diff --git a/content/post/2020-07-13-getting-started-in-data-science-for-healthcare.md b/content/post/2020-07-13-getting-started-in-data-science-for-healthcare.md index 9e460ce..5bab181 100644 --- a/content/post/2020-07-13-getting-started-in-data-science-for-healthcare.md +++ b/content/post/2020-07-13-getting-started-in-data-science-for-healthcare.md @@ -3,10 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2020-07-13T15:55:37Z" -guid: http://chrisbeeley.net/?p=1395 -id: 1395 title: Getting started in data science for healthcare -url: /?p=1395 --- I just recruited to a data science post at Nottinghamshire Healthcare NHS Trust and I’ve been asked for feedback by several people about how to get started in data science in healthcare, and indeed how to get a job in data science in healthcare. I will also be recruiting another data scientist for our team in a few months. This post is designed to give you a feel for what we were looking for in the job that I just recruited to, as well as to the job that is coming up. They’re slightly different skill sets as I will discuss. @@ -31,4 +28,4 @@ Again, we need someone who can work in a team (no [hero coders](https://hackerno Some people have told me I’m wasting my time managing my own servers as a data scientist and I really need to get proper IT support, and maybe they’re right, but I’ve come this far, even if I am doing it wrong. I’ve been learning Linux server stuff on my own server for 7 years. If you want to learn this way without buying your own cloud server then just buy a Raspberry Pi and ssh into it from behind your firewall at home. Set up a LAMP stack, set up WordPress, set up the free versions of RStudio Server and Shiny Server, run plumber APIs, run PHP, write a Django application, whatever. You’ll get in the most hideous mess and tear your hair out for entire weekends and you’ll look back at those weekends fondly and be glad of all the learning you did that day 😀. And if you get in a complete mess just wipe the SD card and start again. -As I say, this is all caveat emptor. Your mileage may vary. But if you want my opinions then these are they. Keep an eye on my Twitter if you’re interested in the job, and feel free to @ or DM me, or indeed send an email, my address is in my Twitter profile. \ No newline at end of file +As I say, this is all caveat emptor. Your mileage may vary. But if you want my opinions then these are they. \ No newline at end of file diff --git a/content/post/2020-08-05-shiny-modules-for-beginners.md b/content/post/2020-08-05-shiny-modules-for-beginners.md index edca195..3fd3fc0 100644 --- a/content/post/2020-08-05-shiny-modules-for-beginners.md +++ b/content/post/2020-08-05-shiny-modules-for-beginners.md @@ -3,10 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2020-08-05T17:53:38Z" -guid: http://chrisbeeley.net/?p=1411 -id: 1411 title: Shiny modules for beginners -url: /?p=1411 --- I’ve seen some discussion on the Internet about whether people learning Shiny should start with modules or if they’re an advanced topic. I’m not going to link to any examples because this post is definitely not me saying- hey look at this rubbish over here, here’s why it’s wrong. I’ve seen a couple of posts talking about it. But I just thought I would chip in my perspective. diff --git a/content/post/2020-10-02-analyst-analyse-thyself.md b/content/post/2020-10-02-analyst-analyse-thyself.md index f8d3b34..6e6df67 100644 --- a/content/post/2020-10-02-analyst-analyse-thyself.md +++ b/content/post/2020-10-02-analyst-analyse-thyself.md @@ -3,10 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2020-10-02T09:00:14Z" -guid: http://chrisbeeley.net/?p=1434 -id: 1434 title: Analyst, analyse thyself -url: /?p=1434 --- I work in a small (growing) team of data scientists and we’re part of a larger analytic unit which has a focus on innovation in analytics (hence us) and public health methods. We have a pretty broad remit to do interesting and useful stuff and we focus on things that we think are useful (for example, applying data science methods to problems relating to equity of access to services) and things that people ask us to help with. diff --git a/content/post/2020-10-19-serving-rstudio-connect-content-to-logged-in-and-anonymous-users.md b/content/post/2020-10-19-serving-rstudio-connect-content-to-logged-in-and-anonymous-users.md index d2da46d..2433523 100644 --- a/content/post/2020-10-19-serving-rstudio-connect-content-to-logged-in-and-anonymous-users.md +++ b/content/post/2020-10-19-serving-rstudio-connect-content-to-logged-in-and-anonymous-users.md @@ -3,10 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2020-10-19T17:16:21Z" -guid: http://chrisbeeley.net/?p=1455 -id: 1455 title: Serving RStudio Connect content to logged in and anonymous users -url: /?p=1455 --- We have our [patient feedback dashboard](https://involve.nottshc.nhs.uk:8443/experience/) in the open where anyone can see what Nottinghamshire Healthcare NHS Trust’s patients are saying about us. Now I’ve got a Connect licence I thought perhaps I might build another version for our staff where I put stuff that we can’t share- for example the comments of people who click the “I do not wish to share this comment” box. diff --git a/content/post/2021-01-29-accessing-plot-characteristics-in-shiny-modules.md b/content/post/2021-01-29-accessing-plot-characteristics-in-shiny-modules.md index c4a13da..63c9e05 100644 --- a/content/post/2021-01-29-accessing-plot-characteristics-in-shiny-modules.md +++ b/content/post/2021-01-29-accessing-plot-characteristics-in-shiny-modules.md @@ -3,10 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2021-01-29T22:47:49Z" -guid: http://chrisbeeley.net/?p=1478 -id: 1478 title: Accessing plot characteristics in Shiny modules -url: /?p=1478 --- It was my New Year’s resolution to blog more and that’s going really well because this is the first blog I’ve done all year and it’s nearly the end of January. Well, I suppose to be fair I did do [a post on our team blog](https://cdu-data-science-team.github.io/team-blog/posts/2021-01-20-a-new-github-release-and-future-projects/) but that feels like I’m making excuses. @@ -17,9 +14,6 @@ We wanted to [access the height of a Shiny plot at runtime](https://github.com/r When I looked at the raw HTML (which I did, in desperation) I saw that the input was actually called “output\_mod\_sentiment\_ui\_1-sentiment\_plot\_upset”. The mod\_sentiment bit is the name spacing. So I got pretty close when I tried session$clientData$output\_mod\_sentiment\_ui\_1-sentiment\_plot\_upset\_width. But R thought that the hyphen was a minus, so that didn’t work either. Then the light dawned -
``` -
-session$clientData$`output_mod_sentiment_ui_1-sentiment_plot_upset_width`
-```
+session$clientData$\`output_mod_sentiment_ui_1-sentiment_plot_upset_width\`
 
-
That’s it. Simple, but it took me a while, so hopefully if you have the same problem you will find this post. \ No newline at end of file +That’s it. Simple, but it took me a while, so hopefully if you have the same problem you will find this post. \ No newline at end of file diff --git a/content/post/2021-02-18-building-generic-shiny-applications-with-a-data-module.md b/content/post/2021-02-18-building-generic-shiny-applications-with-a-data-module.md index 7558897..f14ff6c 100644 --- a/content/post/2021-02-18-building-generic-shiny-applications-with-a-data-module.md +++ b/content/post/2021-02-18-building-generic-shiny-applications-with-a-data-module.md @@ -3,10 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2021-02-18T16:13:18Z" -guid: http://chrisbeeley.net/?p=1489 -id: 1489 title: Building generic Shiny applications with a data module -url: /?p=1489 --- We’re rebuilding our patient experience dashboard at the moment, partly to incorporate some of the work that [we’re doing on text mining](https://github.com/CDU-data-science-team/positive_about_change_text_mining) and partly to connect it up to other types of information we have like staff experience and clinical outcomes. It has to be reusable because we’re using it as the basis of the text mining dashboard that we’re building for any provider trust to use with their friends and family test data. We’re trying to make everything reusable anyway partly because the different bits of the NHS should all cooperate and produce stuff together that everyone can use and partly because we’re realising that when you make code reusable the first person who can reuse it is you, 6 months later on a similar project. diff --git a/content/post/2021-03-26-sql-versus-analytic-tools.md b/content/post/2021-03-26-sql-versus-analytic-tools.md index 752b6e9..4c4d748 100644 --- a/content/post/2021-03-26-sql-versus-analytic-tools.md +++ b/content/post/2021-03-26-sql-versus-analytic-tools.md @@ -3,10 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2021-03-26T10:43:42Z" -guid: https://chrisbeeley.net/?p=1495 -id: 1495 title: SQL versus analytic tools -url: /?p=1495 --- From a [tweet from my NHS-R buddy John MacKintosh](https://twitter.com/_johnmackintosh/status/1374986918878965760?s=19) diff --git a/content/post/2021-05-31-what-do-we-want-from-senior-analysts-in-the-nhs.md b/content/post/2021-05-31-what-do-we-want-from-senior-analysts-in-the-nhs.md index ac67ee1..d40f373 100644 --- a/content/post/2021-05-31-what-do-we-want-from-senior-analysts-in-the-nhs.md +++ b/content/post/2021-05-31-what-do-we-want-from-senior-analysts-in-the-nhs.md @@ -3,10 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2021-05-31T12:02:03Z" -guid: https://chrisbeeley.net/?p=1514 -id: 1514 title: What do we want from senior analysts in the NHS? -url: /?p=1514 --- I’ve been meaning to write this for ages and I’ve just had a rather silly conversation on Twitter about managers and leaders in the NHS which has inspired me to get on with it. I think most people are agreed that we have A Problem with mangers and leaders in the analytic space. Much ink has been spilled in the subject, and I think that the two main conclusions of all this ink are broadly accepted by everyone. They are, briefly: diff --git a/content/post/2021-06-01-managing-data-science-teams-in-the-trenches.md b/content/post/2021-06-01-managing-data-science-teams-in-the-trenches.md index e3f1740..f024348 100644 --- a/content/post/2021-06-01-managing-data-science-teams-in-the-trenches.md +++ b/content/post/2021-06-01-managing-data-science-teams-in-the-trenches.md @@ -3,10 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2021-06-01T12:11:00Z" -guid: https://chrisbeeley.net/?p=1517 -id: 1517 title: Managing data science teams in the trenches -url: /?p=1517 --- We’re systematically devaluing management and leadership in the analyst space, and I encounter a lot of people who think that a day with no code written is a day wasted. I do write code, but I do a lot of other valuable stuff too. I’ve written this post as someone who is very new to managing people with my personal opinion, so just like my posts on proxied SSL with Apache, there is your caveat emptor 🙂 @@ -23,4 +20,4 @@ This is pretty basic stuff, really. It feels a bit silly to have to spell it out I’ve never in my life had a manager who has the slightest idea what autoregression is or how to test the assumptions of OLS regression. I’m really happy now that I do manage people and that I do know what those things are, and I hope the people I manage can benefit from my understanding of what they’re doing (even if they usually know way more about it than I do- I can at least keep up if they explain it to me). -(if you’ve read my [previous post](https://chrisbeeley.net/?p=1514) and you’re paying attention you’ll realise that I’ve just contradicted myself by saying firstly that analysts should do more than just write code all day, and then said in this post that a manager’s job is to help analysts write code all day. Forgive me. In reality the people in the trench have got other people in the trench, or possibly in a neighbouring trench, and it’s their job to stick their head in that trench and help that person write code instead of needing to get out of their trench, before coming back to their own trench. Indeed, really, the trench visitor is in fact in their own trench, and someone else sticks their head in there occasionally, but the analogy gets a bit convoluted and silly at this point. I think you get the idea, even if it doesn’t translate to actual trenches within trenches within trenches) \ No newline at end of file +(if you’ve read my [previous post]({{< ref "2021-05-31-what-do-we-want-from-senior-analysts-in-the-nhs.md" >}}) and you’re paying attention you’ll realise that I’ve just contradicted myself by saying firstly that analysts should do more than just write code all day, and then said in this post that a manager’s job is to help analysts write code all day. Forgive me. In reality the people in the trench have got other people in the trench, or possibly in a neighbouring trench, and it’s their job to stick their head in that trench and help that person write code instead of needing to get out of their trench, before coming back to their own trench. Indeed, really, the trench visitor is in fact in their own trench, and someone else sticks their head in there occasionally, but the analogy gets a bit convoluted and silly at this point. I think you get the idea, even if it doesn’t translate to actual trenches within trenches within trenches) \ No newline at end of file diff --git a/content/post/2021-07-14-shoddy-data.md b/content/post/2021-07-14-shoddy-data.md index 070640d..8993d24 100644 --- a/content/post/2021-07-14-shoddy-data.md +++ b/content/post/2021-07-14-shoddy-data.md @@ -3,12 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2021-07-14T16:42:02Z" -guid: https://chrisbeeley.net/?p=1530 -id: 1530 -spay_email: -- "" title: Shoddy data -url: /?p=1530 --- You know, naming no names because I’ll get in trouble but someone somewhere has paid for some data from a proprietary vendor and they’re shipping absolutely unusable garbage data. diff --git a/content/post/2021-07-18-stop-punishing-people-with-data.md b/content/post/2021-07-18-stop-punishing-people-with-data.md index 4346fde..bddfc60 100644 --- a/content/post/2021-07-18-stop-punishing-people-with-data.md +++ b/content/post/2021-07-18-stop-punishing-people-with-data.md @@ -3,12 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2021-07-18T15:28:30Z" -guid: https://chrisbeeley.net/?p=1533 -id: 1533 -spay_email: -- "" title: Stop punishing people with data -url: /?p=1533 ---
