Neil Pettinger

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Neil Pettinger

Neil Pettinger

@kurtstat

Designs learning materials. Drives up and down motorways. Dissects health service data. Delivers training courses. Draws graphs.

Edinburgh, UK Katılım Aralık 2008
3K Takip Edilen1.7K Takipçiler
Neil Pettinger
Neil Pettinger@kurtstat·
Ben Lawers from Beinn Ghlas.
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Joe Hill
Joe Hill@jo3hill·
The FT reported this morning that the Government are looking at cutting back NHS recruitment in the upcoming workforce plan. This is a good idea. The NHS keeps hiring more and more staff, but delivering much less with their workforce. Our 'Hospital of the future' research papers called for an approach which uses much more automation and shifts more secondary care into the community. Between 2019 and 2023 hospital staff numbers grew significantly - consultants up by 15.8%, junior doctors by 24.6%, nurses up by 19.5% and support staff by 18.5%. In comparison, activity fell or stayed flat. Emergency admissions fell by 4.3%, and non-emergency admissions by 1.4%. Outpatient appointments grew by only 1.8%, and waiting list treatments grew by only 0.8%. We are buying much more capacity, but getting little or nothing to show for it. The pattern is really stark in A&E - between 2010 and 2022 attendances grew by about 24%, but doctor numbers skyrocketed by over 80%. It isn't sustainable to plan for an NHS workforce of up to 2.3 million people by the mid 2030s, employing 9 per cent of all workers in England. All other industries have to adapt and find ways to get productivity benefits over time, the NHS isn't different. AI isn't the whole answer, but it will be part of it. Clinical roles aren't unique in terms of their complexity or the risk considerations, and human clinicians make plenty of errors and mistakes in their work as it is. But language models are consistently improving over time, whereas human clinicians aren't - at some point it's likely that whole bundles of tasks will be outsourceable to machine intelligence, which will be a good thing for patients, medical professionals and taxpayers alike. @restate_thinks 'Hospital of the future' series is linked here, stats above are from the framing paper. re-state.co.uk/publications/h…
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Neil Pettinger
Neil Pettinger@kurtstat·
@TJCoats @jo3hill Yes, I always find that it's the fullness of the ED (the green scatterplot) that explains performance better than the number of arrivals (the red scatterplot). And the ED's fullness is - in turn - determined by the fullness of the wards and specialties downstream of it.
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Tim Coats
Tim Coats@TJCoats·
@jo3hill You have the A&E example productivity example just plain wrong. For A&E it’s not the attendance numbers that determine workload - its attendances multiplied by time the patient spends in A&E. Time in A&E has risen dramatically (boarding).
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Neil Pettinger
Neil Pettinger@kurtstat·
@Montyburnout123 Yes, but one of my complaints about NHS data analysts is that they rarely present data to meetings *as if they mean it*. There's no purpose. No conviction. They're utterly detached from (even ignorant of) the organisation's objectives. So all we're left with is insipid head.
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Monty burns
Monty burns@Montyburnout123·
@kurtstat Things might work better if we based decisions on logic and data, not heart and gut
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Neil Pettinger
Neil Pettinger@kurtstat·
There’s a striking sentence at the bottom of page three of @mrianleslie’s book How to Disagree: “When we disagree, we bring the whole of our selves to the conversation: head, heart and gut.” 1/2
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Neil Pettinger
Neil Pettinger@kurtstat·
@Montyburnout123 OK, yes, good point. Hard to gate-crash a meeting you weren't invited to. Easier to get copied into an email or WhatsApp discussion thread.
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Monty burns
Monty burns@Montyburnout123·
@kurtstat Meetings are the best way to exclude people whose opinion you want to suppress. Asynchronous methods make this more difficult.
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Neil Pettinger
Neil Pettinger@kurtstat·
@Montyburnout123 Mind you, I do concede that asynchronous forums allow more time and space for more *considered* interventions and responses. The best ideas don't always come from those who are best at thinking on their feet.
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Monty burns
Monty burns@Montyburnout123·
@kurtstat Is the crapness perhaps an inherent property of NHS meetings? Asynchronous methods of discussion are better in my opinion.
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Neil Pettinger
Neil Pettinger@kurtstat·
@Montyburnout123 That may well be the case. And indeed your description matches my experience of NHS meetings. But it's not a reason to give up on meetings. If meetings are crap, shouldn't we try to make them less crap?
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Monty burns
Monty burns@Montyburnout123·
@kurtstat In my experience NHS meetings are mostly about distributing future blame when something goes wrong. Decisions are made before meetings, disagreement is not allowed.
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Neil Pettinger
Neil Pettinger@kurtstat·
@jburnmurdoch Are we jumping too fast to 'fertility rate'? Isn't there an intermediate step? People (generally) have to be in long-term relationships before they have kids, so do we need to be clearer about why fewer people are entering into long-term relationships (if that is the case)?
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John Burn-Murdoch
John Burn-Murdoch@jburnmurdoch·
Excellent as ever from Jesus Some overlap w/ the thesis set out in my piece — that smartphones and social media are in large part accelerants, amplifiers and ‘internationalisers’ of social/cultural shifts that have been slowly unfolding for decades if not longer.
Jesús Fernández-Villaverde@JesusFerna7026

