Volume 7 Issue 3 August2013 Welcome to Knowledge Matters For my first stint as editor of Knowledge Matters we’ve rolled back the clock (insert wobbly screen effect here) to the time of ancient Rome, a tenuous link to the emperor Caesar Augustus, after whom the month is named and whose reign is considered to have laid the foundations for a regime that lasted nearly 1,500 years. In this edition we have an interesting article from Prof. Moira Livingston, clinical director for Improvement Capability at NHS IQ, and how their work will fit within the new structure of the NHS going forward, plus details of the proposed care.data programme which will impact all providing analysis within the NHS, and further development from the world of NHS Insight provided by Samantha Riley. Tickling my geek sense this month is a particularly genius piece in Skills Builder on how to create dynamic charts and drop down lists in your spreadsheets without having to resort to pesky VBA code with all its complications. I know I’ll definitely be using that in the future! Oh and just a last piece of fun I’ve found - a great site with pretty but awful visualisations. Always remember when you are presenting your analysis, it may look good but does it tell you anything and can anyone actually understand what it means? http://www.wtfviz.net
Inside This Issue : Making Connections: NHS IQ
2
Making Connections: NHS Insight
8
Geographical Information Systems
4
Ask An Analyst: Percentiles
10
Care.Data: What will it do?
5
Analysis Ancient & Modern
13
Skills Builder: Dynamic Charts & Drop Downs
6
News
14
twitter.com/SECSHAQO issuu.com/SECQO http://www.networks.nhs.uk/nhs-networks/sec-qo www.QualityObservatory.nhs.uk
2 The new driving force for improvement across the NHS in England Prof. Moira Livingston, Clinical Director for Improvement Capability, NHS Improving Quality
This year has a seen a radical shake up of the landscape of the NHS, with a wealth of new bodies and organisations being established. I’m the clinical director for one of these new organisations NHS Improving Quality (NHS IQ), which is the national improvement body for the NHS in England. Our remit is to help drive up the quality of outcomes and experience for patients across the health and care system in England by providing improvement and change expertise. Aligned with the NHS Outcomes Framework NHS IQ brings together a wealth of knowledge, expertise and experience, while establishing a new vision and re-shaping the healthcare improvement landscape. In forming NHS IQ, we have taken on board the lessons of history and the experience of previous national improvement teams. For the first time the NHS has a single improvement body that is fully aligned to its commissioning priorities as expressed through the five domains of the NHS Outcomes Framework. A number of key programmes of work have been identified, which map against these five domains (see diagram below).
Empowering people with passion and skills to improve quality In his recent report A promise to learn, a commitment to act, professor Don Berwick stated that the most important change in the NHS would be for it to become ‘a system devoted to continual learning and improvement of patient care, top to bottom and end to end.’ This concept is at the heart of what we do at NHS IQ – enabling healthcare staff to continuously develop their skills for improvement. Our Improvement Capability team is working to create opportunities where people are liberated to develop new skills and improve the quality of what they do; to help share and spread new ideas, knowledge and tools; and to connect people at all levels. Our work is underpinned by a three-pronged approach; Growing People, Growing Knowledge and Growing Science. Growing People focuses on developing the culture, conditions and mindset that underpins successful improvement.
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3
Growing Science is around supporting on-going research in improvement science, and the application of robust evaluation methods to support the application of improvement in practice. Growing Knowledge bridges these gaps, developing networks and tools that underpin the movement of knowledge from ‘science’ and into everyday use. As a whole, these three areas support the growth of evidence-base of science, which improves our understanding of what works when we try to improve quality of services to patients. Examples of how our work fits into these strategies can be seen below: Growing people and knowledge A recently launched programme to build transformational capacity within Clinical Commissioning Groups (CCGs) is attracting good interest. Working with their local commissioning partner organisations, CCGs are supported to tackle locally identified priority large scale or complex change priorities, rather than their routine improvement goals. CCGs interested in joining the programme should contact enquiries@nhsiq.nhs.uk. We are also developing a comprehensive transformational change prospectus, which will consist of modules and programmes designed to build capability in the workforce to deliver transformational change and service delivery improvements. Growing people We are rolling out the NHS Change Model across NHS England, CCGs, and primary care, as a single approach to transformation and change across the NHS, and testing its application in care settings. Growing science We are committed to increase knowledge and understanding of how to use data to improve quality, and this autumn we are delivering a measurement masterclass series for senior clinical leaders. This is designed to help strengthen understanding amongst clinicians of the principles of measurement for improvement, and to provide the confidence to hold influential discussions with policy makers and data collectors. Working in collaboration to drive improvement With support and engagement from across the health and care system, NHS IQ will act as a catalyst to drive transformational change across the NHS. In doing this, we will create innovative and new knowledge of how to achieve sustainable change. We look forward to working collaboratively to ensure that our NHS continues providing top quality, affordable healthcare for all. For further information, or to contact us, visit www.nhsiq.nhs.uk or email - enquiries@nhsiq.nhs.uk
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4
Geographical Information Systems (GIS) David Harries A Geographic Information System (GIS) can be defined as a computerized database management system for capture, storage, retrieval, analysis, and display of spatial data. Any data that includes information about location, for example an address, postcode, Local Authority boundary, census area or GPS coordinate, can be considered spatial.
