs. Most mornings I find it hard to concentrate on reading through entire articles, especially the really long ones, so I leave the tab open on my computer, often for days, before reading them. Given my experience of reading blogs, why would anyone want to read through mine about the NHS-R Community conference?

    If I’d gone to the conference I’d probably skim that paragraph thinking ‘yes, I went, I know how good it was’.

    If I’d not gone to the conference I’d probably skim that paragraph because I might prefer not to know just how great a conference was when I’d missed it!

    Even though the conference was moved to a bigger location to accommodate more people and around 250 people attended, I have still spoken to people who didn’t get a ticket or missed submitting an abstract to speak. People who never made the conference are talking about an event that is only in its 2nd year. What is going on? What is it that has made the event so successful?

    Organising an event of any size takes a lot of work and that is often overlooked. There were the core people who did the real work – the arrangements – and quite frankly, they made it look easy, which itself is an indication of how hard they worked. But there were others who were part of a committee that chipped in with bits they could help with: setting up a specific email; reading through abstracts; suggesting things the organisers might consider, like how to ensure diversity of questioners (https://oxfamblogs.org/fp2p/how-to-stop-men-asking-all-the-questions-in-seminars-its-really-easy/).

    That organising committee was made up from a group who have shown a particular interest in R, and as such I found myself part of that group. Now although I have submitted a few blogs to NHS-R, I only really started using R a couple of years ago. Deep down I’m still a SQL analyst and my contributions to the conference were pretty minimal, but I feel encouraged to make those small contributions (even that last one about who gets to ask the first question in seminars) and each small involvement builds up to a bigger thing. This really is feeling like an equal and inclusive group and that’s where I think this success is coming from.

    It may have been by design or it may be a happy accident but there is a crucial clue in the name of this group that gives away its success – Community. This conference wasn’t managed top-down. There are some key people, of course, but they are as much of this Community as the people who contribute to the blogs, those that stood up on stage and showed their work, have those that will be learning to run the R Introduction training. This is our NHS-R Community.

    If you missed this year’s conference and want to go to the next one, get involved. The more people involved, the less work there is for everyone individually. Plus, given that tickets this year ran out in just 2 hours, you’ll be more likely to secure yourself a ticket.

    Speaking of which, provisional dates for the next conference are the 2nd and 3rd November 2020 (Birmingham). Now aren’t you glad you read this blog!

    Zoë Turner, Senior Information Analyst @AppliedInfoNott @Letxuga007

  • Welcome to Leeds

    R Users Leeds

    Why create a group ?

    Trying to learn R is tricky, there are so many ways to do things that I often ended up Googling everything and still not feeling like I was doing anything the right way.

    Then someone sent me a link to the NHS-R Community website where I found lots of interesting and helpful information. Plus there were R groups, but not one in Leeds. I was surprised by this given the density of health analysts and other R users in and around Leeds. There should definitely be a group in Leeds.

    How to create a group ?

    So I ran my idea past a colleague to check if I was crazy. They agreed to help anyway and offered to email some contacts at the University of Leeds. I approached the Sheffield-R group and the NHS-R community (who also thought it was a good idea). We also connected with NHS Digital and NHS England and Improvement.

    Through this process we were very lucky to find some clever individuals who had already thought about starting up a group in Leeds. This meant the group already had a website (R Users Leeds), Twitter, email and logo. This gave us a great starting point with a planning team covering Leeds Teaching hospitals NHS Trust, NHS Digital, University of Leeds, Leeds Beckett University and Sky Betting and Gaming. We are very lucky in Leeds to have access to both local and national NHS organisations, academic institutions and digital and technology companies.

    What do we want from a group ?

    From the beginning it was important to think about the aims and ethos of the group which for Leeds are:

    • Create an open and inclusive community
    • Meetings should be free
    • Organise meetings within and outside office hours to ensure everyone has the opportunity to participate.
    • Include the NHS, academia and other industries using R

    Where will the group meet ?

