Kurtosis | Information Training for the NHS

Time 2021-01-12 14:04:54

Web Name: Kurtosis | Information Training for the NHS

WebSite: http://www.kurtosis.co.uk

ID:164817

Keywords:

Training,Information,Kurtosis,

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I went to the NHS-R Community Conference in Birmingham on Tuesday. It was great. Here are three observations about it. Read more>>> What should we do while we wait for a new and better media container for data messages? Read more>>> 29 November 2017 Analysts don't just need to master the stats; they also need to understand the processes they're describing, Read more>>> 22 November 2017 What are the practical actions that need to be taken to make the use of control charts the default choice for trusts to monitor their operational data as well as being used for improvement projects? Read more>>> 3 October 2017 If NHS data analysts were to draft an American Declaration of Independence-style manifesto, then one of the truths we hold to be self-evident would be that all information should be useful. Our data shouldn't just be something that managers and clinicians find "interesting". And it certainly shouldn't just be something they ignore. No. Our data should be instrumental in helping to change things that need to be changed. But the process by which information gets turned into action (Before he started using the hashtag #showflow, Chris Green used to add the hashtag #dataintoaction to his tweets) is not at all straightforward. This engagement between data and decision-making is the Holy Grail for a lot of us, and we spend a lot of time trial-and-error-ing different ways of achieving this alchemy. One theory I stumbled across recently is the Learning Healthcare System. This approach by Charles Friedman makes the point that there are behavioural as well as technical aspects to getting data into the bloodstream of the decision-making process. Read more... One of my more vivid Flowopoly memories is of a workshop on a wintry day at Wishaw General Hospital two-and-a-half years ago. Back in those days the method we used for choosing which bad day and which good day to replay wasn't as sophisticated as it is now (we used to just pick days when A&E four-hour compliance was either "bad" or "good"), and I remember that the thing that made the good day good wasn't the usual thing (that there were empty beds available downstream of A&E for the patients who needed to be admitted to flow into). Instead it was that none of the A&E attendances that day needed to be admitted until mid-afternoon, by which time the Assessment wards had had time to recover from their perilous 8:00am fullness situation and release beds thus enabling a relatively breach-free day. The hospital's unscheduled care system was effectively "rescued" by the late arrival times of its majors in A&E. Read more... When information analysts use data to describe healthcare they usually start with institutions or departments or staff disciplines and measure things within those categories. How many hospital admissions? How many GP consultations? How many A&E attendances? How many district nurse contacts? It’s as if we are looking at a map of healthcare where boxes represent buildings (e.g. hospitals or A&E departments) and circles represent staff disciplines (e.g. district nurses or GPs), and we then populate these shapes with aggregated numbers. Read more... Two months ago, the Health Foundation published a thought paper written by Martin Bardsley. The first paragraph of the report sets out the problem it was addressing. Read more... Flow_ology is a method that gets data about patient flow into the bloodstream of a general hospital. I teach this method in a workshop that has three acts. Read more... Imagine you've been given the job of preparing a great big three-course Sunday lunch for the full extended family. Three complicated dishes you've never cooked before. But all you've got in front of you is an incomplete, fragmented list of ingredients. No step-by-step instructions. And even the list of ingredients has got vital things missing from it. Read more... There's a narrative arc to the Flow_ology course which mirrors the argument underpinning the theory I call "The Fullness Hypothesis". Read more... What's the use of data without pictures or conversations? Anaximaps is a new one-day workshop that shows data analysts how to acquire, analyse and populate user-drawn maps of health and social care processes. Read more... This is a thought-provoking piece by William Davis, published in the Guardian on 19 January 2017. Although its sweep is broad, much of what this article says is highly relevant to healthcare statistics. One of my favourite sentences from it is: "Official knowledge becomes ever more abstracted from lived experience, until that knowledge simply ceases to be relevant or credible." Read more... One of the questions that keeps me awake at night is this: "When you've got a problem, and you don't know what the solution to that problem is but you do know that information will help in the understanding and solving of the problem how do you decide what information to look at?" Read more... We need to start looking at health and social care activity from an "individual patient journey" perspective. This means being a lot less interested in knowing separately and in isolation how many A E attendances in total, how many district nurse contacts in total, how many homecare visits in total, how many GP consultations in total. And instead being a lot more interested in how individual patients become an embodiment of collections of events. Read more... There are three open course dates in London coming up over the next two months. Demystifying Statistics is a whistle-stop tour through the basic stats syllabus. Arguing with Numbers shows how to describe numbers using the written word and the spoken word - ranging from the one-side-of-A4 summary to the longer, more complex, data-rich report. Flow_ology teaches a 'method' for analysing and presenting unscheduled care data on patient flow within acute hospital organisations. Read more... I considered at great length the question of field. In classical anthropology, there's a rigid distinction between "field" and "home". Field's where you go to do your research, immersing yourself, sometimes at great personal risk, in a maelstrom of raw, unsorted happening. Home's where you go to sort and tame it: catalogue it, analyse it, transform it into something meaningful. Read more...

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