Makeover Monday – week 16, 2017: Vitamin D prescriptions in England – do we need to get out more?

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While some of our participants may have hoped for a chocolate themed Easter dataset this weekend, I decided that a long weekend is the perfect time to give everyone another big data challenge. For quite a while now I’ve been thinking about when to ‘drop’ this dataset  and for week 16 the stars aligned.

I do have to say a big thanks to my colleague Johannes, who tirelessly helps me bring these and other ideas to life and supply the Tableau community with large datasets.

So for week 16 we’re looking at prescribing data for England from 2010-2017. What I like about this dataset apart from it’s massive size (over 700 million records) is that there is so much in there. Our community can explore the data from countless different angles focus in on a small topic or keep it really broad. It is also a topical issue with research published regularly based on the data and I’m already looking forward to the insights our community will come up with. It has the potential to have a big impact…

The original article investigated prescribing statistics and features a couple of simple line charts looking at summar level data:

original.png

What I like about it:

  • it is simple and has clear chart titles that I can understand easily
  • the time scale is the same for both charts
  • the overall title tells me where the data is from and what timeframe is covered
  • the colour choice is simple and appropriate, nothing over-engineered, but the lines stand out enough

What I don’t like about it:

  • without further context, the overall title isn’t actually that easy to understand. Trends in pescribing – is it clear that this relates to medication? Might be a language thing and I’m not a native English speaker, but to me something like ‘Trends in medical prescriptions…’ would make a bit more sense
  • the use of net ingredients costs, while interesting, isn’t very helpful for me. These costs don’t factor in the ‘dispensing’ costs and I would prefer to see ‘Actual costs’ at this level
  • I would prefer the gridlines to be lighter and dashed, so they are further in the background
  • I would also prefer the axis lines and markers to be a lighter shade. They are purely to aid my understanding, but they don’t need to stand out as much as the data
  • while I said above that the colour of the line is fine, I would personally choose a different colour. Green in a line chart to me looks very much like a finance dashboard
  • and while I do like the simplicity, I think it undermines the magnitude of the numbers. The axes don’t necessarily have to start at zero and I find that by having them start at zero in the original chart, the variations in the data over time are very difficult to identify, especially for the costs. But a variation of half a billion £ is HUGE. That is a lot of money, so I would prefer to see the data visualised in a way that shows those more clearly

 

What I did:

The benefit of putting together the data for this challenge is that I had to spend a few hours looking at the dataset as we brought it into our database. So I had to familiarise myself with BNF codes and some of the other dimensions and measures.

I decided that I wanted to find a story for food-related medication.

  • as a first step I created some calculated fields that would give me BNF section and paragraph details that I researched online. I also created some sets to narrow down the data easily.
  • I looked at prescriptions and their costs for the BNF chapter 9 which focuses on Blood and Nutrition:Nutrition and Bloog.png
  • Oral nutrition looked like a very interesting topic to focus on because of the costs. But I had some ideas for Vitamins, so I decided to go down that route…

Vitamin D.png

  • Then I went to my whiteboard and started to sketch out some ideas for the dashboard, adding text, Big Ass Numbers, charts and explanations.
  • Then I had to take a break because I had signed up for a local 10km running race. It was 2 degrees and snowing, but we went there anyway, ran the race and returned. Perfect weather to get back to my desk for the viz.
  • With my dashboard planned out on the whiteboard I started pulling together the necessary information
    • I used the data (of course!), but I also
    • did some research into sunshine hours in England between 2011-2016 and
    • reminded myself of some of the finer detail around Vitamin D
  • Again I focused on story telling and not just showing some data (There are actually so many stories to be found in this dataset that I don’t think I’ll stop at this one…). That’s why I included a lot of text in my viz
  • I knew that with the single dataset I would have to make some (wordy) assumptions, so I included those as well and spent a fair amount of time on formatting, adding lines, trying to get everything aligned just right and added colour to highlight certain aspects of the dashboard
  • And then I was done and sent my viz to Andy for feedback.

(Click to view on Tableau Public)

Vitamin D Dashboard

Overall while I feel I’m making some progress with expanding my ‘viz type portfolio’, these stories aren’t yet at the level where I want them to be. I still find it difficult to keep my call-outs concise but informative and to create a design that is really effective. But hopefully that’ll come with time ;-).

 

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