NHS data people know all about [Goodhart’s law](https://en.wikipedia.org/wiki/Goodhart%27s_law). First stated by Goodhart as the not very catchy diff --git a/content/post/2021-07-19-graphs-tables.md b/content/post/2021-07-19-graphs-tables.md index f36ece6..8f0bb96 100644 --- a/content/post/2021-07-19-graphs-tables.md +++ b/content/post/2021-07-19-graphs-tables.md @@ -3,12 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2021-07-19T17:30:17Z" -guid: https://chrisbeeley.net/?p=1537 -id: 1537 -spay_email: -- "" title: Graphs > tables -url: /?p=1537 --- One phenomenon that I find very strange in the NHS (and elsewhere, probably, I’ve never worked anywhere else) is the obsession people have with having tables of numbers instead of graphs. I have encountered this absolutely everywhere. People really want to know whether something is 21.4% of the whole or 19.2% of the whole and they can’t tell by looking at the beautiful graph that you’ve drawn. diff --git a/content/post/2021-08-19-pay-and-reward.md b/content/post/2021-08-19-pay-and-reward.md index 4834ae3..65e6b69 100644 --- a/content/post/2021-08-19-pay-and-reward.md +++ b/content/post/2021-08-19-pay-and-reward.md @@ -3,12 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2021-08-19T22:30:25Z" -guid: https://chrisbeeley.net/?p=1545 -id: 1545 -spay_email: -- "" title: Pay and reward -url: /?p=1545 --- I’m reading No Rules Rules, the Netflix management book. It’s really good, lots of interesting stuff in there about doing things differently and although clearly there’s a lot I can’t do in the NHS, there are lessons in there for sure. diff --git a/content/post/2021-09-17-data-saves-lives-and-so-does-open-code.md b/content/post/2021-09-17-data-saves-lives-and-so-does-open-code.md index 5bc99f4..6aa0715 100644 --- a/content/post/2021-09-17-data-saves-lives-and-so-does-open-code.md +++ b/content/post/2021-09-17-data-saves-lives-and-so-does-open-code.md @@ -3,12 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2021-09-17T16:56:25Z" -guid: https://chrisbeeley.net/?p=1554 -id: 1554 -spay_email: -- "" title: Data saves lives- and so does open code -url: /?p=1554 --- I’m reading [data saves lives](https://www.gov.uk/government/publications/data-saves-lives-reshaping-health-and-social-care-with-data-draft/data-saves-lives-reshaping-health-and-social-care-with-data-draft). And look, it’s that thing that I say all the time, that I have pinned on my Twitter profile, the thing I’ve heard time and time again for a decade that everybody just stands around nodding at and nothing actually changes. I quote: diff --git a/content/post/2021-11-13-make-statistics-sexy.md b/content/post/2021-11-13-make-statistics-sexy.md index 780dbba..b49d2f2 100644 --- a/content/post/2021-11-13-make-statistics-sexy.md +++ b/content/post/2021-11-13-make-statistics-sexy.md @@ -3,12 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2021-11-13T23:12:54Z" -guid: https://chrisbeeley.net/?p=1570 -id: 1570 -spay_email: -- "" title: Make statistics sexy -url: /?p=1570 --- I’ve been enjoined to make [statistics sexy](https://twitter.com/ChrisBeeley/status/1458382972990763010?t=-jJDY6EMGq2UNuWlA1HKow&s=19). It’s really taking root in my brain.There are no easy answers in statistics; it’s a long, hard road. It’s rigorous, and honest, and that’s why I love it. [Frank Harrell’s talk at NHS-R](https://youtu.be/5HnW1YP3vTk) typified this. The price of truth can be very high- like binning all the data from your £1m study instead of doing what many do which is slice it into so many pieces that something looks shiny and publishing that. diff --git a/content/post/2021-11-16-in-defence-of-dashboards.md b/content/post/2021-11-16-in-defence-of-dashboards.md index bb7889e..913a6be 100644 --- a/content/post/2021-11-16-in-defence-of-dashboards.md +++ b/content/post/2021-11-16-in-defence-of-dashboards.md @@ -3,10 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2021-11-16T22:19:27Z" -guid: https://chrisbeeley.net/?p=1574 -id: 1574 title: In defence of dashboards -url: /?p=1574 --- I’ve had lively debates about dashboards with various people, including someone in my own team, and somebody on Twitter just mentioned that dashboards are often not used (this blog post will be my response to this tweet, not the first time I’ve answered a tweet with a blog and very on brand for me 😉). @@ -15,7 +12,7 @@ I should acknowledge at the top that I’m The Dashboard Guy. I’ve written boo People say that dashboards proliferate, and that nobody uses them. That is quite true in a lot of cases. I’d like to suggest why that is so, and talk about when people do use them. -The first thing to say is that in the NHS (which is where I have always and will always work) many staff are not engaged with data in general. They’re not engaged with data, they’re not engaged with analysis, they’re not engaged with reports, they’re just not engaged. [They see data as a punishment, a “test” they cannot win](https://chrisbeeley.net/?p=1533). They can’t see the point of it and it’s just a distraction at best and over-critical and unfair at worst. +The first thing to say is that in the NHS (which is where I have always and will always work) many staff are not engaged with data in general. They’re not engaged with data, they’re not engaged with analysis, they’re not engaged with reports, they’re just not engaged. [They see data as a punishment, a “test” they cannot win]({{< ref "2021-07-18-stop-punishing-people-with-data.md" >}}). They can’t see the point of it and it’s just a distraction at best and over-critical and unfair at worst. So my first question would be what do you replace the dashboards with? What will they engage with? I became The Dashboard Guy because we used to make a 300 page report by hand every quarter. It took literal person weeks and every recipient was only interested in their four page chunk. It was ridiculously inefficient. But everybody did want their four page chunk. Dashboards are useful for data that people want to see. diff --git a/content/post/2021-11-24-in-defence-of-eating.md b/content/post/2021-11-24-in-defence-of-eating.md index 184e427..960d5cf 100644 --- a/content/post/2021-11-24-in-defence-of-eating.md +++ b/content/post/2021-11-24-in-defence-of-eating.md @@ -3,12 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2021-11-24T15:07:03Z" -guid: https://chrisbeeley.net/?p=1582 -id: 1582 -spay_email: -- "" title: In defence of eating -url: /?p=1582 --- One weird thing in remote/ pandemic times is that people have started turning their cameras off when they eat. I’m all for the right to turn your camera off, I think you should be able to do that at any time without giving a reason, but I think it’s a shame if people think that they can’t eat on camera. I have therefore been glad to eat several large, difficult to eat things in meetings on camera recently, to perhaps give others the idea that it’s okay if they want to do it too. diff --git a/content/post/2021-12-16-in-defence-of-holiday-working.md b/content/post/2021-12-16-in-defence-of-holiday-working.md index 8910104..98edf1d 100644 --- a/content/post/2021-12-16-in-defence-of-holiday-working.md +++ b/content/post/2021-12-16-in-defence-of-holiday-working.md @@ -3,10 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2021-12-16T21:21:14Z" -guid: https://chrisbeeley.net/?p=1591 -id: 1591 title: In defence of holiday working -url: /?p=1591 --- This might be a little bit controversial, this post. If you hate it please don’t be offended, it’s just my opinion. Totally open to being completely wrong always, especially here. diff --git a/content/post/2021-12-22-in-defence-of-looking-at-jobs.md b/content/post/2021-12-22-in-defence-of-looking-at-jobs.md index 6cbf59d..60a710f 100644 --- a/content/post/2021-12-22-in-defence-of-looking-at-jobs.md +++ b/content/post/2021-12-22-in-defence-of-looking-at-jobs.md @@ -3,12 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2021-12-22T11:14:41Z" -guid: https://chrisbeeley.net/?p=1595 -id: 1595 -spay_email: -- "" title: In defence of looking at jobs -url: /?p=1595 --- Nobody should ever have to apologise for looking at jobs, however settled they are. Looking at jobs just means one of: diff --git a/content/post/2022-01-10-in-defence-of-the-ordinary.md b/content/post/2022-01-10-in-defence-of-the-ordinary.md index b7a0b31..12417dc 100644 --- a/content/post/2022-01-10-in-defence-of-the-ordinary.md +++ b/content/post/2022-01-10-in-defence-of-the-ordinary.md @@ -3,10 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2022-01-10T17:40:24Z" -guid: https://chrisbeeley.net/?p=1599 -id: 1599 title: In defence of the ordinary -url: /?p=1599 --- I think this might be a general cultural problem, but I notice it a lot in my field of healthcare analytics. There are lots of “case studies” and “pathfinders”, that kind of thing, groups of people who are doing amazing stuff. diff --git a/content/post/2022-05-22-the-goldacre-review-greatest-hits.md b/content/post/2022-05-22-the-goldacre-review-greatest-hits.md index 8156a8f..535d448 100644 --- a/content/post/2022-05-22-the-goldacre-review-greatest-hits.md +++ b/content/post/2022-05-22-the-goldacre-review-greatest-hits.md @@ -3,10 +3,7 @@ author: chrisbeeley categories: - Uncategorized date: "2022-05-22T12:18:25Z" -guid: https://chrisbeeley.net/?p=1626 -id: 1626 title: The Goldacre review- greatest hits -url: /?p=1626 --- I absolutely love the [Goldacare review](https://www.gov.uk/government/publications/better-broader-safer-using-health-data-for-research-and-analysis/better-broader-safer-using-health-data-for-research-and-analysis), I really can’t praise it enough, and I will be doing a lot of work based on it in the coming weeks and months looking at it from the perspective of my own Trust and, (with others) from the perspective of my ICS, and NHS-R. NHS-R has a couple of repos looking at matters related to the review ([statement on tools](https://github.com/nhs-r-community/statements-on-tools) and [NHS-R vision](https://github.com/nhs-r-community/nhs-r_vision)) and we need to do some thinking about stuff that particularly comes out of this review that we can look at (which I have started [doing on my own](https://chrisbeeley.github.io/notebook/docs/goldacre_review/nhs-r/), community effort will follow). diff --git a/content/post/2024-05-04-decisions-decisions.md b/content/post/2024-05-04-decisions-decisions.md index 9a8268c..01f1fb2 100644 --- a/content/post/2024-05-04-decisions-decisions.md +++ b/content/post/2024-05-04-decisions-decisions.md @@ -14,7 +14,7 @@ The general feeling for an analyst as they come up the ranks, I would say, is fe The first reason people ask me stuff is because I know what I'm talking about in my little bit of data science. I'm happy with this one, clearly. I've already recruited such a good team that I think already it is true that any question about data science would be better answered by at least one of the team, and that's entirely what I want, but I do obviously know some stuff and I can answer questions and talk about it. I'm going to put in this category stuff that I should answer better than the team too, which would be strategic questions about data science. This is less familiar ground to me but I have never had a technical person as a manager and never will now so I'm reasonably comfortable plotting a course, although clearly sometimes I will be right and sometimes wrong. -The second reason people ask me stuff is because I'm the human shield if it all goes wrong. For example, thorny issues of prioritisation come up sometimes. We have tough choices to make about what to do and what not to do, the order to do it in, how well to do it, and so on. Making these decisions is clearly a team sport- between the customers, and me, and the team. If we get it wrong someone suffers- the customers don't get what they want, the team work too hard or on something they don't believe in. But owning the decisions is my job. I want the customer to feel assured that we are going to get the calls right, and I want the team to know that if it all goes wrong it's my job to explain why, and it's my decision making process that got us there. I'm accountable, not them. As I said in the [previous post on this blog]({{< ref "2024-03-25-new-year-new-blog.md" >}} "About Us") that's what the extra money is for. Not for having all the answers, but for owning the solutions, trying to find a path through any problems, and always being in front of your team if it all goes wrong. +The second reason people ask me stuff is because I'm the human shield if it all goes wrong. For example, thorny issues of prioritisation come up sometimes. We have tough choices to make about what to do and what not to do, the order to do it in, how well to do it, and so on. Making these decisions is clearly a team sport- between the customers, and me, and the team. If we get it wrong someone suffers- the customers don't get what they want, the team work too hard or on something they don't believe in. But owning the decisions is my job. I want the customer to feel assured that we are going to get the calls right, and I want the team to know that if it all goes wrong it's my job to explain why, and it's my decision making process that got us there. I'm accountable, not them. As I said in the [previous post on this blog]({{< ref "2024-03-25-new-year-new-blog.md" >}}) that's what the extra money is for. Not for having all the answers, but for owning the solutions, trying to find a path through any problems, and always being in front of your team if it all goes wrong. So far so good. I'm on those two now, and it feels natural to me to give good advice where it's needed, help make the best decisions we can, and to own those decisions. And now we come to the last reason, which I'm still not great with. The third reason people ask me stuff is just out of sheer it's