When we want to describe how an AMU affects its patients' prior length of stay in the ED, 'heaviness' explains it better than fullness. But 'stickiness' explains it even better.

Yesterday it was cows using tools, today its penguins using satellite imagery.

"All of these three measurement failings – the wrong doors, the wrong time zone, the wrong connotations – conspire to prevent the rigorous examination of cause-&-effect relationships in the health & care system that’s needed" @kurtstat.bsky.social for #NHS2048 www.enlighten.scot/nhs2048/thre...

Well, it's a little clearer now why billionaires are so invested in technology that produces better written emails.

Guys this is the ONE client you really need to double check

My AMU 'heaviness' metric came about after I tried showing AMU lengths of stay so far (ALoSSF) as horizontal timelines on top of each other. On the left: a snapshot that captured 60 patients with an ALoSSF of 24.6 hours. On the right: 58 patients with an ALoSSF of 37.8 hours. #rstats #ggplot2

I want to have a go at adapting Stuart Hall's encoding/decoding model so that it works for how healthcare data messages are communicated. I think the key to this is how I flesh out the meaning structures on each side of the diagram.

I'm hoping that - eventually - *everyone* involved in acute hospital patient flow will be talking about AMU 'heaviness'! (Meanwhile I can't work out if this chart is a volcano metaphor or a Pandora's Box metaphor...) #rstats #ggplot2

Acute Medical Unit (AMU) 'heaviness' scores are calculated by multiplying each day's AMU mean lengths of stay by the same day's AMU fullness snapshots. The scores are closely correlated with Emergency Department (ED) performance, so I thought a scatterplot would be the way to go. #rstats #ggplot2

Error in gg_point() : could not find function "gg_point". Please tell me I'm not the only person who's made this mistake! #rstats #ggplot2

Tried to sneak a photo of a cute doggo and accidentally had long exposure on and I believe I have created man’s greatest expression of art

I'm working on a diagram that shows how we might incorporate emotion into data visualizations. I'm trying to mash together some ideas from Gavin McMahon's new book (www.story-business.com) with Don Norman's three layers of design (www.interaction-design.org/literature/a...).

This is a fascinating - and excellent - post by @samfr.bsky.social on his recent experience of being an NHS hospital patient. My heart jumped when I saw bed occupancy mentioned in the article: I have “views” on bed occupancy, so I thought I’d say something about it. substack.com/inbox/post/1... 1/6

Man walking into the Post Office earlier: You look like a person who knows about things. Person behind the til: I do? Well I know about some things I suppose. Man (showing him his phone): Good. What do I press to answer this thing?

I still think of pivot_wider() as magic, basically.

Indicators of patient flow dysfunction mainly focus on either the hospital front door (e.g. breaches of the four-hour target) or the hospital back door (e.g. delayed transfers of care). But patient flow dysfunction manifests itself *everywhere* in a general hospital. 1/6

I've been using open access data to explore the relationship between Emergency Department 12-hour performance and ambulance turnaround times. Each blue dot is a week between mid-November last year and early September this year. It's a pretty close relationship for this hospital.

Just had an email from Microsoft telling me that my 365 subscription is increasing in price by 31%.

Please enjoy today, 25/9/2025, the last square date until 2116 (5^2/3^2/45^2).

There’s a great talk by Marc Farr (“I wish I was macho instead of just deep”) that you can view on the Midlands Analyst Network website. It's very thought-provoking. Here are some of my thoughts… 1/18

American fascist: your going to the camps, American Liberal, chuckling: ‘you’re’. "You don’t fight the politics of violence by quibbling with the details! You stamp it into a million pieces!" Fantastic piece by @jonnelledge.bsky.social substack.com/inbox/post/1...

Is there a difference between upper case emphasis and bold-and-underlined emphasis?

This graffiti on Restalrig Road made me remember that fantastic article by Nicholas Carr ("The Tyranny of Now") in which he wrote about Harold Innis's distinction between 'time-biased' media and 'space-biased' media! www.thenewatlantis.com/publications...