Many different types of data can be integrated into GIS and represented as a map layer. When these layers are drawn on top of each other, GIS allows you to view, question, interpret and visualize data from which patterns and relationships often emerge.
How can GIS help you? GIS has the potential to act as powerful evidence-based tool for early problem detection and solving. GIS can: inform and educate; empower decision-making at all levels; help in planning clinically- and costeffective actions, in predicting outcomes before making any financial commitments and ascribing; change practices; and continually monitor and analyse changes, as well as sentinel events. By combining health datasets with other sources, such as census data for small areas, GIS can be used to investigate spatial patterns in health outcomes in relation to socio-economic characteristics of areas, in identifying gaps in healthcare provision, as well as in monitoring the impacts of changes in policy. Types of Map •
Choropleth or Thematic (colour shaded) maps. This is especially appropriate for showing standardised data such as rates, densities or percentages.
•
Dot maps. Individual events or groups of events are marked with a dot, allowing users to identify geographic patterns such as clusters.
•
Proportional symbol maps. These use symbols that are proportional in size to the values they represent, such that the biggest symbol will fall in the area with the highest value.
•
Heat maps. Also known as hot spot mapping, heat maps show locations of higher densities of geographic entities.
•
Interactive online maps
Access to Ordnance Survey data through the Public Sector Mapping Agreement has enabled the Quality Observatory to use their expertise in the field of mapping technologies to integrate the power of GIS mapping for detailed and informative visualisations of data, on a local, regional and national scale.
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5
Care.Data– what will it actually do? Kate Cheema You may have heard of care.data or even been invited to an event abut it. But what is it and what does it mean for healthcare information? Approved back in April 2013, the care.data programme, being delivered by the Health and Social Care Information Centre, is designed to extract and link large amounts of primary and secondary care data, providing, for the first time, a more holistic view of the patient journey. Data, with appropriate levels of anonymisation, will be available to the public, providers, commissioners and public health as well as researchers and, most importantly, patients. This availability will not just be static presentation but will be capable of interrogation by stakeholders, including the public. In the long term, the care.data service will be populated with extended data sets from hospital inpatient, outpatient and A&E, GP practices, community services, mental health and learning disability services, clinical audit, disease registries and social care. This will provide the most comprehensive single source of healthcare data that the NHS has ever seen, and given the coverage the NHS has of the English healthcare market, one of the most important public health and health improvement resources ever commissioned. The view is that the data can be used to identify variation in healthcare provision and outcomes, build predictive models and provide important controls in research studies. For healthcare information providers it could be revolutionary, moving us away from scrabbling to put different sources of data together to a more straightforward provision and interpretation of analysis of the data i.e. making the data work for patients The extract was approved following an independent review of the information governance issues surrounding data extraction and linkage on this scale, particularly from a primary care perspective. Key recommendations were made including identification of relevant and reliable codes to be included, and allowing individual patients to ‘reasonably object’ to their data being extracted and used in this way. A briefing on care.data has been circulated to CCGs and Area Team leads and provides an update on the activities being carried out in 2013. We would encourage all Knowledge Matters readers to get involved in these consultations as they happen, to help influence the shape of what could be the dataset we’ll all be using in a few years. GP data extract: Primary care data will be extracted from practices as agreed with the RCGP and BMA. 80 early implementer GP practices have received communication materials for their practice (posters and patient leaflets) in June to support an 8 week consultation, during which practices recorded patients wishing to opt-out of providing their data; first extracts of data from their systems are scheduled for mid-September. All other practices will receive their communication materials in mid-August to allow them to run their 8 week consultations, record any patient opt-outs, with data extractions scheduled for late October. The linked data sets will be available from HSIC from December 2013. Hospital data consultation: Between 22 July 2013 and 16 September 2013 NHS England and HSCIC are consulting on the data that should be collected from hospital data systems as an extension to the existing Hospital Episodes Statistics (HES). The Hospital Data and Datasets Consultation asks for views on what information should be extracted from hospitals in future to support the commissioners of health care services, and how to minimise any extra burden on hospitals. http://www.england.nhs.uk/2013/07/22/consultation-hospdata/
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6
Dynamic Drop Down List and Chart In a previous edition of KM (Volume 6 Issue 6), we discussed how to create a drop down list that depends on another drop down list and we even discussed how to make this dynamic. Well, there has been a request to expand on this further to create a dynamic chart. Using the same example as last time, imagine we have two lists of items, Fruits and Proteins and we would like to show the number of items in a single chart, but which item is dependent on which list has been selected.