my job to decide stuff. Sometimes there are just no correct answers or no data to answer the questions with, sometimes there is deadlock between two parties. Sometimes people who would be better at answering the questions don't want to own the decisions for whatever reason (sometimes it involves money, that's a common one). So I will advise or make decisions because someone has to, and the most obvious person in the room to do that is me. A classic thing I've always noticed before I was given any decision making power is a group of managers all sitting round deciding on the visual design of something. They're all completely ignorant of visual design, it would be far better to get somebody that understands visual design to decide, but it just feels natural for the managers to sit around and argue about it and pick something. Honestly I feel like some people are way too good at this, they jump straight in with their opinions without any apparent regard for their complete ignorance, but maybe I'm being unfair. Maybe they're perfectly well aware that they don't know what they're talking about, but they've been at this game longer than me and they know that their role in that moment is to make or contribute to a decision. diff --git a/public/404.html b/public/404.html index 57478d5..15d8a7d 100644 --- a/public/404.html +++ b/public/404.html @@ -7,7 +7,7 @@ - + @@ -31,11 +31,12 @@ - + - - + + + diff --git a/public/?p=1016/index.html b/public/?p=1016/index.html index 41ebcf3..5ded2ec 100644 --- a/public/?p=1016/index.html +++ b/public/?p=1016/index.html @@ -7,7 +7,7 @@ Ellen Townsend: Small talk saves lives — IMH Blog (Nottingham) | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1017/index.html b/public/?p=1017/index.html index 518058e..a515dbe 100644 --- a/public/?p=1017/index.html +++ b/public/?p=1017/index.html @@ -7,7 +7,7 @@ Filtering data straight into a plot with tidyverse | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1023/index.html b/public/?p=1023/index.html index caca24e..c7bf91a 100644 --- a/public/?p=1023/index.html +++ b/public/?p=1023/index.html @@ -7,7 +7,7 @@ One editor to rule them all- Atom | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1025/index.html b/public/?p=1025/index.html index 66e700b..2da71b2 100644 --- a/public/?p=1025/index.html +++ b/public/?p=1025/index.html @@ -7,7 +7,7 @@ Better Git commit messages | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1030/index.html b/public/?p=1030/index.html index 9c757e3..7b8ee0e 100644 --- a/public/?p=1030/index.html +++ b/public/?p=1030/index.html @@ -7,7 +7,7 @@ Font size of code in .Rpres presentations | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1032/index.html b/public/?p=1032/index.html index eb6b24f..fda21a5 100644 --- a/public/?p=1032/index.html +++ b/public/?p=1032/index.html @@ -7,7 +7,7 @@ Analysis tools for Manager Joe | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1037/index.html b/public/?p=1037/index.html index 31c3078..58ecf39 100644 --- a/public/?p=1037/index.html +++ b/public/?p=1037/index.html @@ -7,7 +7,7 @@ Failure to produce pdf with RMarkdown tidyverse | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1042/index.html b/public/?p=1042/index.html index 51e9f95..7db0201 100644 --- a/public/?p=1042/index.html +++ b/public/?p=1042/index.html @@ -7,7 +7,7 @@ Gathering data (wide to long) in the tidyverse | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1047/index.html b/public/?p=1047/index.html index 57b4370..ddcd67d 100644 --- a/public/?p=1047/index.html +++ b/public/?p=1047/index.html @@ -7,7 +7,7 @@ Analysing runs from the Polar web flow service | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1052/index.html b/public/?p=1052/index.html index a373374..b44ea09 100644 --- a/public/?p=1052/index.html +++ b/public/?p=1052/index.html @@ -7,7 +7,7 @@ New Year blog post | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1057/index.html b/public/?p=1057/index.html index 36d440f..105d68d 100644 --- a/public/?p=1057/index.html +++ b/public/?p=1057/index.html @@ -7,7 +7,7 @@ One weird trick to getting column types right with read_csv | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1064/index.html b/public/?p=1064/index.html index 1b0b994..5dea84f 100644 --- a/public/?p=1064/index.html +++ b/public/?p=1064/index.html @@ -7,7 +7,7 @@ Scraping the RStudio webinar list | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1077/index.html b/public/?p=1077/index.html index 36cf4c7..de18f49 100644 --- a/public/?p=1077/index.html +++ b/public/?p=1077/index.html @@ -7,7 +7,7 @@ Securing Shiny Server over SSL with Apache on Ubuntu | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=108/index.html b/public/?p=108/index.html index fc5132a..3228094 100644 --- a/public/?p=108/index.html +++ b/public/?p=108/index.html @@ -7,7 +7,7 @@ Robin Hood marathon results | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1092/index.html b/public/?p=1092/index.html index 049a4dd..d31574e 100644 --- a/public/?p=1092/index.html +++ b/public/?p=1092/index.html @@ -7,7 +7,7 @@ Convert icons to different colours | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1096/index.html b/public/?p=1096/index.html index e151103..ab65239 100644 --- a/public/?p=1096/index.html +++ b/public/?p=1096/index.html @@ -7,7 +7,7 @@ Checking memory usage in R | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1098/index.html b/public/?p=1098/index.html index f919c8c..932bdd0 100644 --- a/public/?p=1098/index.html +++ b/public/?p=1098/index.html @@ -7,7 +7,7 @@ Recoding to NA with dplyr | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1104/index.html b/public/?p=1104/index.html index 4b52432..d1f91bd 100644 --- a/public/?p=1104/index.html +++ b/public/?p=1104/index.html @@ -7,7 +7,7 @@ Selectively hide text with JavaScript in RMarkdown | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1116/index.html b/public/?p=1116/index.html index d266071..a58fb1d 100644 --- a/public/?p=1116/index.html +++ b/public/?p=1116/index.html @@ -7,7 +7,7 @@ Passing strings as variables from a Shiny app into dplyr | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1124/index.html b/public/?p=1124/index.html index d58e7bc..9ce2dd1 100644 --- a/public/?p=1124/index.html +++ b/public/?p=1124/index.html @@ -7,7 +7,7 @@ Shiny Pro in a Windows/ NHS environment, part 1: The curse of Kerberos | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1143/index.html b/public/?p=1143/index.html index 374db59..914c871 100644 --- a/public/?p=1143/index.html +++ b/public/?p=1143/index.html @@ -7,7 +7,7 @@ Producing several plots at once with RMarkdown and purrr | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1147/index.html b/public/?p=1147/index.html index ae9bda3..68e5541 100644 --- a/public/?p=1147/index.html +++ b/public/?p=1147/index.html @@ -7,7 +7,7 @@ Jupyter, Python, interactive web frameworks, and more | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1152/index.html b/public/?p=1152/index.html index 7bc29bb..5eb63d8 100644 --- a/public/?p=1152/index.html +++ b/public/?p=1152/index.html @@ -7,7 +7,7 @@ In praise of awkward questions | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1155/index.html b/public/?p=1155/index.html index 39c0938..6dff101 100644 --- a/public/?p=1155/index.html +++ b/public/?p=1155/index.html @@ -7,7 +7,7 @@ Filling in non missing elements by row (Survey Monkey masterclass) | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1157/index.html b/public/?p=1157/index.html index f50ba73..122a68c 100644 --- a/public/?p=1157/index.html +++ b/public/?p=1157/index.html @@ -7,7 +7,7 @@ The shinyverse | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1159/index.html b/public/?p=1159/index.html index 33f5337..a63a381 100644 --- a/public/?p=1159/index.html +++ b/public/?p=1159/index.html @@ -7,7 +7,7 @@ Produce tables in loop | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1170/index.html b/public/?p=1170/index.html index 550453d..72c4761 100644 --- a/public/?p=1170/index.html +++ b/public/?p=1170/index.html @@ -7,7 +7,7 @@ Drawing stacked barcharts the tidyverse way | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1173/index.html b/public/?p=1173/index.html index 5628ca4..c3f4529 100644 --- a/public/?p=1173/index.html +++ b/public/?p=1173/index.html @@ -7,7 +7,7 @@ A tidy text talk and some stuff from my Shiny book | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1181/index.html b/public/?p=1181/index.html index 5adced0..bcda2b8 100644 --- a/public/?p=1181/index.html +++ b/public/?p=1181/index.html @@ -7,7 +7,7 @@ New Year&#8217;s post | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1186/index.html b/public/?p=1186/index.html index bc9083c..ac01798 100644 --- a/public/?p=1186/index.html +++ b/public/?p=1186/index.html @@ -7,7 +7,7 @@ Data science accelerator lesson one- build a pipeline and ship the code! | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1188/index.html b/public/?p=1188/index.html index 2690347..8a52888 100644 --- a/public/?p=1188/index.html +++ b/public/?p=1188/index.html @@ -7,7 +7,7 @@ Dplyr function to replace nested ifelse (like SQL CASE WHEN) | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1190/index.html b/public/?p=1190/index.html index cb98309..34ef5ec 100644 --- a/public/?p=1190/index.html +++ b/public/?p=1190/index.html @@ -7,7 +7,7 @@ Citing R packages in RMarkdown | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1195/index.html b/public/?p=1195/index.html index 8e5514c..5d3f2ca 100644 --- a/public/?p=1195/index.html +++ b/public/?p=1195/index.html @@ -7,7 +7,7 @@ A world of #plotthedots and&#8230; what else? | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1198/index.html b/public/?p=1198/index.html index 1ab2819..8841ec8 100644 --- a/public/?p=1198/index.html +++ b/public/?p=1198/index.html @@ -7,7 +7,7 @@ Suppress console output with ggplot, purrr, and RMarkdown | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1209/index.html b/public/?p=1209/index.html index 0013a37..50f800f 100644 --- a/public/?p=1209/index.html +++ b/public/?p=1209/index.html @@ -7,7 +7,7 @@ Producing RMarkdown reports with Plumber | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1212/index.html b/public/?p=1212/index.html index 5fe334c..685dbdf 100644 --- a/public/?p=1212/index.html +++ b/public/?p=1212/index.html @@ -7,7 +7,7 @@ Adding line returns in RMarkdown in a loop | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1214/index.html b/public/?p=1214/index.html index b356b6f..09919a2 100644 --- a/public/?p=1214/index.html +++ b/public/?p=1214/index.html @@ -7,7 +7,7 @@ The future of patient experience data at Nottinghamshire Healthcare | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1216/index.html b/public/?p=1216/index.html index 92d1448..85297c4 100644 --- a/public/?p=1216/index.html +++ b/public/?p=1216/index.html @@ -7,7 +7,7 @@ A note for Kindle readers of my Shiny book | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1218/index.html b/public/?p=1218/index.html index 37e61ec..905d6f4 100644 --- a/public/?p=1218/index.html +++ b/public/?p=1218/index.html @@ -7,7 +7,7 @@ Python, working together, and productionising code at Nottinghamshire Healthcare NHS Trust | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1222/index.html b/public/?p=1222/index.html index c3f2355..283eaaa 100644 --- a/public/?p=1222/index.html +++ b/public/?p=1222/index.html @@ -7,7 +7,7 @@ The analysts&#8217; manifesto | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1230/index.html b/public/?p=1230/index.html index 95b243a..afd7f8a 100644 --- a/public/?p=1230/index.html +++ b/public/?p=1230/index.html @@ -7,7 +7,7 @@ Add label to shinydashboard | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1242/index.html b/public/?p=1242/index.html index 502613c..75c6d87 100644 --- a/public/?p=1242/index.html +++ b/public/?p=1242/index.html @@ -7,7 +7,7 @@ Authenticating using LDAP from Active Directory using Shiny Server Pro | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1257/index.html b/public/?p=1257/index.html index 1f34fa5..c857d7b 100644 --- a/public/?p=1257/index.html +++ b/public/?p=1257/index.html @@ -7,7 +7,7 @@ NHS-R conference | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1263/index.html b/public/?p=1263/index.html index fd2e835..442ac47 100644 --- a/public/?p=1263/index.html +++ b/public/?p=1263/index.html @@ -7,7 +7,7 @@ My superpower (a talk I gave about being ill) | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1273/index.html b/public/?p=1273/index.html index 2fcf3ab..c9cc20b 100644 --- a/public/?p=1273/index.html +++ b/public/?p=1273/index.html @@ -7,7 +7,7 @@ Decade round up post | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1287/index.html b/public/?p=1287/index.html index ac2a224..f709735 100644 --- a/public/?p=1287/index.html +++ b/public/?p=1287/index.html @@ -7,7 +7,7 @@ Converting words on a survey dataset to numbers for analysis | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1292/index.html b/public/?p=1292/index.html index e9d3f55..5ab75d2 100644 --- a/public/?p=1292/index.html +++ b/public/?p=1292/index.html @@ -7,7 +7,7 @@ Rapidly find the mean of survey questions | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1307/index.html b/public/?p=1307/index.html index 17a0619..bc89c73 100644 --- a/public/?p=1307/index.html +++ b/public/?p=1307/index.html @@ -7,7 +7,7 @@ The Great Survey Munge | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=133/index.html b/public/?p=133/index.html index d11ca2e..17fe6a6 100644 --- a/public/?p=133/index.html +++ b/public/?p=133/index.html @@ -7,7 +7,7 @@ Simulating data | - + @@ -32,7 +32,7 @@ - + @@ -47,8 +47,10 @@ - - + + + + diff --git a/public/?p=1336/index.html b/public/?p=1336/index.html index 32980f3..4636f9b 100644 --- a/public/?p=1336/index.html +++ b/public/?p=1336/index.html @@ -7,7 +7,7 @@ NHS data science and software licensing | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1341/index.html b/public/?p=1341/index.html index 0e6cecb..ab77312 100644 --- a/public/?p=1341/index.html +++ b/public/?p=1341/index.html @@ -7,7 +7,7 @@ Data science for human beings | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1344/index.html b/public/?p=1344/index.html index 863db73..d226250 100644 --- a/public/?p=1344/index.html +++ b/public/?p=1344/index.html @@ -7,7 +7,7 @@ app.R and global.R | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1366/index.html b/public/?p=1366/index.html index 301ca38..27da84e 100644 --- a/public/?p=1366/index.html +++ b/public/?p=1366/index.html @@ -7,7 +7,7 @@ Productionising R at Nottinghamshire Healthcare | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1380/index.html b/public/?p=1380/index.html index 4c4ee20..83f6f54 100644 --- a/public/?p=1380/index.html +++ b/public/?p=1380/index.html @@ -7,7 +7,7 @@ RStudio Connect in the cloud | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/?p=1388/index.html b/public/?p=1388/index.html index c4fcf60..80e6eec 100644 --- a/public/?p=1388/index.html +++ b/public/?p=1388/index.html @@ -7,7 +7,7 @@ RStudio Connect behind the firewall | - 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Getting started in data science for healthcare