    Another consideration was how to get venues especially at low or no cost. After making contacts I was assured that I could get things for free, I wasn’t too sure but thought that I should give it a go. This is going to be an ongoing task but I have been surprised by how many organisations want to help. Following a first planning meeting we managed to organise speakers and get a date and venue for the first meeting:

    5th December 2019, NHS Digital, Leeds

    • Reproducible wRiting with RMarkdown. Ed Berry, Senior Data Scientist, Sky Betting & Gaming
    • Efficient WoRkflows getting more done with R. Robin Lovelace, University Academic Fellow, University of Leeds
    • Putting the R into Reproducible Research. Anna Krystalli, Research Software Engineer, University of Sheffield

    R we nearly there yet ?

    Our first event is almost upon us so I suppose we have nearly reached the first destination. With tickets booking up quickly it is clear to see that there is a need for a group in Leeds to bring the analytical community together.Thank you to everyone who has supported us so far, hopefully this is just the beginning of the journey.

    If you would like to speak at R Users Leeds please get in touch.

    You can keep in touch with us on Twitter, GitHub, Gitter and email.

    R Users Leeds

    This blog was written by Louise Hick, Real World Data Analyst, the Leeds Teaching Hospitals NHS Trust
  • NHS meets R

    Welcome to the NHS-R Community – born March 2018. 

    Hello and welcome to our nascent NHS-R Community; a community dedicated to promoting the learning, application and utilisation of R in the National Health Service (NHS) in the United Kingdom. Like any community, NHS-R relies on the vibrancy of its participants to be relevant and productive – and fun.

    So why get involved?

    The NHS is one of the best healthcare systems in the world[1]. It was launched in 1948 with the guiding principle of being free at the point of delivery – a kind of crowd funded open-source freeware equivalent of healthcare. More than half (52%) of the public say the NHS is what makes them most proud to be British, placing it above the armed forces (47%), the Royal Family (33%), Team GB (26%) and the BBC (22%)1.

    The NHS in England deals with about 1 million people every 36 hours[2] and is continually generating vast amounts of data about the health and care of people[3]. This data is one of the most precious, yet under tapped, resources in the NHS.  “Data is the new oil of the digital economy”[4] and drilling and mining NHS data could improve the NHS[5]. But mining these mountains of data is a colossal task.

    This is where R comes in. R was conceived in 1992[6] as a free open-source statistical programming environment, which is now widely used in industry[7] (Google, Microsoft, Airbnb, New York Times, Lloyds of London, etc) and academia, and is now ranked amongst the most popular (sixth as of 2017) programming languages[8].  But its use in the NHS is almost non-existent. Whilst there are several reasons for this, the absence of R at scale in the NHS, means that the NHS is unable to take advantage of the huge benefits of R, including cutting-edge visualisation and statistical tools, and a worldwide R community, which freely shares learning and resources.

    So, our aim is to promote the use of R in the NHS, and help to make the NHS better.

    To kick-start the NHS-R Community, we have developed a website [www.nhsrcommunity.com] and are offering four free workshops (3 days each, repeated in Yorkshire and Wales). Workshop (1) will be an introduction to R for healthcare analysts. Subsequent workshops will focus on the following problems:- (2) understanding and reporting hospital mortality statistics, (3) predicting urgent demand for hospital care and (4) evaluation of interventions using matched retrospective controls. Each workshop will be led by experts in both the problem domain and R, and captured electronically for wider dissemination. Registration for the workshops is now open*.

    However, anyone can contribute to the NHS-R Community, so why not share your experience (novice, beginner, or otherwise) of using R in the healthcare setting? Write a blog, share R tips, do an on-line R tutorial, suggest topics for ongoing development and support, and share ideas on how to embed R into the NHS.


    From the NHS-R Team [Posted: 19 March 2018]

    The NHS-R Community project is funded by The Health Foundation.

    *NB: To be eligible for the workshops you must have a working NHS email address.  Places are limited.

    [1] https://www.newscientist.com/article/2140698-us-ranked-worst-healthcare-system-while-the-nhs-is-the-best/

    [2] https://www.nhs.uk/NHSEngland/thenhs/about/Pages/overview.aspx

    [3] http://content.digital.nhs.uk/article/4963/What-we-collect

    [4] https://www.wired.com/insights/2014/07/data-new-oil-digital-economy/

    [5] https://www.herc.ac.uk/get-involved/data-saves-lives/

    [6] http://blog.revolutionanalytics.com/2017/10/updated-history-of-r.html

    [7] http://makemeanalyst.com/companies-using-r/

    [8] https://spectrum.ieee.org/computing/software/the-2017-top-programming-languages