By making this dynamic so that it takes into account the number of items in the list, we should be able to avoid situation where the chart may look something like below: Notice the blank space at the end of the chart as a result of Protein List having fewer items that Fruits. Again, we’ll start by creating two drop down lists – one for Types of food (Fruits and Protein) and the 2nd to show specific food item based on the type of food selected.
We need a list of items and also a cell to link the drop down box to. (I have typed the following into cells A1: H6). For charting purposes, let’s assume the vertical axis will show the count of each item. The first drop down (Food Type) is the simpler of the two – Click View ->Toolbars >Forms and select the ComboBox. (or in 2007/10 Developer tab -> Insert -> ComboBox). Food Types 1 Fruits 2 Protein
0 1 2 3 4 5
Fruits Orange Banana Mango Strawberry Kiwi
Count of Item 10 20 15 10 30
1 Food Types
0 Protein 1 Fish 2 Meat
Count of Item 10 15
This should give you a blank dropdown list. Right click on this and select Format Control and then select the Control tab. In the input range (this is the list you’re selecting from) highlight your list of food types. Also select your cell to link it into - in this case I have chosen cell A9 .
The next step is how to make the 2nd list change depending on what has been selected in the first. Create another list but using a combination of vlookup and if formulas to determine the list (basically, if Food Type is 1,
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7 lookup from Fruits else lookup from Protein).
Example of formula “=IF($A$9=1,VLOOKUP($O2,$C$2:$E$6,2,0),VLOOKUP
($O2,$F$2:$H$3,2,0))” Food Types 1 Fruits 2 Protein
0 1 2 3 4 5
Fruits Orange Banana Mango Strawberry Kiwi
Count of Item 10 20 15 10 30
0 Protein 1 Fish 2 Meat
Count of Item
0 Protein 1 Fish 2 Meat 3 #N/A 4 #N/A 5 #N/A
It is this combined list that will be used to drive the 2nd #N/A #N/A dropdown list. As you can #N/A see in cell H4, we get an error message because Protein only has 2 food items. This will come into play in the next steps. (Notice that if the drop down is to be truly dynamic, it would avoid the situation below where part of the drop down is blank but is still being displayed as a selectable option). 10 15
10 15
Before we create the 2nd drop down list, let’s create a defined named range that we will use in the 2nd drop down list. Click on Insert ->Name ->Define (2007/10 Formulas tab ->Name Manager -> New): Add a new named range called lookup and using a combination of offset and countif, we can define the area of the name range based on the combined column but not including any cell containing an error message (#N/A). (Example formula: “=OFFSET(Sheet1!$P$2,0,0,MAX(Sheet1!$O$2:$O$6)-COUNTIF(Sheet1!$P$2:$P$6,#N/A),1)”) Now lets create a second drop down list but this time instead of selecting from a list of items, let’s used the name range we just created: And that’s it, the dynamic select box is finished. Now when the food type is selected, the 2nd drop down will update to show only the food items applicable to that food type.