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diff --git a/public/index.html b/public/index.html index 18b87b8..431f8db 100644 --- a/public/index.html +++ b/public/index.html @@ -7,7 +7,7 @@ - + @@ -35,11 +35,11 @@ - + - - + + diff --git a/public/index.xml b/public/index.xml index 1c65078..de81c97 100644 --- a/public/index.xml +++ b/public/index.xml @@ -59,149 +59,149 @@ The Goldacre review- greatest hits - https://chrisbeeley.github.io/chris_beeley_blog/?p=1626/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2022-05-22-the-goldacre-review-greatest-hits/ Sun, 22 May 2022 12:18:25 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1626/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2022-05-22-the-goldacre-review-greatest-hits/ I absolutely love the Goldacare review, I really can’t praise it enough, and I will be doing a lot of work based on it in the coming weeks and months looking at it from the perspective of my own Trust and, (with others) from the perspective of my ICS, and NHS-R. In defence of the ordinary - https://chrisbeeley.github.io/chris_beeley_blog/?p=1599/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2022-01-10-in-defence-of-the-ordinary/ Mon, 10 Jan 2022 17:40:24 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1599/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2022-01-10-in-defence-of-the-ordinary/ I think this might be a general cultural problem, but I notice it a lot in my field of healthcare analytics. In defence of looking at jobs - https://chrisbeeley.github.io/chris_beeley_blog/?p=1595/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-12-22-in-defence-of-looking-at-jobs/ Wed, 22 Dec 2021 11:14:41 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1595/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-12-22-in-defence-of-looking-at-jobs/ Nobody should ever have to apologise for looking at jobs, however settled they are. In defence of holiday working - https://chrisbeeley.github.io/chris_beeley_blog/?p=1591/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-12-16-in-defence-of-holiday-working/ Thu, 16 Dec 2021 21:21:14 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1591/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-12-16-in-defence-of-holiday-working/ This might be a little bit controversial, this post. If you hate it please don’t be offended, it’s just my opinion. In defence of eating - https://chrisbeeley.github.io/chris_beeley_blog/?p=1582/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-11-24-in-defence-of-eating/ Wed, 24 Nov 2021 15:07:03 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1582/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-11-24-in-defence-of-eating/ One weird thing in remote/ pandemic times is that people have started turning their cameras off when they eat. In defence of dashboards - https://chrisbeeley.github.io/chris_beeley_blog/?p=1574/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-11-16-in-defence-of-dashboards/ Tue, 16 Nov 2021 22:19:27 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1574/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-11-16-in-defence-of-dashboards/ I’ve had lively debates about dashboards with various people, including someone in my own team, and somebody on Twitter just mentioned that dashboards are often not used (this blog post will be my response to this tweet, not the first time I’ve answered a tweet with a blog and very on brand for me 😉). Make statistics sexy - https://chrisbeeley.github.io/chris_beeley_blog/?p=1570/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-11-13-make-statistics-sexy/ Sat, 13 Nov 2021 23:12:54 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1570/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-11-13-make-statistics-sexy/ I’ve been enjoined to make statistics sexy. It’s really taking root in my brain. Data saves lives- and so does open code - https://chrisbeeley.github.io/chris_beeley_blog/?p=1554/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-09-17-data-saves-lives-and-so-does-open-code/ Fri, 17 Sep 2021 16:56:25 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1554/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-09-17-data-saves-lives-and-so-does-open-code/ I’m reading data saves lives. And look, it’s that thing that I say all the time, that I have pinned on my Twitter profile, the thing I’ve heard time and time again for a decade that everybody just stands around nodding at and nothing actually changes. Pay and reward - https://chrisbeeley.github.io/chris_beeley_blog/?p=1545/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-08-19-pay-and-reward/ Thu, 19 Aug 2021 22:30:25 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1545/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-08-19-pay-and-reward/ I’m reading No Rules Rules, the Netflix management book. It’s really good, lots of interesting stuff in there about doing things differently and although clearly there’s a lot I can’t do in the NHS, there are lessons in there for sure. Graphs > tables - https://chrisbeeley.github.io/chris_beeley_blog/?p=1537/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-07-19-graphs-tables/ Mon, 19 Jul 2021 17:30:17 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1537/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-07-19-graphs-tables/ One phenomenon that I find very strange in the NHS (and elsewhere, probably, I’ve never worked anywhere else) is the obsession people have with having tables of numbers instead of graphs. Stop punishing people with data - https://chrisbeeley.github.io/chris_beeley_blog/?p=1533/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-07-18-stop-punishing-people-with-data/ Sun, 18 Jul 2021 15:28:30 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1533/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-07-18-stop-punishing-people-with-data/ Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes Shoddy data - https://chrisbeeley.github.io/chris_beeley_blog/?p=1530/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-07-14-shoddy-data/ Wed, 14 Jul 2021 16:42:02 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1530/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-07-14-shoddy-data/ You know, naming no names because I’ll get in trouble but someone somewhere has paid for some data from a proprietary vendor and they’re shipping absolutely unusable garbage data. Managing data science teams in the trenches - https://chrisbeeley.github.io/chris_beeley_blog/?p=1517/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-06-01-managing-data-science-teams-in-the-trenches/ Tue, 01 Jun 2021 12:11:00 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1517/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-06-01-managing-data-science-teams-in-the-trenches/ We’re systematically devaluing management and leadership in the analyst space, and I encounter a lot of people who think that a day with no code written is a day wasted. What do we want from senior analysts in the NHS? - https://chrisbeeley.github.io/chris_beeley_blog/?p=1514/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-05-31-what-do-we-want-from-senior-analysts-in-the-nhs/ Mon, 31 May 2021 12:02:03 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1514/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-05-31-what-do-we-want-from-senior-analysts-in-the-nhs/ I’ve been meaning to write this for ages and I’ve just had a rather silly conversation on Twitter about managers and leaders in the NHS which has inspired me to get on with it. SQL versus analytic tools - https://chrisbeeley.github.io/chris_beeley_blog/?p=1495/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-03-26-sql-versus-analytic-tools/ Fri, 26 Mar 2021 10:43:42 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1495/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-03-26-sql-versus-analytic-tools/ From a tweet from my NHS-R buddy John MacKintosh Building generic Shiny applications with a data module - https://chrisbeeley.github.io/chris_beeley_blog/?p=1489/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-02-18-building-generic-shiny-applications-with-a-data-module/ Thu, 18 Feb 2021 16:13:18 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1489/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-02-18-building-generic-shiny-applications-with-a-data-module/ We’re rebuilding our patient experience dashboard at the moment, partly to incorporate some of the work that we’re doing on text mining and partly to connect it up to other types of information we have like staff experience and clinical outcomes. Accessing plot characteristics in Shiny modules - https://chrisbeeley.github.io/chris_beeley_blog/?p=1478/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-01-29-accessing-plot-characteristics-in-shiny-modules/ Fri, 29 Jan 2021 22:47:49 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1478/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2021-01-29-accessing-plot-characteristics-in-shiny-modules/ It was my New Year’s resolution to blog more and that’s going really well because this is the first blog I’ve done all year and it’s nearly the end of January. Serving RStudio Connect content to logged in and anonymous users - https://chrisbeeley.github.io/chris_beeley_blog/?p=1455/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2020-10-19-serving-rstudio-connect-content-to-logged-in-and-anonymous-users/ Mon, 19 Oct 2020 17:16:21 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1455/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2020-10-19-serving-rstudio-connect-content-to-logged-in-and-anonymous-users/ We have our patient feedback dashboard in the open where anyone can see what Nottinghamshire Healthcare NHS Trust’s patients are saying about us. Analyst, analyse thyself - https://chrisbeeley.github.io/chris_beeley_blog/?p=1434/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2020-10-02-analyst-analyse-thyself/ Fri, 02 Oct 2020 09:00:14 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1434/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2020-10-02-analyst-analyse-thyself/ I work in a small (growing) team of data scientists and we’re part of a larger analytic unit which has a focus on innovation in analytics (hence us) and public health methods. Shiny modules for beginners - https://chrisbeeley.github.io/chris_beeley_blog/?p=1411/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2020-08-05-shiny-modules-for-beginners/ Wed, 05 Aug 2020 17:53:38 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1411/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2020-08-05-shiny-modules-for-beginners/ I’ve seen some discussion on the Internet about whether people learning Shiny should start with modules or if they’re an advanced topic. Getting started in data science for healthcare - https://chrisbeeley.github.io/chris_beeley_blog/?p=1395/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2020-07-13-getting-started-in-data-science-for-healthcare/ Mon, 13 Jul 2020 15:55:37 +0000 - https://chrisbeeley.github.io/chris_beeley_blog/?p=1395/ + https://chrisbeeley.github.io/chris_beeley_blog/post/2020-07-13-getting-started-in-data-science-for-healthcare/ I just recruited to a data science post at Nottinghamshire Healthcare NHS Trust and I’ve been asked for feedback by several people about how to get started in data science in healthcare, and indeed how to get a job in data science in healthcare. diff --git a/public/post/2015-09-01-producing-headings-in-word-files-programmatically-using-knitr/index.html b/public/post/2015-09-01-producing-headings-in-word-files-programmatically-using-knitr/index.html index 9c9cfb5..e5f260d 100644 --- a/public/post/2015-09-01-producing-headings-in-word-files-programmatically-using-knitr/index.html +++ b/public/post/2015-09-01-producing-headings-in-word-files-programmatically-using-knitr/index.html @@ -7,7 +7,7 @@ Producing headings in Word files programmatically using knitr | - + @@ -32,7 +32,7 @@ - + @@ -42,8 +42,10 @@ - - + + + + diff --git a/public/post/2020-07-13-getting-started-in-data-science-for-healthcare/index.html b/public/post/2020-07-13-getting-started-in-data-science-for-healthcare/index.html new file mode 100644 index 0000000..9578e37 --- /dev/null +++ b/public/post/2020-07-13-getting-started-in-data-science-for-healthcare/index.html @@ -0,0 +1,174 @@ + + + + + + + Getting started in data science for healthcare | + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Getting started in data science for healthcare

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I just recruited to a data science post at Nottinghamshire Healthcare NHS Trust and I’ve been asked for feedback by several people about how to get started in data science in healthcare, and indeed how to get a job in data science in healthcare. I will also be recruiting another data scientist for our team in a few months. This post is designed to give you a feel for what we were looking for in the job that I just recruited to, as well as to the job that is coming up. They’re slightly different skill sets as I will discuss.