You don't have to be old to be right wing, but it helps. Great graph by @owenwntr.bsky.social in @samfr.bsky.social's latest newsletter.

I've just had a quick glance at this book - it looks ABSOLUTELY FANTASTIC!!!

“Why not paintings or sculpture or other persuasive visual images, or persuasion by the written word alone? … A map is different from other forms of communication because it is uniquely presumed to be a source of honest, objective information.” persuasivemaps.library.cornell.edu/about/

I've written a lot about disordered discourse and counterpublics, but given recent events I want to cover a key part of disordered discourse, which I call the four pillars of disordered doubt.

"I regret the thing that someone else did to me"

The top of Arthur's Seat (Edinburgh) seen from Crow Hill this morning.

1/ Scotland hospital (EDs) weekly A&E performance, week ending August 24 - Rise in %age Within 4 Hours, remaining at 2022/23/24 levels - public.tableau.com/views/Scotla...

You can access long - and interesting - emergency care data timelines from the @publichealthscot.bsky.social website. www.publichealthscotland.scot/healthcare-s...

German diplomat at Versailles: 'I wonder what future historians will say about all this.' Clemenceau: 'Well they won't say Belgium invaded Germany.'

It shows such a basic lack of political understanding that Labour didn't go straight on the attack over this. Just because most people are worried about immigration being too high it doesn't mean they're psychopaths.

This is how the NHS sees its patient flow problem.

Well it’s bizarre that in 2025 the political dividing line is pro rounding people up and putting them in camps and anti rounding people up and putting them in camps. Even more bizarre that the nuanced position of the Government appears to be rounding people up and putting them in better run camps

@chrisbrogan.bsky.social This is what happens when you try to be brutally honest with yourself in relation to the Impact Attributes...

I bought this book by @chrisbrogan.bsky.social and Julien Smith ages ago. Well, I'm finally getting round to reading it. Up to page 70 already. It's very, very good.

Looking over north Edinburgh towards the Firth of Forth from the top of Crow Hill (the hill next to Arthur's Seat).

I was inspired by @nrennie.bsky.social's datafile of the Scottish Munros, and managed to create a rough 'progress-so-far' scatterplot. But - alas! - I am new to #rstats maps and have absolutely no idea how to superimpose an outline of Scotland on this...

I took Scotland's four-hour compliance data going back to 2008 and drew a 17-year trendline. I'm trying to come up with names for The Five Stages of Four-hour Compliance. So far I've got: 1. Achievement 2. Hankering 3. Brief - very brief - remission 4. Collapse 5. Late rally #rstats #ggplot2

The top of Mount Keen, the easternmost Munro.

we need this on uk tv asap

I liked this #dataviz by BBC Sport. There's a lot of information to pore over here. The only thing I'd change would be to *not* shade the period after 2017-18 so that the shading is congruent with the message in the title.

I tried juxtaposition - using {patchwork} - to emphasise the difference between these two years. In 2019-20 (when the system was less dysfunctional) there was a clear relationship between AMU bed occupancy and four-hour compliance. By 2023-24 that relationship had broken down. #rstats #ggplot2

I’m watching a live stream

@samfriedman.bsky.social This chart is a bit 'lazy'. There isn't a *direct* cause-and-effect relationship between beds occupied by patients in delay and long waits in A&E; there are a few steps in the intervening chain reaction. But it's interesting to see the two indicators on the same graph.

The latest delayed discharge figures for NHS Scotland were published by @publichealthscot.bsky.social on Tuesday this week. I've paired them with the latest >12-hour ED stays figures that were released on the same day. And I added a bit of grey shading to invite comments... #rstats #ggplot2

the scenario we all feared

I'm trying to create a chart that helps us understand - indirectly - what causes Emergency Department (ED) crowding. Here's a barcode graph of Acute Medical Unit (AMU) 'heaviness' (see the alt text for definition), showing how it relates to ED length of stay. #rstats #ggplot2