Smartphones are not the explanation for the recent decline in fertility. Instead, they are an accelerator of deeper forces already at work. Let’s start with the facts. Fertility is falling almost everywhere: in rich, middle-income, and poor countries; in secular and religious countries; and in countries with high and low levels of gender equality. The decline accelerated around 2014. So, no country-specific explanation will work unless you are willing to believe that 200 distinct country-specific explanations arrived at roughly the same time. Smartphones look like the obvious candidate: the first iPhone was released in 2007, and global adoption has been astonishingly fast. Economists understand the first major decline in fertility in advanced economies, from 6 or 7 children per woman throughout most of human history to about 1.8, that occurred between the early 1800s and roughly 1970, well before smartphones. The main drivers were a sharp fall in child mortality (effective fertility was rarely above 3 and often close to 2) and the shift from a low-skill, rural agrarian economy to a high-skill, urban industrial one. We have quantitative models that fit these facts well. Country-specific factors mattered too, of course. Proximity to low-fertility neighbors accelerated Hungary’s decline, while fragmented landowning structures accelerated France’s. But these were second-order mechanisms. This is also why most economists long considered Paul Ehrlich’s doom scenarios implausible. We forecast that fertility in middle- and low-income economies would follow the same path as in the rich, probably faster, because reductions in child mortality reached India or Africa at lower income levels (medical technology is nearly universal, and most gains come from handwashing and cheap antibiotics, not Mayo Clinic-level care). Much of what we see in Africa or parts of Latin America today is still that old story. But in the 1980s, a new pattern appeared. Japan and Italy fell below 1.8, the level we had thought was the new floor. By 1990, Japan was at 1.54 and Italy at 1.36. This second fertility decline began in Japan and Italy earlier than elsewhere, driven by country-specific factors, but the underlying dynamics were widespread: secularization, an education arms race, expensive housing, the dissolution of old social networks, and the shift to a service economy in which women’s bargaining power within the household is higher. The U.S. lagged because secularization came later, suburban housing remained relatively cheap, and African American fertility was still high. U.S. demographic patterns are exceptional and skew how academics (most of whom are in the U.S.) and the New York Times see the world. My best guess is that, without smartphones, Italy’s 2025 fertility rate would be about 1.24 rather than 1.14. I doubt anyone will document an effect larger than 0.1-0.2. Italy was at 1.19 in 1995, not far from today’s 1.14. The TFR is cyclical due to tempo effects, so I do not read too much into the rise between 1995 and 2007 or the decline from 1.27 in 2019 to 1.14 today. The direct effect of smartphones is not zero, but it is not, by itself, that large. Where social media, in general, and smartphones, in particular, matter is in the diffusion of social norms. What would have taken 25 years now happens in 10. Social media are not the cause of fertility decline; modernity is. But they are a very fast accelerator. That is why social media are a major part of the story behind Guatemala (yes, Guatemala) going from 3.8 children per woman in 2005 to 1.9 in 2025. Without them, Guatemala would also have reached 1.9, just 20 years later. Modernity, in its current form, is incompatible with replacement-level fertility. By modernity, I do not mean capitalism: fertility fell earlier and faster in socialist economies than in market economies. Socialist Hungary fell below replacement in 1960, and socialist Czechoslovakia in 1966 (both experienced small, short-lived baby booms in the mid-1970s). By modernity, I mean a society organized around rational, large-scale systems and formalized knowledge. Countries will not converge to the same fertility rate. East Asia is likely stuck near 1, possibly below, given its unbalanced gender norms and toxic education systems. Latin America faces the same gender problem plus weak growth prospects, so I expect something around 1.2. Northern Europe has more egalitarian family structures and might hold near 1.5. The very religious societies are probably the only ones that will sustain 1.8. All of this could change with AI or changes in population composition. We will see. But on the current evidence, deep sub-replacement fertility is the “new new normal.” Unless we reorganize our societies, better learn to handle it as best we can.