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I should say at the top that I am pretty much a person on the Internet, there are people much better qualified than I am to answer this question, and there are much better jobs out there than the ones I have advertised and will advertise. My trust is a great place to work, and we have a lot of freedom to innovate, and we are big believers in using and publishing open source code. I hope we’re a friendly and supportive team too. But I’m sure there are many out there that do all this and more, and better. With all that said, let’s discuss what I was looking for last time, what I’m looking for next time, and what you can do to get the skills for these or any other similar jobs.

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The recent post I advertised was for a band 7 data scientist, one year contract, starting salary of £38K. It’s for a funded piece of work designing algorithms that can read patient feedback and tell you: what it’s about (parking, food, communication…), how positive or negative it is (you saved my life, this service is a disgrace, the ward was dirty, the food was cold…) and making a dashboard so people can interrogate their data. I don’t want to say too much about it here, otherwise this post will get way too long.

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The first thing to say is that the field was VERY strong. I didn’t think we could get quite as much interest from quite as many talented people as we did. We were definitely spoiled for choice but the areas that ended up being very important were.

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  1. Machine learning. Because it’s a one year project, with a specific goal, we were looking for someone who could just run with a machine learning project and could build a pipeline with real data
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  2. Team working. The ability to help more junior staff, and to work with non technical staff is absolutely vital in such a small team. We were looking for people skills as well as “technical” team working skills- version control, package management, documentation. Avoiding “it works on my machine”, basically
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  3. Communication. Some people are completely on board with data science and trust experts to just get on with it and can engage them about what they want and ask the right questions. And some people will sit with their arms folded (literally or figuratively) and wait to be convinced. And a strong organisation needs both. Cheerleaders and critics. And we were looking for someone who could navigate a meeting with a healthy dose of each, as well as someone who could engage the straight up disengaged
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If you want to get good at this stuff, there are lots of things you can do. This book is excellent if you want to go the Python route. Kaggle is a great resource for datasets and how-to’s. Try to get some real data in your workplace and do some ML with it. Be a mentee. Be a mentor. Work with your team to get better practice around version control and code style. Sell it to your bosses. Even if they’re idiots and don’t listen, it’s all experience. Come to the interview and say that. “I identified several areas of data and analytic practice that could be improved by x, y, and z. I wrote them a five point plan explaining the training their staff would need, the likely benefits and pitfalls. They are idiots and didn’t listen.”

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If you already work in the public sector I highly recommend the data science accelerator. Twelve days, one a week, with a data science mentor. I was a mentee a year and a half ago. Then I was a mentor. Doing one or both is a really good way of getting out of your silo, seeing new datasets and challenges, and learning to ask and answer the right questions. Besides my PhD it’s the best thing I ever did, career wise.

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The next job is going to be a bit more general purpose. The team has quite a few pieces of smaller paid work coming in and I need somebody who can help out as well as work in the Trust building on the work we’re already doing: statistics, machine learning, and publishing either as a document or a Shiny powered dashboard. We’re looking for similar stuff as last time, but not as focused on machine learning, perhaps someone with some stats knowledge- regression, experimental design, measures of association, all that stuff. I feel like R would be a big advantage, but if somebody can do all that in Python then that’s good too, and ditto other things like Julia. They would probably end up learning some R just to read the stuff we’re all writing, and we’d all end up learning Python/ Julia just to read their stuff. All to the good.

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Again, we need someone who can work in a team (no hero coders) and communicate at all levels of the Trust and beyond. We need someone who can teach, and learn, and someone who can convince the sceptical and engage the disengaged. Something I would absolutely love to be able to recruit to is Linux server maintenance experience. I’m in charge of two Linux servers that do our work for us, one in the cloud, one behind the firewall (see this blog, passim) and I would love to be able to give the keys to somebody who knows what they’re doing. Even more, I’d love for them to do the next upgrade. Going to RStudio Connect with Ubuntu 20.04 was hideous (not the fault of RStudio or Ubuntu, obviously, purely my fault 😀) and having someone be able to worry about that would have been wonderful.

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Some people have told me I’m wasting my time managing my own servers as a data scientist and I really need to get proper IT support, and maybe they’re right, but I’ve come this far, even if I am doing it wrong. I’ve been learning Linux server stuff on my own server for 7 years. If you want to learn this way without buying your own cloud server then just buy a Raspberry Pi and ssh into it from behind your firewall at home. Set up a LAMP stack, set up WordPress, set up the free versions of RStudio Server and Shiny Server, run plumber APIs, run PHP, write a Django application, whatever. You’ll get in the most hideous mess and tear your hair out for entire weekends and you’ll look back at those weekends fondly and be glad of all the learning you did that day 😀. And if you get in a complete mess just wipe the SD card and start again.

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As I say, this is all caveat emptor. Your mileage may vary. But if you want my opinions then these are they.

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Shiny modules for beginners

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I’ve seen some discussion on the Internet about whether people learning Shiny should start with modules or if they’re an advanced topic. I’m not going to link to any examples because this post is definitely not me saying- hey look at this rubbish over here, here’s why it’s wrong. I’ve seen a couple of posts talking about it. But I just thought I would chip in my perspective.

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I really love modules and they solve a lot of problems, and I think they could be a great thing for a beginner to learn. No reason at all why beginners can’t learn them. The only caution I would give those learners is that some things can be weird or fiddly with modules. So if you’re learning at your own pace, and want to do everything really neatly and use industry standards, great, go for it. But if you want to throw up a Shiny application to impress your boss (for example) and learn by doing then you may find yourself going down some very long, dark rabbit holes trying to get the particular thing you want working. (and yes, I am writing this post now because I have been down a few myself recently 😀)

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As I say, purely my perspective generated from sitting at my keyboard and interacting regularly with maybe five people learning Shiny. Your mileage may vary

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Analyst, analyse thyself

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+ By chrisbeeley +

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I work in a small (growing) team of data scientists and we’re part of a larger analytic unit which has a focus on innovation in analytics (hence us) and public health methods. We have a pretty broad remit to do interesting and useful stuff and we focus on things that we think are useful (for example, applying data science methods to problems relating to equity of access to services) and things that people ask us to help with.

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I’m getting more and more interested in making sure that we offer a good service to everyone across my Trust and that we work on truly useful projects rather than just stuff that comes to us through the networks of staff that we already know (I’ve worked in my Trust for nearly 20 years so I know quite a few people).

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We’re all resistant to the idea of having a bureaucratic process to decide what we do because quite often we don’t even do that much, we just give a bit of advice and show them some of their own data and they’re off again, so I think what I would like to aim for is transparency. We won’t audit the stuff coming in but we’ll show what comes out and then people can judge for themselves.

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And then I thought “Why am I bothering with all that? Surely this job is about helping people and getting stuff done, not collecting data”. And then I realised a millisecond (as my eldest would say) later that that is exactly what clinicians always say about their data collection! And we make the same arguments back to them that I just made to justify it in the first place. We collect data to make sure that what we are doing is effective and to make sure that it is being distributed fairly and works for everyone.

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This is a long way of saying that we’re now thinking about how to capture our activity and present it in a way that follows all the usual rules of data collection- not burdensome, timely, accurate, transparent, all that stuff. I suppose really we need a system that’s transparent to everyone- our partners in the region and the general public, so hopefully I’ll be back with data (unless I get in trouble for even suggesting such a thing, in which case forget I said anything 😆)

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+ + + + diff --git a/public/post/2020-10-19-serving-rstudio-connect-content-to-logged-in-and-anonymous-users/index.html b/public/post/2020-10-19-serving-rstudio-connect-content-to-logged-in-and-anonymous-users/index.html new file mode 100644 index 0000000..ae33d1b --- /dev/null +++ b/public/post/2020-10-19-serving-rstudio-connect-content-to-logged-in-and-anonymous-users/index.html @@ -0,0 +1,174 @@ + + + + + + + Serving RStudio Connect content to logged in and anonymous users | + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Serving RStudio Connect content to logged in and anonymous users

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+ By chrisbeeley +

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We have our patient feedback dashboard in the open where anyone can see what Nottinghamshire Healthcare NHS Trust’s patients are saying about us. Now I’ve got a Connect licence I thought perhaps I might build another version for our staff where I put stuff that we can’t share- for example the comments of people who click the “I do not wish to share this comment” box.

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But I don’t want to build and maintain two versions, that would be hideous, and I was going to put a litte

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Just publish one and make people authenticate to it, and publish one in the open. Separate apps, separate links, same code. But add somewhere something like

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if(isTruthy(session$user)){

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} else { +FALSE +} +})

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+</div>Success!
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Accessing plot characteristics in Shiny modules

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+ By chrisbeeley +

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It was my New Year’s resolution to blog more and that’s going really well because this is the first blog I’ve done all year and it’s nearly the end of January. Well, I suppose to be fair I did do a post on our team blog but that feels like I’m making excuses.

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Anyway, never mind! This is a quick blog post because this problem I had the other day has, as far as I can tell, absolutely no Google juice at all and it stumped me for ages, even though it is very simple.

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We wanted to access the height of a Shiny plot at runtime but we couldn’t get it to work in a Shiny module. I googled all sorts of stuff, “session$clientData module”, “accessing plot characteristics shiny module”, “session variable shiny module”, all kinds of things, but it just didn’t work. I figured the namespacing was probably messing it up but I couldn’t figure it out. The simple version would have been session$clientData$output_sentiment_plot_upset_width, but I wasn’t surprised that that didn’t work because of the namespacing.

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When I looked at the raw HTML (which I did, in desperation) I saw that the input was actually called “output_mod_sentiment_ui_1-sentiment_plot_upset”. The mod_sentiment bit is the name spacing. So I got pretty close when I tried session$clientData$output_mod_sentiment_ui_1-sentiment_plot_upset_width. But R thought that the hyphen was a minus, so that didn’t work either. Then the light dawned

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session$clientData$`output_mod_sentiment_ui_1-sentiment_plot_upset_width`

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That’s it. Simple, but it took me a while, so hopefully if you have the same problem you will find this post.

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+ + + + diff --git a/public/post/2021-02-18-building-generic-shiny-applications-with-a-data-module/index.html b/public/post/2021-02-18-building-generic-shiny-applications-with-a-data-module/index.html new file mode 100644 index 0000000..ecf6770 --- /dev/null +++ b/public/post/2021-02-18-building-generic-shiny-applications-with-a-data-module/index.html @@ -0,0 +1,176 @@ + + + + + + + Building generic Shiny applications with a data module | + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Building generic Shiny applications with a data module

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+ By chrisbeeley +

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We’re rebuilding our patient experience dashboard at the moment, partly to incorporate some of the work that we’re doing on text mining and partly to connect it up to other types of information we have like staff experience and clinical outcomes. It has to be reusable because we’re using it as the basis of the text mining dashboard that we’re building for any provider trust to use with their friends and family test data. We’re trying to make everything reusable anyway partly because the different bits of the NHS should all cooperate and produce stuff together that everyone can use and partly because we’re realising that when you make code reusable the first person who can reuse it is you, 6 months later on a similar project.
+So we have a patient experience dashboard that we want to hook up to our other data in our own context, and we have other trusts who want to take what we produce and hook their stuff in to it. An obvious approach is to use modules in Shiny and have a data module at the heart of the operation, which can take account of the different datasets available in each context. The next level would be a “summary type” module which would bring together all of the inputs and outputs for a particular type of data- one for patient experience, one for staff experience, etc. And the bottom level would be submodules which would carry out the individual tasks- one module to produce graphical summaries, one to produce downloadable reports, etc. We would use the {golem} package for all the reasons that we normally use {golem} (help with dependencies, packaging, testing, and deployment)
+The basic structure would look like this:

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  • Data module. This module would be responsible for loading ALL data, patient experience data and any other datasets that the person deploying the application might want- clinical outcomes, staff experience, whatever it might be. This module would contain upload and download features as appropriate (users may wish to upload their own data or download processed data) but it would in the main merely draw from databases, process the data into a useful form, and prepare them to be imported into the other modules
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  • Function module. Each of these modules is responsible for a particular type of data (staff, patient, clinical outcome). In some trusts the dashboard wouldn’t have access to data of all of the necessary types and these modules would not show in these contexts.
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  • Sub modules. Each function module would have access to submodules which do different tasks- draw graphs, make reports, etc. Because some types of data are quite similar (e.g. staff and patient experience data) there is potential to reuse these modules in some areas.
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Although this is a nice approach there are lots of different ways of achieving this and I’m hoping for a bit of guidance as to which might work best.