The next stage is to extend the same principle into the chart. First, create another named range similar to the “lookup” above using a similar formula but this time point it to the Count of Item column (the named range has been named “chartValue”). Create your chart as normal but the value field, instead of using the normal static cell ranges, you can enter the name range: multipleselectbox.xls!chartValue. The first part in red is the file name and the 2nd part is the named range. Similarly, in the chart instead of using the labels by selecting a static cell range, use the named range from above in 2nd drop down list “Lookup”. And now that’s it – because of clever use of countif, vlookups and named ranges, we now have a dynamic chart which is based on selected item from the drop down list. If you would like a copy of the Excel document used to create this example, contact us at the usual address.
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8
Developments in the world of NHS Insight Samantha Riley, Director of Insight, NHS England Hello Knowledge Matters readers! I hope that you have been enjoying the sunshine! Since the last edition, lots has happened in the world of NHS Insight. Firstly, on 30th July, many of you (I hope) will be aware that the first three months of the Friends and Family Test data for inpatients and A&E was published. This was my first experience of being on a pre-release list for an official statistic….. and let’s just say that it is a memory that will stay with me for some time! I don’t plan on making attendance in Quarry House until 11pm a regular occurrence! Anyway, the first publication received a considerable amount of media coverage on the day with Tim Kelsey (or Dr Tim Kelsey according to Sky News!) appearing on many of the national news channels. In the main the coverage was positive and there was some lively Twitter debate on a variety of issues surrounding FFT, the methodology, comparability etc. This Twitter dialogue continues and it would be great if Knowledge Matters readers contributed to this virtual discussion. The hashtag we are using is #NHSFFT if you would like to share your views and stories and join the debate (and if you would like to follow me please do @samriley). There were a number of themes which emerged on the day in terms of clarifications and further explanation being required. For those of you who are familiar with FFT, these probably won’t surprise you. They were: •
Misunderstanding the score and assuming that a score of 67 meant 67% which of course it does not (the score of course ranges from -100 to +100);
•
Understanding the calculation of the score;
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Understanding the suppression of small numbers;
We committed some months ago to undertake a review of the Friends and Family Test 6 months after its introduction. As part of this review, we will be considering these types of issues as well as assessing the improvements that have been made as a result of the introduction of FFT, and the contributing factors associated with where improvements have been made. I’ll talk more about the review in the next edition of Knowledge Matters. 30th August saw the publication of the July FFT data. To date approximately 600,000 responses have been received from patients across England. The number of responses rose by 8% from June to July which is great news. Other headline figures for the July data are as follows: •
The number of wards with the most positive score (+100) increased from 497 in June to 560 in July;
•
The number of sites with an inpatient score of +100 also increased from 46 to 58 – many of these are independent sector hospitals;
•
The overall response rate for inpatients (NHS and independent sector providers) increased from 27.1% to 27.8%. Only 12 NHS Trusts had an inpatient response rate below 15%;
•
The England level response rate for A&E rose marginally from 10.3% to 10.4%.
•
The A&E response rates range from 0.2% to 44.6%. 108 NHS Trusts had a response rate below 15% in July.
