Neil Pettinger

@kurtstat.bsky.social

Healthcare data analyst. Aspiring Munroist.

About this time yesterday I was marvelling about how uplifting the World Cup has been, even though it’s taking place in Trump’s America. Incredible that’s he’s found a way to spoil it. An incredible achievement.

Data conversations need to take place between managers and data analysts. But managers don't initiate them because they have an antipathy towards data. And data analysts don't initiate them because they have an antipathy towards conversations.

This is a cross between a graph and a diagram. The horizontal axis is labelled "domain knowledge". The vertical axis is labelled "data knowledge". There's a blue square (labelled "Data analysts") positioned in the graph's top left quadrant and a red square (labelled "Managers") positioned in the graph's bottom right quadrant. Between the two squares is a double-pointed arrow labelled "Data conversations".

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

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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.

Stuart Hall's encoding/decoding model (adapted from his 1973 essay) made to look a bit smarter with blue and pink text boxes.

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

A scatterplot showing the relationship between Acute Medical Unit (AMU) 'heaviness' (measured along the horizontal axis) and Emergency Department (ED) length of stay (measured up the vertical axis). Two red dots in the chart represent the 'worst' day of the year (23 Jan 2024, when four-hour compliance was 40%) and the 'best' day of the year (23 Jun 2023, when four-hour compliance was 79%). A "grey zone of flow" has been (arbitrarily) drawn in the bottom right of the chart.

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?

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.

A scatterplot showing the relationship between the percentage of an emergency department's patients seen within 12 hours (measured along the horizontal axis) and the median ambulance turnaround time (measured in minutes up the vertical axis). The scatterplot has 43 blue dots on it, each dot representing a single week in the 43 -week period from 18 November 2024 to 8 September 2025. A clear pattern is visible. Weeks with high 12-hour compliance percentages are associated with shorter ambulance turnaround times. And weeks with low 12-hour compliance percentages are associated with longer ambulance turnaround times.

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...

What Do We Have To Lose

If Keir Starmer won’t even make a moral case against deporting our friends and neighbours, then what is the point of him? Plus: some natural borders; and the non-existence of grey, and other letters.

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