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  1. “Automatic dictator” data module. This would be a data module that works with no instruction from the person deploying the application and which instructs all the other modules. This data module would simply attempt to load all of the data, catch any errors that result in doing so, report them to the user (in an unobtrusive format- “No staff data found”) and then instruct which of the function modules should appear. Further, it would export not only dataframes but also a set of instructions to the function modules as to how to carry out their processing. For example, there may be just one or several free text questions in a patient experience function module. The data module would determine that and would export with the dataframe a description of the dataset for the use of each function module
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  2. “Automatic” data module. As above, except it would not export instructions, but just data. Function modules would be responsible for understanding the shape of the data and would instruct their submodules accordingly.
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  3. “Programmable” data module. This data module would accept a list of options within the run_app() function and would therefore be set up individually within each trust. For example, the run_app() function might be passed list(patient_experience = c(TRUE, 2, 5), staff_experience = c(FALSE)), indicating to draw the patient experience function module with 2 free text questions and 5 Likert-type questions, and to omit staff experience. In practice the options list would need to be longer, but this is just to illustrate the principle. The data module would load and process the data according to the arguments in run_app(). It could then either instruct the function modules as in the dictator data module or leave it up to them as in the automatic dictator module.
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  4. “Dumb” data module. This data module would be dumb. It would just load the data, process, and export it to the other modules. The function modules would be expected to react intelligently to the presence or absence of data and to make sense of the structure of the data. I don’t think this example would work well because there would be nothing to turn off the function modules, which mean there would be blank tabs in the application, but I’m including it for the sake of completeness in case it gives me or anyone else an idea at a later stage.
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Most of the options, except 4, are pretty similar, but they have a lot of scope to change the overall way that the application is programmed. Leaving stuff up to the function modules is probably more flexible but it may be that all the function modules need tweaks in different trusts, which is not really what we want. Having an automatic dictator model is very attractive in that you should just be able to seal the whole thing and deploy it anywhere but the reduced flexibility inherent in that approach may make it more difficult to actually get it working in different contexts. In practice some of it is probably a bit of a grey area anyway- I don’t think you could have a completely dumb data module, and nor could you have a completely dumb function module. Even the submodules will have various degrees of “dumb”. It’s more about getting an idea of where you build the flexibility and how much control you give each module over its behaviour.
+I’ve written this blog post to show it to one person whom I will now ask politely on Twitter for their opinion but if anybody else has any thoughts I would be very glad to hear them. It’s better to tweet @chrisbeeley because I don’t seem to get email notifications from blog comments for some reason.

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SQL versus analytic tools

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+ By chrisbeeley +

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From a tweet from my NHS-R buddy John MacKintosh

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“Two schools of thought :
+1. Do as much as possible using SQL (joins/ munging/ calculations and analysis) so that your analysis is portable between different BI / Viz tools
+2. Do the basics (e.g. joins and simple aggregates) in SQL, calcs and analysis in front end tools”

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This is a great question, and I don’t mean to detract from its greatness when I say it is over simplistic. It’s an important question, and I have a lot to say on the subject, so much so in fact that I’m going to answer a tweet with a blog, which is very on brand for me 😄.When we think of data scientists and data engineers, we tend to think of data engineers providing beautifully normal and rapid data structures and data scientists wrangling them with a mix of SQL and R/ Python/ whatever. But in my experience it doesn’t really work cleanly that way, and nor should it.

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An important factor is the way that the data is organised and documented. People in the NHS often get upset about all the different datasets that we use. A common complaint is that they don’t link up easily. People who don’t work in data think that the Trust has this big database of everything, and you just go and look up the thing you’re interested in, and it’s right there indexed against every other piece of data, and off you go. This notion is hilarious to anyone to anybody who actually works with data.

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It’s not because the data is bad or because it’s not being looked after properly. It seems to me that databases, far from being perfect platonic ideas about the trust are in fact opinionated. You tend to find that they do the thing that they were originally designed to do very well. The payroll database is really good at paying people. The EHR is really good at, well, being an EHR. Data scientists, by our very nature, always want to do something that the database was not designed to do. That almost seems to me to be an actual definition of data science. Taking a database and making it do something else. If your database has already done what you’re doing, chances are you don’t need a data scientist. Just stick one of those auto ML things on it or point PowerBI at the cube. Boom. Instant insight.

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So what does this all mean for the question? It means that the data engineers and data scientists are on the same team. They’re not just throwing stuff over the wall at each other. The data scientists are customers of the data engineers, and we couldn’t do a thing without them, but we can be smart customers. We might want the data in a different form, sure. We might prefer it if some of the joins were done in the backend to save us a bit of work and to help us all work together. But we can give stuff back. We might use an algorithm to predict the risk of rehospitalisation at 28 days, say. Once we’ve done that we can probably use that calculated value more quickly if it’s productionised in the DB. And if it is productionised in the DB that means everyone can access it- not just the data scientists but also the data engineers and all of their customers.

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Data scientists and data engineers working together can take a database that does one thing and turn it into a database that does two things. And they can turn that database into something that does three things. And the whole time the data engineers are keeping it all fast, scalable, legible, and accurate. It’s early days for us, working this way. I’ve read about it many times, but we’re working with our friends in data engineering and I hope one day to tell our story and how we’ve all worked together to produce lots of insights and delivered them all around the Trust.

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To answer the question, then, I would say that if you want to go fast, use analytic based tools, and if you want to go together take the time to port all of the insight to SQL based tools. And given the state of analytics in the NHS as it stands today I would recommend we all go as fast and as together as possible. I know we at Nottinghamshire Healthcare are.

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+ + + + diff --git a/public/post/2021-05-31-what-do-we-want-from-senior-analysts-in-the-nhs/index.html b/public/post/2021-05-31-what-do-we-want-from-senior-analysts-in-the-nhs/index.html new file mode 100644 index 0000000..0536123 --- /dev/null +++ b/public/post/2021-05-31-what-do-we-want-from-senior-analysts-in-the-nhs/index.html @@ -0,0 +1,167 @@ + + + + + + + What do we want from senior analysts in the NHS? | + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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What do we want from senior analysts in the NHS?

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+ By chrisbeeley +

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I’ve been meaning to write this for ages and I’ve just had a rather silly conversation on Twitter about managers and leaders in the NHS which has inspired me to get on with it. I think most people are agreed that we have A Problem with mangers and leaders in the analytic space. Much ink has been spilled in the subject, and I think that the two main conclusions of all this ink are broadly accepted by everyone. They are, briefly:

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1: Managers often lack the analytical training and experience to critically engage with the data and analyses with which they are presented (or indeed, to do analyses well themselves) and this leads to decision by anecdote and hunch.

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2: Analysts lack a clear career track that rewards them for developing their analytic skills rather than for their becoming managers, unlike, say, surgeons, who can be very successful by just being very good surgeons and aren’t expected to become managers (although there’s a bit of nuance even in there that I’m getting to so stick with me if you’re thinking I’m talking rubbish already)

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I’m not really going to talk about point number one except to say that in my view part of the solution to this problem is to have analysts in more senior positions, including at board, and by that I mean actual analysts, not managers of analysts. Many people with much more knowledge and experience (and credibility) than me have said this already, so you didn’t really come here to read that. All this does relate to point number two, however, which I will talk about now.

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Having advanced some way in my career as an analyst, I can say that my experience absolutely fits with the general point that people make about analyst careers. Quite honestly, there wasn’t really a career structure that I fitted into when I finished my PhD in 2009, and I’ve sorted of bobbed around doing different stuff. I’ve never looked at job and thought “That’s the job for me, I’m applying for that”. I’ve pretty much just made it up as I went along.

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The thing I’m not sure about, however, is this idea that we need to reward analysts just for their analytical skills. Sometimes when I talk to people about this I get the idea that they’re promoting the idea that we’ll have these Python geniuses just sitting in a box doing linear algebra and deep learning and advancing up the career track like that. To me I think that misunderstands what we want from analysts in the NHS. I believe the likes of Google and Facebook do pay some very, very clever people to just work on really high end statistical and computational tasks, and they use the methods that these people are producing to increase revenue. I think we in the NHS look at that and we imagine that we can make that work for us. But the NHS is not Google, and most analytical teams are far too small to support an individual working that way. There may be scope to employ people in that capacity in the national bodies, which are much larger. I don’t claim to know much about that. But speaking as someone who works in a provider trust and who has worked with people all over the country in trusts and CCGs, I’m pretty confident in my belief that we actually want to reward people to do other stuff than just clever Python and machine learning.

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We do want to employ people with high end technical skills. Source control. Statistics. Machine learning. But once they’re good at that stuff we want more from them. I don’t want them sitting in a box writing code all day. That is a much too narrow definition of working effectively. They need to be training. Mentoring. Doing high level design. Understanding the local, regional, and national landscape. Writing and winning funding applications. Even if they’re not line managing anybody they need to be aware of what more junior colleagues are doing, helping them prioritise and understand their work, and managing projects so they’re delivered on time and to spec.

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And therein lies the heart of what I consider to be the mythology around this issue. This stuff is hard. Universities are churning out people who can write Python for data science at a rate of knots now. We’ve got it the wrong way round. Yes, those people at Google are terribly clever, and I couldn’t do what they do in a thousand years. But this stuff is hard too. Teamwork. Mentoring. Communication. Understanding what to do where, with whom, and how. These skills are incredibly valuable. Recruit to and reward technical skills, by all means. But ask yourself if you want more from your team members.

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Managing data science teams in the trenches

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+ By chrisbeeley +

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We’re systematically devaluing management and leadership in the analyst space, and I encounter a lot of people who think that a day with no code written is a day wasted. I do write code, but I do a lot of other valuable stuff too. I’ve written this post as someone who is very new to managing people with my personal opinion, so just like my posts on proxied SSL with Apache, there is your caveat emptor 🙂

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The people I manage like to get in the zone and write code. I think of it as like they’re digging a trench. They’re not getting out of the trench, they’re not sticking their head out, they’re just digging. And it’s efficient, they’re digging fast, and it’s rewarding too. They’re working on interesting problems and solving them and it feels good. My job is just to stick my head in the trench occasionally.

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“What are you digging there? Oh yes, I like it, nice. You know, you could use that other tool over there on that bit. And actually, have you thought about trying this other technique? Let me show you, pass me the chisel. Okay, great. Let me know if you get stuck”

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next trench… “Hey, that looks good, what is it? I like this trench, I like this bit. You know, you’re actually going the wrong way, though, you’ve gone off at an angle. Come up here and I’ll show you. See that trench over there? We’re trying to get there. Just jump back in and I’ll help you get it pointing in the right direction”

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next trench… “Hey, this trench is taking ages, isn’t it?! We need to finish it soon, really. I think we maybe need to not finish some bits of it for now. Which are the really important bits, do you think? Okay, let’s keep this bit. This other bit, I know you love it, and I love it too. It’s really clever what you’ve done. But we can’t ship on time with it. I think we need to come back to it later, or maybe just chalk it up to experience and maybe we can do it next time”

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This is pretty basic stuff, really. It feels a bit silly to have to spell it out. The point I’m trying to make is that the people getting in the trench occasionally are helping the people in the trench stay in the trench and that’s good for them and good for the project. And that’s my test for all the stuff that we do. Code review. Standup. Appraisals. Hack days. Overall, is it helping them stay in the trench, digging quickly and solving problems, or is it just a silly distraction?

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I’ve never in my life had a manager who has the slightest idea what autoregression is or how to test the assumptions of OLS regression. I’m really happy now that I do manage people and that I do know what those things are, and I hope the people I manage can benefit from my understanding of what they’re doing (even if they usually know way more about it than I do- I can at least keep up if they explain it to me).

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(if you’ve read my previous post and you’re paying attention you’ll realise that I’ve just contradicted myself by saying firstly that analysts should do more than just write code all day, and then said in this post that a manager’s job is to help analysts write code all day. Forgive me. In reality the people in the trench have got other people in the trench, or possibly in a neighbouring trench, and it’s their job to stick their head in that trench and help that person write code instead of needing to get out of their trench, before coming back to their own trench. Indeed, really, the trench visitor is in fact in their own trench, and someone else sticks their head in there occasionally, but the analogy gets a bit convoluted and silly at this point. I think you get the idea, even if it doesn’t translate to actual trenches within trenches within trenches)

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Shoddy data

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+ By chrisbeeley +

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You know, naming no names because I’ll get in trouble but someone somewhere has paid for some data from a proprietary vendor and they’re shipping absolutely unusable garbage data.

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They won’t fix it because “no-one else has complained”.

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HAVE SOME PRIDE IN WHAT YOU’RE DOING. How about that? How about fixing it because it’s an embarrassment? I’m a random idiot in some random NHS Trust in the countryside and I couldn’t sleep if my database looked like what you’re sending.