If you would like to have a look at the data yourself and you are within the NHS, I would recommend you to have a look at the FFT tool developed by the Quality Observatory tool. Here’s the link: http://nww.fft.england.nhs.uk/
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9 In addition, data files can be downloaded from the NHS England website. Here’s the link http://www.england.nhs.uk/ statistics/2013/08/29/friends-and-family-test-july-2013/ I’m a recent convert to Twitter and it has been really interesting to see the types of analysis being undertaken by people in the Twittersphere! Chris Graham (@ChrisGrahamUK) from the Picker Institute undertook some analysis to correlate FFT data with the inpatient and staff survey data. Carl Plant (@CarlPlant) has done some really interesting work looking at how the data can be visualised. http:// wai2k.wordpress.com/2013/08/18/nhs-friends-and-family-test -vs-staff-survey/ With thanks to Chris Graham Wai Keong Wong (@wai2k) wrote a blog on the correlation between FFT data and staff survey data which you might want to have a look at http:// wai2k.wordpress.com/2013/08/18/nhs-friends-and-family-test-vs-staffsurvey/ Thanks everyone for undertaking the interesting work! I was really pleased to see that the Picker Institute this week made available some free FFT resources which cover the following areas: • how the FFT score is calculated • FFT score and confidence interval online calculator • FFT score difference and confidence interval online calculator • FFT calculation and comparison: key assumptions and caveats • the effect of response numbers on FFT score confidence intervals With thanks to Carl Plant • what to do with small numbers of FFT responses • how to make use of people's free text comments to improve These are all available from the Picker Institute website http://www.pickereurope.org/fft-resources/ FFT publication dates for the remainder of the financial year are as follows: August data – 3 October September – 31 October October – 28 November November – 9 January December – 30 January January – 6 March We are currently working on the development of guidance for the introduction of FFT to different areas of the NHS. I’ll talk in the next issue about the roll out approach and timetable for this in more detail, but just to mention that FFT for maternity goes live in October. We will be reissuing a Unify template for maternity within the next week or so and disseminating this to Trusts. Finally, (and just to show that there is more to life than FFT), the bereaved Voices survey was published on 11th July. Here’s the link http://www.ons.gov.uk/ons/rel/subnational-health1/nationalbereavement-survey--voices-/2012/stb---national-bereavement-survey-2012.html. The Cancer Patient Experience Survey was published on 30th August. Here’s the link to the NHS England press release http://www.england.nhs.uk/2013/08/30/cancer-patients-positive/ . And watch out for the Community Mental Health survey which is published on 17th September.
I look forward to seeing you next time. As always, please do get in touch directly if you have any issues, ideas and would like to share work that you are doing around patient insight samanthariley@nhs.net
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Percentiles We often get asked about what percentiles are and how they work, so here’s a revisit of something we did a long time ago, as a bit of a refresher
Solution: Complexity 3/5 Would you be surprised to know that there is no standard definition of percentiles? You would be right in thinking that they have something to do with percentages. As discussed in the last issue percent (%) means "out of 100" and is a way of expressing any number as a fraction of 100, or another way to think about it is dividing any number into 100 equal pieces, or 100 percentages. Percentiles similarly are a way of dividing a group of values into 100 pieces with an equal number of values in each, or 100 percentiles. A quick search on the internet quickly reveals two slightly different definitions of percentiles: Either as a value on a scale of one hundred that indicates the percent of a distribution that is equal to or below it, Or as a value on a scale of one hundred that indicates the percent of a distribution that is below it. This difference in definition makes little difference in large data sets, but can have significance in smaller ones! As with all descriptive techniques it is important to understand what you are looking at. Take the following set of numbers: 1,2,3,4,5,11,12,13,15,20 Now there are two ways of describing the values in this series: We can compare these values to each other using techniques like percentages or fractions e.g the value 5 is 25% of the value 20, or 5 is ¼ of the value 20 Or We can compare the values to their relative positions in the series e.g. 5 is the 5th value in a series of 10. So how are percentiles used as a description of position? Let’s look at the first definition of percentiles: “a value on a scale of one hundred that indicates the percent of a distribution that is equal to or below it" So if we look at the value 5, this is the 5th value in a series of 10, or 5 out of 10 values are equal to or below 5, we can use the same calculation as with percentages to determine the percentile. (1-(5/10))*100 =50th percentile. In this case the value 5 being the 50th percentile means that 50% of values are smaller than or equal to the value 5.
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11 What about the second definition of percentiles: “a value on a scale of one hundred that indicates the percent of a distribution that is below it”? So if we look at the value 5, this is the 5th value in a series of 10, so 4 out of 10 values are below 5, we can again use the same calculation as with percentages to determine the percentile. (1-(4/10))*100 =40th percentile. In this case the value 5 being the 40th percentile means that 40% of values are smaller than the value 5. As you can see this variation in definitions can lead to a difference in result which you do need to take into account when interpreting data, especially with small data sets! The technique of percentiles allows you to compare a value’s position in a group but not the magnitude or scale of difference between the value and any other value in the series. Percentiles can be found across the NHS being used in a number of ways. Most frequently you may come across them being used to rank a series of numbers (usually ranking organisations according to a specific indicator such as waiting times), but they can also be used on historical data sets to determine upper and lower confidence intervals which can be used to compare against actual values to highlight anomalies and patterns that may require further analysis. For Example: Below is a weight chart This chart was created by taking a historical sample of children’s weight at different ages. For example if we looked at the data for 10 year olds and plotted the number of children in each weight band it might look something like this:
No. of children
Weight
Now we can split these values up either by percentage of the biggest value, or by the order of the values. We can then identify ranges of concern i.e. in this case any weight that falls under the 5th or over the 95th percentiles should be flagged as of concern.