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Neil Pettinger
Neil Pettinger@kurtstat·
@Montyburnout123 But if we're not meeting, we're not disagreeing. And if we're not disagreeing, we're not deepening our knowledge. (Though I concede that this view of the world assumes that meetings are appropriately convened and properly conducted!)
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Monty burns
Monty burns@Montyburnout123·
@kurtstat Productivity occurs in spite of meetings not because of them. At least on Teams you can do some work at the same time as attending a meeting.
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Neil Pettinger
Neil Pettinger@kurtstat·
@drewhill79 I don't know. Maybe men are - in general - more motivated by target thresholds than women are? Your point about smart watches makes me want to see if I can find pre-smart watch era data to see if the spikes are less evident...
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Andrew Hill
Andrew Hill@drewhill79·
@kurtstat 🤣🤣🤣 I wonder what those actual spikes in the men’s graph are? Are we thinking this is more male runners looking at their smart watches and pushing themselves to get over the line at that timing? Or something else?
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Neil Pettinger
Neil Pettinger@kurtstat·
This happens to be a distribution of finishing times at the 2019 London Marathon, but I think it's a pattern we see in all marathons. The sudden spikes (at 02:59, 03:29 and 03:59, for example) are much more evident for men than for women.
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Neil Pettinger
Neil Pettinger@kurtstat·
@drewhill79 Ha ha! Yes! That thought (belatedly) occurred to me, too! (FWIW, the data I used for the graph was from the London_2019_mass_results.csv file. I didn't include data from London_2019_elite_results.csv!)
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Andrew Hill
Andrew Hill@drewhill79·
@kurtstat For any comparative work against modern datasets that X axis might need to start at 119 now 😬
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Hugh Laurie
Hugh Laurie@hughlaurie·
Well heck. The Arsenal. What an amazing achievement. BPM 150, dropping slowly.
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Duncan Alexander
Duncan Alexander@oilysailor·
Max Dowman is the first player born after ITV shut down Teletext to win the Premier League
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Neil Pettinger
Neil Pettinger@kurtstat·
@TJCoats Oh I like that idea. It fits with my general complaint that managers try to improve patient flow by focusing on individual patients rather than patients-as-a-whole.
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Tim Coats
Tim Coats@TJCoats·
@kurtstat If you want to increase the number of sub 3hr marathon runners you should definitely not try and get everyone to improve. You should concentrate on getting those between 3:00 and 3:10 to train a bit harder. BUT is this the best way to create overall improvement?
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Neil Pettinger
Neil Pettinger@kurtstat·
I've rashly said I'll do a 10-minute talk on the topic of "Endurance" at a local storytelling event on Friday. I thought I'd use this pair of graphs as my theme (thanks to @TJCoats for planting the idea a few weeks ago!). Anyone got any good 'compare-and-contrast' suggestions?
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