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I swear on my life the NHS could do 99% of this stuff better itself if we just dug in and had a go. Everyone’s in thrall to these people with expensive watches and glossy brochures but it’s all a confidence trick.

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Stop punishing people with data

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+ By chrisbeeley +

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Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes

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It was then popularised by Strathern as

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When a measure becomes a target, it ceases to be a good measure

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So far, so ordinary. What else do we all know? League tables are a bad idea too. Somewhat related to Goodhart’s law, the problem with league tables is that they often ignore nuance. “Bad” schools aren’t bad, they just have an intake that starts way behind. “Bad” surgeons aren’t bad, they just take on the more complex cases or work in a geographical location where there are more complex cases. There are ways of trying to balance out this bias, “value added” in the case of schools (being married to a teacher, I hear a lot about this one), and case mix adjustment in the case of surgeons. Although these methods go some way to ironing out problems there is always the chance that an unmeasured variable is affecting the results and distorting the picture.

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In my own area of work, patient experience data, league tables are a terrible idea because the services are all so different and they serve so many different people. Older people are, on average, more satisfied with healthcare. People who are detained under the mental health act for what can be 10 years are, unsurprisingly, often less positive about their healthcare.

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I would like to add another law of data to the canon.

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The more data is used as a punishment the less engaged those it punishes will be with all data

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I’ve read so many beautifully written and persuasive arguments about the power of data, all, naturally enough, written by True Believers. People who can see how data can be used to inform service delivery and planning. If I’m honest I think I live in an echo chamber, filled with analysts and technical types, all passionate about the insights data can generate. But sadly the reality outside my little bubble is that mostly people have data done “to” them. Every quarter a manager or public body drops out of the sky and asks them for all these numbers.

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They’re punished if the numbers are late. They’re punished if the numbers are wrong

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And they’re punished if the numbers don’t show them in a good light even if everybody knows there’s a perfectly good explanation as to why the data looks like that (thinking back to value added and case mix adjustment above).

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They get it all done, feeling harried and that the way the data is collected and scrutinised is unfair and makes their team/ department look bad, they cross their fingers and pray that it doesn’t come back with red pen on it three days later, and then they forget about it for another quarter.

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And the really sad thing is that these people have questions that could be answered with data. Everybody makes suppositions and hypotheses all the time, it’s impossible not to, and with help and understanding they could refine their ideas and be more effective at their job.

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But data has crashed through their window like a rabid dog and made a mess of the place and it never occurs to them to take that same dog to the park to see if it can help them find the jacket they left there last week

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They’re just glad to close the door and lock it and forget about the whole ordeal until the next quarter.

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I think we do need to keep promoting the value of data and analytics, and I obviously spend a decent chunk of my time either selling people that dream or (more often) fighting Python dependencies on a server to make that dream a reality.

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But I think it’s just as important to stop beating people with data, to try to work with them to understand why their numbers look the way they do, and to try to make all processes that involve data more to do with learning and less to do with punishing people with an unfair analysis of what really goes on in their department.

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Graphs > tables

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+ By chrisbeeley +

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One phenomenon that I find very strange in the NHS (and elsewhere, probably, I’ve never worked anywhere else) is the obsession people have with having tables of numbers instead of graphs. I have encountered this absolutely everywhere. People really want to know whether something is 21.4% of the whole or 19.2% of the whole and they can’t tell by looking at the beautiful graph that you’ve drawn.

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I saw an analysis today which had nine separate tables of proportions. I’m going to go out on a limb and say no human being can understand a thing of such complexity. Nine tables, each with three categories, 27 proportions given. You could fit the whole thing on one graph and it would be readily apparent how they compare with each other.

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But no, people want to know is it 13% or 15%, even though in almost all cases the amount of precision far exceeds the confidence levels of the sample.

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Your report needs to say “category A is found twice as often as C, whereas A and B are similar”. Not “category A is found 17.6% of the time, whereas C is found 9.2% of the time- on the other hand category B is found 19.5% of the time”. Just writing it is exhausting me, never mind trying to understand it from cold in a meeting.

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There are of course rare exceptions to this rule, sometimes you really need to know that something is 13.5% of the whole. But you should be asking yourself more questions- how reliable is the measure? What is the sampling error associated with this estimate? Otherwise your 13.5% is 14.6% is 12.3%. And who is usually saying this, if anyone-me!

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Pay and reward

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+ By chrisbeeley +

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I’m reading No Rules Rules, the Netflix management book. It’s really good, lots of interesting stuff in there about doing things differently and although clearly there’s a lot I can’t do in the NHS, there are lessons in there for sure.

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I’ve just read the bit about paying people top of market rate and I’m so happy because it describes loads of people who are on $250,000, crazy money, moping around and leaving because they can get a 40% pay rise somewhere else.

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How does 40% on top of $0.25m make you any happier? It’s a nonsense. But the people I work with and recruit don’t chop and change for money. They do what they do because it’s meaningful, and because they believe in the founding principles of the NHS.

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So although I can’t pay top of market I don’t need to, either. I just need to ask people to do useful stuff, in the open, for everyone, and to do it their way with whatever support they need. And pay them properly, of course.

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That I can do ❤️

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That is, in fact, my jam 🎸🎸🎸

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Data saves lives- and so does open code

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+ By chrisbeeley +

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I’m reading data saves lives. And look, it’s that thing that I say all the time, that I have pinned on my Twitter profile, the thing I’ve heard time and time again for a decade that everybody just stands around nodding at and nothing actually changes. I quote:

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“Working in the open

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Public services are built with public money, and so the code they are based on should be made available for digital pioneers across the health and care system, and those working with it, to reuse and build on.

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Analysts should be encouraged to think from the outset of a project about how work can be shared, or consider ‘coding in the open’ for example, through use of open notebook science. This will include sharing of technical skills and domain knowledge through sites like Cross Validated and StackOverFlow, and sharing code and methodology through platforms like GitHub, will build high quality analytics throughout the system

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Our commitments:

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My team does this, proudly. Does yours?

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Make statistics sexy

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+ By chrisbeeley +

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I’ve been enjoined to make statistics sexy. It’s really taking root in my brain.There are no easy answers in statistics; it’s a long, hard road. It’s rigorous, and honest, and that’s why I love it. Frank Harrell’s talk at NHS-R typified this. The price of truth can be very high- like binning all the data from your £1m study instead of doing what many do which is slice it into so many pieces that something looks shiny and publishing that.

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At the same time there’s a lot of hype in ML and AI. There are serious minded people doing ML properly and making a real difference but there are also a lot of private companies selling the NHS snake oil in a new, fancy bottle and giving them overfit, janky, ungeneralisable models or even just selling them a pile of promises and a dashboard and leaving them with nothing.

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How can the “I think you’ll find it’s more complicated than that” brigade compete with the “Our data science team showed that this model increased patient flow by 17%” (but please don’t ask us about pre-existing trend, or the Hawthorne effect, or the other 8 models they deployed that didn’t do much at all).

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I truly have no idea, but I’m going to have a good go at finding out. Rest assured if I discover the answer I shall write it here first 😃

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In defence of dashboards

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I’ve had lively debates about dashboards with various people, including someone in my own team, and somebody on Twitter just mentioned that dashboards are often not used (this blog post will be my response to this tweet, not the first time I’ve answered a tweet with a blog and very on brand for me 😉).

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I should acknowledge at the top that I’m The Dashboard Guy. I’ve written books about making dashboards in R. It’s my role in the data science team in which I sit. Shiny in production. It’s my thing. So take all this with as much salt as you wish, I promise I won’t be offended.

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People say that dashboards proliferate, and that nobody uses them. That is quite true in a lot of cases. I’d like to suggest why that is so, and talk about when people do use them.

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The first thing to say is that in the NHS (which is where I have always and will always work) many staff are not engaged with data in general. They’re not engaged with data, they’re not engaged with analysis, they’re not engaged with reports, they’re just not engaged. They see data as a punishment, a “test” they cannot win. They can’t see the point of it and it’s just a distraction at best and over-critical and unfair at worst.

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So my first question would be what do you replace the dashboards with? What will they engage with? I became The Dashboard Guy because we used to make a 300 page report by hand every quarter. It took literal person weeks and every recipient was only interested in their four page chunk. It was ridiculously inefficient. But everybody did want their four page chunk. Dashboards are useful for data that people want to see.

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The team and I have recently built a classification algorithm for free text patient experience data. There is no way on earth anybody could use that without a dashboard because there are thousands of points of data and you are typically only interested in a few hundred at a time. So we built one. If they are using the algorithm at all, they’re using the dashboard (or someone else’s, it’s open source so you can DIY the dashboard if you want). If they’re not, that means they’re not looking at what their patient experience data is about, or they’re reading a 4000 row spreadsheet (and I do know people who have done/ are doing that).

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So I think dashboards are very useful when you have a large highly structured dataset where everyone wants their own bit, and I’ve deployed perhaps three or four that have certainly been used by the individuals who wanted that data.

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But something else that I think they can be used for is putting data science tools in the hands of your users. I just built a dashboard that allows you to pick how many LDA topics you want to use, and then shows you:

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(I should say, it’s very rough and unfinished, but you get the idea). The idea of this is to allow the person who is interested in the data to make the topic model work themselves without writing R code. In this particular project all the data hasn’t come in yet anyway so the dashboard will contain more data in the future. It may be that the first tranche of data contains four topics, and the final dataset six. Building a dashboard makes the enduser part of that decision making process.

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In fact, I actually build them for myself. A few years ago I was fitting a lot of structured topic models and it was such a pain in the neck fiddling around with the code that I just made a dashboard for myself so I could just sit and play around with it. The analysis itself took days, tens of hours, and the dashboard took an afternoon (to be fair, I’m probably a little faster than the average person with Shiny at least, because I have a lot of experience with it).

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If your users are not using your dashboards, ask yourself why that is so. If they aren’t engaged with data or don’t care about the metrics then you have a bigger problem than dashboards. Would they engage with a report? An email? A bullet point in a team meeting? Build what they want, not what you think they want or should want.

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Dashboards give you an opportunity to devolve analysis to your users. I work with a lot of text data. The users are the experts, not me. I want them to be able to do all the stuff I do in code but in a browser- sort, filter, summarise, aggregate, and even tune models (do they want five topics or fifteen? Do they want an overinclusive multilabel classification algorithm that captures all of a theme, or a conservative one that only shows them the highlights?).

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In my opinion the dashboard is the icing on the cake. The team and I are building a very large, complex dashboard summarising many types of data, in the hope of driving customers between the types (patient experience data users looking at staff sickness levels, clinical effectiveness data users looking at all-cause mortality). But the work is in uniting the data, in producing analytics that are meaningful and useful. I don’t think it’s terribly important whether it’s a dashboard or a report or just played over the PA every Monday morning (there’s an idea 😉). Engage people in data and analytics first, and then serve that need using all the tools at your disposal.

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In defence of eating

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One weird thing in remote/ pandemic times is that people have started turning their cameras off when they eat. I’m all for the right to turn your camera off, I think you should be able to do that at any time without giving a reason, but I think it’s a shame if people think that they can’t eat on camera. I have therefore been glad to eat several large, difficult to eat things in meetings on camera recently, to perhaps give others the idea that it’s okay if they want to do it too.

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So far I’ve eaten a footlong Subway which was kind of falling apart really and today it was half of a pretty massive pizza which was also a bit lacking in the structural integrity stakes. So please join me if you wish, we all used to eat in front of each other in The Before Times, it’s totally natural and normal- but also if you don’t want your camera on because you’re eating or for any other reason that’s okay too.

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In defence of holiday working

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This might be a little bit controversial, this post. If you hate it please don’t be offended, it’s just my opinion. Totally open to being completely wrong always, especially here.

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I’ve heard a lot of people talk about the importance of taking your leave, and encouraging your staff to take your leave, and I do think it’s super important to take leave, and I certainly think if you’re managing someone you should definitely encourage them to take their leave. There is more to life than work, and having your leave can even make you better at your job when you get back, so it’s win-win, you benefit and your job benefits.

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However, I’ve had people tell me that it’s wrong that I sometimes work in my leave, because I’m setting a bad example to my staff. This I don’t agree with. Particularly now during COVID but really for the last decade my life has been limited by health problems (primary sclerosing cholangitis, chronic ulcerative colitis, and now hepatic arterial stenosis, but that’s another blog post) and my job has become something I can do that I love that I’m good at, replacing some of the other stuff I used to do (aikido and running, mainly). I’ve been isolating from my whole house on and off since March 2020 and my job really keeps me sane.