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12
Percentiles (continued!) This distribution can then be used to compare “new� data points against, or to monitor or flag for concern, in this example any weight over the 95th percentile of the original sample distribution (45kg). 5th percentile
95th percentile
No. of children Of concern
25kg
Weight
45kg
This can also be used to compare distributions e.g. if more than 5% of a recent sample falls inside the 5th percentile of a historical distribution, this could be highlighted as an area for concern. 5th percentile
95th percentile
New Data
No. of children
Weight
Percentiles can also be used in place of other comparative techniques like averages; for example, you may want to compare values to the middle of a series or to a higher point in the data series. When using descriptive techniques, always take a moment to consider what you are looking at or what you are trying to describe before deciding which technique to apply as there may be more appropriate techniques to use. For more information or to explore this topic further here are a few websites with further info: http://cnx.org/content/m10805/latest/ http://en.wikipedia.org/wiki/Percentile_rank http://en.wikipedia.org/wiki/Percentile
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Analysis Ancient and Modern Adam Cook What Have the Romans Ever Done for Us? Although he was known by many names the doctor and philosopher Galen was one of the most pre-eminent surgeons of the Roman period. Popular medicine in those times was heavily influenced by the teachings of Greek doctor Hippocrates, and was based around the idea that the body was controlled by four ‘humors’. Medicine itself was as much a philosophy as it was a science, and was dictated more or less by what people thought, rather than what was observed and empirically recorded. Galen tried to bring medical science forward by introducing elements of direct observation. He was a great one for cutting things open, and through his work in vivisection and dissection of pigs, and monkeys, his writings on anatomy were the standard to which everyone worked to up to the mid 16th century. Although much of his work was superseded from this point on, his writings were still important to medical students and continued to be studied up until the 19th century. Galen was not perfect and there were many imperfections in his beliefs, but however flawed his teachings may have been his work on the circulatory system, the nervous system, and the respiratory system were the foundations upon which many later physicians built their work. Galen was not an epidemiologist in any sense of the word; his interests were in the symptoms of individual patients and how to cure them. However his methods of observation and research have helped retrospectively identify the Antonine Plague. The Antonine Plague originally broke out in 166 AD, and is believed to have caused over 3 million deaths. Galen noted what symptoms patients had and described the blackened sores, and blistery rash in enough detail that current medical science is able to confidently identify this plague as a smallpox outbreak.
An extract of Galen’s treatise on the pulse
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14
NEWS Hospital Data & Data Sets
OpenAthens
NHS England and the Health and Social Care Information Centre (H&SCIC) are undertaking consultation on hospital data and data sets. The Hospital Episode Statistics (HES) system collects statistical information about the care provided to hospital inpatients, outpatients, and A&E patients. The consultation is to explore the future development of HES. In particular, views are sought on what electronic data should flow into the H&SCIC. BCS Health is holding an event on 9th September in London to openly debate these proposed changes.
NICE the National Institute for Clinical Excellence - has signed a two-year agreement with Eduserv to provide identity and access management services through OpenAthens to over 1.5 million users.
Consultation document: http://www.england.nhs.uk/ wp-content/uploads/2013/07/hosp-data-consult.pdf To book for an event: book/776/.
https://events.bcs.org/
Health Apps Downloadable apps available from NHS Choices include apps for getting fit, quitting smoking, alcohol awareness and weight loss. The apps are free-ofcharge. See: http://www.nhs.uk/Toolslibrary.aspx? Tag=Downloads+and+widgets. DIARY DATES 05 Sep 13
NHS FFT Site User Guide Webex For joining details please contact: info@qualityobservatory.nhs.uk
09 Sep 13 BCS Health, “Debate on Proposed Changes to Hospital Data Sets” London https://events.bcs.org/book/776/ 11 Sep 13 Southern Institute for Health Informatics
The agreement, which is on behalf of 700 NHS-affiliated organisations that make up NHS England, is worth £550k over a two year period and will enable users to access all centrally procured online information, such as bibliographic databases, e-journals and e-books. The contract will enable NHS organisations in England to have the latest information and resources at their fingertips, so documents can be accessed both onsite and remotely. It will make accessing information and data quicker and easier for end users as well as helping the different NHS to make better use of their budget by collating usage reports which are then broken down by resource and user group. Through OpenAthens, organisations are able to manage multiple licenses for e-books and e-journals and provide access to them from one portal. This gives administrators total visibility as to which publications and documents are being accessed and lets them manage subscriptions in a cost effective manner. OpenAthens has over 4 million users worldwide, with customers including 50% of UK universities, the Department of Veterans Affairs (USA), Philips Research and South Australian Health. Access to knowledge sources, e-journals and e-books greatly supports teaching, research and innovation. Making these knowledge sources more easily available can only assist the NHS and individual clinicians in forwarding healthcare.
“From Big Data to Collective Wisdom”, Portsmouth www.port.ac.uk/sihi
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More information: http://www.eduserv.org.uk/identity-access
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15
NEWS CQC appoints Inspector of General Practice The CQC has appointed their Professor Steve Field as their first Inspector of General Practice
TOP TEN ON TWITTER New to Twitter? Want to know who to follow in the world of healthcare and analysis? Here are our top ten (this month!)…..
http://www.cqc.org.uk/public/news/professor-steve-fieldchief-inspector-general-practice
@SECSHAQO
Complaints data
Your very own beloved Quality Observatory. Well, it’s a given isn’t it!
The 2012-13 data on written complaints is available from the HSCIC:
@NHSIQ
http://www.hscic.gov.uk/article/3414/NHS-writtencomplaints-data-released
Vital statistics The ONS have now released the Autumn 2013 update to their ‘Vital Statistics: Population and Health Reference Tables’ providing annual and quarterly data for a selection of key statistics under the themes of population, demography and health including data on births, deaths and conceptions. The tables are available from the ONS website and a link is provided below: http://www.ons.gov.uk/ons/publications/re-referencetables.html?edition=tcm%3A77-314699
Population Estimates Clinical Commissioning Group Population Estimates are now available via the ONS website and includes figures by CCG, NHS Area Teams and NHS Commissioning Regions. The figures are available from the link below: http://www.ons.gov.uk/ons/rel/sape/clinicalcommissioning-group-population-estimates/mid-2011-census-based-/index.html
On the road! Many congratulations to Aleks who passed her driving test last month. People of Surrey, look out!
NHS Improving Quality works to provide improvement and change expertise to support health outcomes for people across the NHS in England
@statisticsONS Official channel of the ONS in the UK @anniecoops Clinical Informatics Advisor at NHS England, helps keep informatics where it should be; with the patient @carlplant Data specialist & ex-nurse. groovy ideas
Full of
@NHS_analyst Chief counter of non-financial beans in a London trust. All about better decisions @hscic Our chums at the information centre @informaticsman New to the Twitterverse but with a CSU view on analytics @d_speigel The last word on understanding risk, David Speigelhalter is the guru of appropriate use of healthcare statistics @CSUCassander Lots to say on use of data but also keeper of the NHS Lexicon
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In Condemnation Of Roman Numerals
Call for Articles
I don’t think the Romans had analysts,
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Have you seen the numbers they used? It’s just letters like X, I and V, Leaving a chap all confused. I wouldn’t want to do sums as a Roman, I’d get in a terrible state, Carrying D, when dividing by M Doing a mortality rate. When watching a black and white movie And I want to find out when it was made,
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I watch ‘til the end of the credits, But you know what’s often displayed.
Fascinating Facts
A long stream of letters starting MC,
Using contemporary rules, the largest number that could be represented by Roman numerals was 4,999
Then the rest that make me go blind, It looks like a bad hand at scrabble, Illegible to half of mankind. So I’m thankful to Arabic numbers, Adding and subtracting with ease,
MMMMCMXCIX
And the wonderful digit of zero, That makes calculations a breeze. Romans were very great soldiers, And builders of temples and baths, But I wouldn’t want to be one, When it came time to doing some maths.
Simon says……. Contrary to popular belief thumbs up or down was not used by the emperor to indicate to a gladiator to spare an opponent’s life. Instead, an open or closed hand was used. Held flat it meant spare, if closed, kill him.
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