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So although I may manage people I’m also a human being with my own emotional needs, and I choose to work sometimes in holidays and weekends because it makes me feel good to work and be productive. My whole team completely recognise my position and don’t at all feel any pressure to do likewise.

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So I don’t agree with that. The other thing that I don’t agree with that I see sometimes is the idea that we should view others in our team or whom we manage working in the holidays as something “bad” that we need to “save” them from. The best boss I ever had was absolutely brilliant at taking leave. He would work 50+ hours a week and then in the holidays he would just disappear completely. No phone calls, no email, nothing. It was like he didn’t exist. And that was great, and I think it’s a really good example of doing something that works for you (ignoring the 50+ hours, not really advocating that, but he did work hard, put it that way).

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But just like me I think some people blend their work in a bit more. They like to tickle their brain a bit in their holidays, maybe write some code that’s been bugging them, do a bit of reading, or write a blog post (writing blog posts absolutely should be part of your paid hours). It avoids the cliff edge stress of the last day before your holiday, because you can think “never mind, I’ll just knock that out in the middle of next week and email it over”. And if you then take a bit of time back for yourself in your core hours, that’s all good too. Because that’s one thing I am good at. I may work funny hours and at the weekend and in my leave but if I feel like having a three hour lunch break with a friend and nobody will miss me I do it without hesitation or guilt and that works really well for me.

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So that’s it. I’m not saying “everyone should work in the holidays”, or even “you should try working in your leave, it’s great”. But I am saying that everyone is different, and some people like to blend their work and home lives together for lots of good reasons. As always, what’s important is understanding the needs of the people around us and respecting their autonomy and not coming up with social media friendly soundbites about what you should and shouldn’t do with your self or your team.

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In defence of looking at jobs

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Nobody should ever have to apologise for looking at jobs, however settled they are. Looking at jobs just means one of:

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Any manager that doesn’t like that is a fool, a charlatan, a psychopath, or all three, and then you can add:

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5. My line manager is a fool, charlatan, or a psychopath (or all three), and I am trying to leave my current job as fast as possible now I have realised this

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In defence of the ordinary

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+ By chrisbeeley +

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I think this might be a general cultural problem, but I notice it a lot in my field of healthcare analytics. There are lots of “case studies” and “pathfinders”, that kind of thing, groups of people who are doing amazing stuff.

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I don’t think that it has the desired effect though. People look at these groups doing incredibly complicated things with new tools and they think it just doesn’t apply to them. Let the pathfinders pathfind and we’ll just churn out some rubbish in Excel, same as last week.

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I wonder if we’d be better off setting the bottom higher, rather than raising the bar at the top again. Instead of showing off amazing teams, showcase a solid team getting the basics right, week in, week out. And try to pose the question “If you’re not doing this stuff, why not?”

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The Goldacre review- greatest hits

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I absolutely love the Goldacare review, I really can’t praise it enough, and I will be doing a lot of work based on it in the coming weeks and months looking at it from the perspective of my own Trust and, (with others) from the perspective of my ICS, and NHS-R. NHS-R has a couple of repos looking at matters related to the review (statement on tools and NHS-R vision) and we need to do some thinking about stuff that particularly comes out of this review that we can look at (which I have started doing on my own, community effort will follow).

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Anyway, that’s all for the future. This blog post is just going to be very simple and just be Stuff I Particularly Love. As I’m reading it I occasionally find a bit which really resonates, and I thought it would be useful for me and possibly for others to record them as a kind of “Greatest Hits” outside of all of the other stuff I’m doing digesting it.

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The Goldacare review is a blueprint for change, without doubt, that’s partly why I love it so much, and I intend to be that change and to push it forwards, but in the meantime this is just a bit of fun looking at all the best bits

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Make it ‘okay to ask’ about access to publicly funded code

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“The team heard from several interviewees that at present it is commonly regarded as provocative to ask for access to the code used to implement an analysis, especially in some parts of the academic community, despite general positive statements on open working”

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I absolutely love this. I think it is regarded as being provocative sometimes, and people can get quite defensive. Very often people assure me that the code is forthcoming but it never is. It will surprise nobody to hear that I ask for code whether it’s provocative or not, and so should you. If it’s public money, it’s public code, and I’m sorry if that makes you uncomfortable but I’m going to put my hand up at the end and ask. Every. Single. Time. So get used to it

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Pseudo-open working

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“As a consequence of growing support for open working, there are now individuals and organisations who state that they support open methods, but do not do so; or create only the appearance of open working. During this review the team encountered examples of very senior and influential leaders extolling the virtues of open working, where their published papers from the pandemic in 2021 do not contain code, and require that interested parties contact them personally to negotiate access to the data dictionary codelists used to define the variables used in the analysis”

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I almost whooped with delight when I read this. I’ve encountered this so many times and it makes me feel very cross. I hear so many warm words, and I see so many people extolling the virtues of openness, but very often it’s just a sham. They’ve no intention of sharing anything and they wouldn’t know an open licence if it bit them. I have more respect for the naysayers, at least they’re honest.

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That will do for this post. I’m sure there will be more, and I’ll add more posts as I go.

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+ + + + diff --git a/public/post/2022-05-29-the-prevalence-of-code-sharing-goldacre/index.html b/public/post/2022-05-29-the-prevalence-of-code-sharing-goldacre/index.html index 3a374ed..80e4bc7 100644 --- a/public/post/2022-05-29-the-prevalence-of-code-sharing-goldacre/index.html +++ b/public/post/2022-05-29-the-prevalence-of-code-sharing-goldacre/index.html @@ -7,7 +7,7 @@ The prevalence of code sharing (Goldacre) | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/post/2022-06-16-we-need-more-than-black-box-systems-goldacre/index.html b/public/post/2022-06-16-we-need-more-than-black-box-systems-goldacre/index.html index d586ace..760069c 100644 --- a/public/post/2022-06-16-we-need-more-than-black-box-systems-goldacre/index.html +++ b/public/post/2022-06-16-we-need-more-than-black-box-systems-goldacre/index.html @@ -7,7 +7,7 @@ We need more than "black box"; systems (Goldacre) | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/post/2022-06-23-data-science-for-dummies-goldacre/index.html b/public/post/2022-06-23-data-science-for-dummies-goldacre/index.html index 97f95f1..ebce211 100644 --- a/public/post/2022-06-23-data-science-for-dummies-goldacre/index.html +++ b/public/post/2022-06-23-data-science-for-dummies-goldacre/index.html @@ -7,7 +7,7 @@ Data science for dummies (Goldacre) | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/post/2022-08-23-rap-a-10-year-journey/index.html b/public/post/2022-08-23-rap-a-10-year-journey/index.html index 91327e1..011cd9f 100644 --- a/public/post/2022-08-23-rap-a-10-year-journey/index.html +++ b/public/post/2022-08-23-rap-a-10-year-journey/index.html @@ -7,7 +7,7 @@ RAP; a 10 year journey | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/post/2023-02-14-data-science-panel-questions/index.html b/public/post/2023-02-14-data-science-panel-questions/index.html index 89613d8..0137b26 100644 --- a/public/post/2023-02-14-data-science-panel-questions/index.html +++ b/public/post/2023-02-14-data-science-panel-questions/index.html @@ -7,7 +7,7 @@ Data science panel questions | - + @@ -32,7 +32,7 @@ - + @@ -43,8 +43,10 @@ - - + + + + diff --git a/public/post/2024-03-25-new-year-new-blog/index.html b/public/post/2024-03-25-new-year-new-blog/index.html index ecb4eda..1a92f4a 100644 --- a/public/post/2024-03-25-new-year-new-blog/index.html +++ b/public/post/2024-03-25-new-year-new-blog/index.html @@ -7,7 +7,7 @@ New Job New Blog | - + @@ -32,7 +32,7 @@ - + @@ -42,8 +42,10 @@ - - + + + + diff --git a/public/post/2024-05-04-decisions-decisions/index.html b/public/post/2024-05-04-decisions-decisions/index.html index cfbd183..38420fb 100644 --- a/public/post/2024-05-04-decisions-decisions/index.html +++ b/public/post/2024-05-04-decisions-decisions/index.html @@ -7,7 +7,7 @@ Decisions Decisions | - + @@ -32,18 +32,20 @@ - + - + - - + + + + @@ -120,7 +122,7 @@

Decisions Decisions

This one is, like the last one, about something that made me more uncomfortable the further I got into it. I think it’s fair to say that most analysts in the NHS feel like they are not being heard, and they often feel like they don’t have autonomy over what they learn and do. I’ve been lucky to have been supported by line managers who’ve given me the freedom to explore and do new things, but I know many are not. Despite the support I have received from my managers in the past (and present) I still think it’s fair to say that analysts are not the most influential of NHS staff and are indeed sometimes marginalised and ignored.

The general feeling for an analyst as they come up the ranks, I would say, is feeling like you have some knowledge to contribute but not feeling like that knowledge is welcomed and accepted from those around. I now find myself in the exact opposite situation and am now being listened to not only when I talk about stuff I know about (my slowly ageing knowledge of data science) but also things I don’t have or claim any expertise in at all. Early on I found this to be baffling and worrying in equal measure, and was sometimes put off making comments out of fear of them not being received with the appropriate level of scepticism, but I think I’ve pretty much got used to it now. According to my reckoning, when I’m being asked my opinion or being listened to it’s usually one of three things. There is a fourth, which is sometimes people ask your opinion when they don’t care what you think at all but want you to feel involved for political reasons, but I’m ignoring that. This is people who will actually take note of or action what you say.

The first reason people ask me stuff is because I know what I’m talking about in my little bit of data science. I’m happy with this one, clearly. I’ve already recruited such a good team that I think already it is true that any question about data science would be better answered by at least one of the team, and that’s entirely what I want, but I do obviously know some stuff and I can answer questions and talk about it. I’m going to put in this category stuff that I should answer better than the team too, which would be strategic questions about data science. This is less familiar ground to me but I have never had a technical person as a manager and never will now so I’m reasonably comfortable plotting a course, although clearly sometimes I will be right and sometimes wrong.

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The second reason people ask me stuff is because I’m the human shield if it all goes wrong. For example, thorny issues of prioritisation come up sometimes. We have tough choices to make about what to do and what not to do, the order to do it in, how well to do it, and so on. Making these decisions is clearly a team sport- between the customers, and me, and the team. If we get it wrong someone suffers- the customers don’t get what they want, the team work too hard or on something they don’t believe in. But owning the decisions is my job. I want the customer to feel assured that we are going to get the calls right, and I want the team to know that if it all goes wrong it’s my job to explain why, and it’s my decision making process that got us there. I’m accountable, not them. As I said in the previous post on this blog that’s what the extra money is for. Not for having all the answers, but for owning the solutions, trying to find a path through any problems, and always being in front of your team if it all goes wrong.

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The second reason people ask me stuff is because I’m the human shield if it all goes wrong. For example, thorny issues of prioritisation come up sometimes. We have tough choices to make about what to do and what not to do, the order to do it in, how well to do it, and so on. Making these decisions is clearly a team sport- between the customers, and me, and the team. If we get it wrong someone suffers- the customers don’t get what they want, the team work too hard or on something they don’t believe in. But owning the decisions is my job. I want the customer to feel assured that we are going to get the calls right, and I want the team to know that if it all goes wrong it’s my job to explain why, and it’s my decision making process that got us there. I’m accountable, not them. As I said in the previous post on this blog that’s what the extra money is for. Not for having all the answers, but for owning the solutions, trying to find a path through any problems, and always being in front of your team if it all goes wrong.

So far so good. I’m on those two now, and it feels natural to me to give good advice where it’s needed, help make the best decisions we can, and to own those decisions. And now we come to the last reason, which I’m still not great with. The third reason people ask me stuff is just out of sheer it’s my job to decide stuff. Sometimes there are just no correct answers or no data to answer the questions with, sometimes there is deadlock between two parties. Sometimes people who would be better at answering the questions don’t want to own the decisions for whatever reason (sometimes it involves money, that’s a common one). So I will advise or make decisions because someone has to, and the most obvious person in the room to do that is me. A classic thing I’ve always noticed before I was given any decision making power is a group of managers all sitting round deciding on the visual design of something. They’re all completely ignorant of visual design, it would be far better to get somebody that understands visual design to decide, but it just feels natural for the managers to sit around and argue about it and pick something. Honestly I feel like some people are way too good at this, they jump straight in with their opinions without any apparent regard for their complete ignorance, but maybe I’m being unfair. Maybe they’re perfectly well aware that they don’t know what they’re talking about, but they’ve been at this game longer than me and they know that their role in that moment is to make or contribute to a decision.

If I were to sum up everything I’ve learned about giving opinions and making decisions I would offer this: