Knowledge Matters Volume 5 Issue 5

Volume 5 Issue 5 December 2011 Welcome to Knowledge Matters Hello everyone! Welcome to the fifth Christmas Edition of Knowledge Matters! In this edition, we provide an overview of key documents which were published earlier in December—the NHS Outcomes Framework for 2012/13 and the Innovation report and outline important considerations to be taken into account when looking at SHMI data. I am pleased to report that we have articles from colleagues in other parts of the South highlighting the excellent work which is underway across the whole of the SHA cluster, and we have an excellent article from Nottingham University Hospitals on predicting patient flow which I hope will be useful to a number of our readers. This is the first time that we have a Christmas Appeal. We felt that it was important to highlight the plight of those that sometimes feel unloved. This issue’s poem (see the back page) continues the theme of the appeal. Please give generously…….. All that remains for me to say is very best wishes to all Knowledge Matters readers (wherever you are) for a prosperous, peaceful and productive 2012. See you next year! Best wishes Samantha Riley Director of Information for Service Improvement The Quality Observatory NHS South of England

Inside This Issue : Summary Hospital-Level Mortality Indicator

The Winter Dashboard

Predicting Patient Flow

The NHS Outcomes Framework 2012/13

Innovation Health and Wealth

Ask An Analyst

Flu Fighters

Quality Observatory Christmas Appeal

Analysis Ancient & Modern

Skills Builder

Christmas Crossword

News

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More on the Summary Hospital-Level Mortality Indicator By Katherine Cheema, Specialist Information Analyst Here at Quality Observatory Towers we just can’t get enough of the summary hospital-level mortality indicators (SHMI). The debate as to how to pronounce SHMI (are you a ‘Shimmy’ person, or an advocate of ‘Schmeee’?) still rages across the floor but aside from issues of pronunciation, we’ve been especially concerned with the mixed messages that can come from using different measures of standardised mortality, such as HSMR or RAMI. You’ll remember that in the last issue, Samantha helpfully included a link to CHKS’s useful technical guide which explains the differences between SHMI and RAMI (Risk Adjusted Mortality Index). Here’s the link to it (http:// www.chks.co.uk/assets/files/DataBriefings/Differences_RAMI_AND_SHMI.pdf) in case you don't have your last Knowledge Matters to hand. Here are a few key points and bits of learning we’ve picked up after using and discussing SHMI for a month, plus an insight into what it looks like in the South of England. • SHMI is really useful to use alongside HSMR, RAMI or other standardised measures of mortality, but remember that it effectively measures something different. There are also some other technical differences between the various indicators– make yourself aware of them and what they mean in practice (see the table below for a few pointers). It doesn't mean that one or the other is ‘wrong’ but highlights the importance of seeing them together, and in context. • SHMI is presented with two different types of control limits have been calculated for initial publication, be aware of which is being used for reporting in your area and of the alternative results if the other limits are used: ◊ Exact control limits: using these limits, 9 NHS South of England trusts are identified as having a SHMI higher than expected, and 6 as having a SHMI lower than expected ◊ Control limits that allow for a statistical factor known as ‘overdispersion’: using these limits, only 3 SoE trusts are identified as having a SHMI higher than expected and none as having a SHMI lower than expected • Results for the SHMI should be looked at in conjunction with community providers and social services partners, because deaths occurring outside of hospital within 30 days of discharge are included. Where there is a marked difference between HSMR/RAMI (i.e. in hospital mortality measures) and SHMI a joint approach to investigation is especially important. • As with HSMR/RAMI, SHMI should always (always, always, always!) be looked at in context, with additional measures of quality and safety. The excellent ‘Dying to Know’ paper published by APHO puts it best, suggesting that the hospital mortality ratio is “akin to a smoke alarm; it may signal something serious but more often than not it will go off for reasons unrelated to quality of care. But, like smoke alarms, [they] should never be ignored”.

Difference

Effect

Action

SHMI measures 30-day mortality, HSMR/ RAMI does not (this can add around 35% more deaths per year)

Trusts with a good HSMR/RAMI can have a poor Quality of and variations in community based care also needs to be assessed where SHMI is SHMI if their post-discharge mortality is high poor

The model underlying SHMI does not adjust for deprivation

Trusts with a good HSMR/RAMI can have a poor Assess the impact of deprivation on mortality at SHMI if they serve very deprived areas, where the local level to see if this plays a significant part deprivation has an impact on mortality rate

The data used to calculate SHMI includes palliative care episodes; these are excluded from HSMR/RAMI

Trusts with a good HSMR/RAMI can have a poor Look at the level of palliative care coding over time; if this is increasing then this may have had SHMI if their palliative care coding is very good the effect of improving HSMR/RAMI, an effect

The data used to calculate SHMI includes zero Trusts with a good HSMR/RAMI can have a poor Look at the mortality rates in zero LoS emergenLoS emergencies; these are excluded from SHMI if they have a high number of deaths in cies; these are usually a low risk group and RAMI groups of patients admitted as emergencies with should have minimal impact a zero day length of stay

SHMI data for all hospitals can be accessed at the Information Centre website (as a csv file) http://www.ic.nhs.uk/ statistics-and-data-collections/hospital-care/summary-hospital--level-mortality-indicator-shmi/summary-hospital-levelmortality-indicator-shmi--deaths-associated-with-hospitalisation-england-april-2010--march-2011-experimental-statistics and the methodology for SHMI can also be accessed via the site http://www.ic.nhs.uk/webfiles/Services/SHMI/ SHMI_Specification_V1.8.pdf If organisations require support or advice on the new measure, please do get in contact and we will do our best to assist! quality.observatory@southeastcoast.nhs.uk

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The NHS Outcomes Framework 2012/13 By Samantha Riley, Director of Information for Service Improvement The Outcomes Framework for 2012/13 was published on 7th December The updated framework renews the focus on improving patient results with the NHS being measured against a number of areas including whether a patient’s treatment was successful, whether they were looked after well by NHS staff and whether they recovered quickly after treatment The updated NHS Outcomes Framework describes the changes made since the December 2010 edition. This includes a number of changes to indicators along with the introduction of new indicators (including those for stroke and children and young people as covered in Knowledge Matters last time). The updated version recaps the purpose of the NHS Outcomes Framework and how it will work in the wider system and also contains a very useful technical appendix which provides detailed information about each of the indicators in the framework. The NHS Outcomes Framework is one of a series of frameworks which support the Government’s desire to improve integration of services. The other frameworks are the Adult Social Care Outcomes Framework and the forthcoming Public Health Outcomes Framework. In terms of why there are three frameworks rather than one, it is to ensure that there is clear accountability in each of the areas and a focus on the areas which can be influenced. Having said that, there are a number of indicators which will be shared between the frameworks. An example of this is an indicator on the ‘under 75 mortality rate from cancer’ which will be shared with the Public Health Outcomes Framework. From the outset, the intention was for the Outcomes Framework to support comparison internationally and work is underway with a number of organisations (including the World Health Organisation (WHO) to ensure that indicators with the framework are comparable internationally. Watch this space for further news as we hear more. As previously, a useful summary appears in Annex A with details of all of the indicators within the 5 domains. The Quality Observatory are currently assessing the feasibility of regular reporting against each of these indicators. This will be an important area to report to the Board of NHS South of England over the coming year and of course post transition to the NHS Commissioning Board. The framework and associated documents can be downloaded from the Department of Health website : http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/PublicationsPolicyAndGuidance/DH_131700

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Flu Fighters ……….. By Rebecca Girdler, Public Health Epidemiologist, NHS South of England (Central) Winter again, the weather’s finally turned and if, like me writing this, you have a sore throat or blocked nose you may be thinking “I’ve got the ‘flu”. Yet this term is often misused. Influenza causes cold-like symptoms but it’s a completely different, more harmful virus than the common cold. Symptoms include high fever and severe malaise lasting a week or so. Thankfully most people recover but it contributes to an estimated 10,000-12,000 deaths annually in the UK. Influenza has a short incubation period and spreads rapidly between people. This results in a wave of infection, or epidemic, which surges through the population in a short time. Influenza has many different types but a few strains cause most of the serious infections in any one season. So every year batches of vaccine are tailor-made to match the most common and severest circulating strains. A new strain emerged in the June 2009 pandemic and is expected to be prevalent in circulation again this winter. Untypically, it displays a higher attack rate and causes more serious complications in younger adults under 65. Plus people with a medical condition and pregnant women have a further increased risk of hospitalisation and death. In fact those in a risk group are around 11 times more likely to die (over 40 times for some conditions, see Figure 1 below). The most effective method of prevention is vaccination. Despite vaccination being free to those at risk, safe and cost-effective; vaccination uptake in the under 65s at risk is low, with nearly half the people at risk in South Central going unvaccinated last year. Research is lacking in younger age groups but data from over 65s concludes there is an overwhelming belief among immunised and unimmunised individuals they are not at risk or don’t deem influenza to be serious. While those rejecting vaccination overstate vaccination side effects (less than 1% have reactions). Multiple prompts from family and friends and direct advice from GPs are significant motivators to get vaccination.1,2,3 The latest Cochrane evidence review (2010) lists benchmarked performance feedback to GPs as one of the most effective professional interventions to improve organisational processes, thereby increasing vaccination uptake. Following this, the SHA has worked in partnership with PCT immunisation leads and local HPA colleagues on a flu project which provides GPs with benchmarked feedback so they can compare their performance with peers. Every month vaccination uptake data is collected from practices. This is collated to give a “best” performance benchmark. As previous uptake was low, the bar was set high to achieve reasonable trajectories towards advised vaccination levels (60% coverage in 2011/12 but working up to a minimum 75% recommended as an effective level).

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This season we used the top 5 best practices as a comparator. Individual practice performance is then presented alongside the PCT benchmark for each disease group on a dual axis chart. The relative risk ratio of mortality (number of times more likely this group is to die from influenza than someone in the general population that has no increased risk factors). This information is sent to practice managers along with locally devised communications resources. Although in some disease groups small numbers can be a problem, the charts do give important quantitative information on peers can help practices identify achievable improvement. It is also a step in fostering conversations between partners, enabling us to work co-operatively to disseminate good work and gain further insights about potential barriers to vaccination. As this goes to press, the second monthly dataset is being submitted. It’s too early to draw conclusions but sentinel surveys suggest national uptake is still falling short of required levels. This would be disappointing given uptake for other vaccinations is high in the UK; evidence of the acceptability of vaccination as a prevention strategy. We’ll be collating lessons learnt and sampling patients’ views of vaccination and communications materials to yield some qualitative analysis at the end of the season. With thanks to Noel McCarthy and David van Santen at TVHPA and all others involved with the flu project. References: 1http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2047008/ 2 http://her.oxfordjournals.org/content/18/6/743.full 3 http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2648.2010.05397.x/full

Doppler Tools updated By Simon Berry, Specialist Information Analyst The Oesophageal Doppler tools, developed in conjunction with NTAC, have now been updated with HES final published data for 2010/11 and are now available on the QO website. http:// nww.qualityobservatory.nhs.uk/index.php? option=com_cat&view=item&Itemid=2&cat_id=486

NTAC Doppler Length of Stay Benchmarking by Specialty 2010/11 HES Brighton & Sussex University Hospitals NHS Trust (RXH) Highlighted - 1501 Patients Elective - All Specialties - SE Coast SHA Peer Group Comparator 20 Top Decile Top Quartile 18

Mean

16 Potential Savings from LoS Reduction

To Mean - 1,886 bed days To top quartile - 2,791 bed days To top decile - 3,143 bed days

Future developments early in 2012 will include a refresh using provisional HES data for Q1-Q3 2011/12 and a time series dashboard type tool for length of stay and mortality by provider.

5.9 5.3 5.1

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#N/

RXH

RN7 RTP

RYR

RPA

RTK

RXC RVV

0 RA2

As ever, if you have any queries or suggestions for future, please do get in touch! Simon.berry@southeastcoast.nhs.uk

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Pie Bashing… Live and let Pie By Fats Ogunlayi, Quality Innovation and Productivity Analyst Over the years, readers of Knowledge Matters could be forgiven for thinking The Quality Observatory is an active member of The International Pie Bashing club. No, this does not refer to the “wild and wacky game which involves bashing pies to smithereens using a roll of Aluminium foil” but rather a group of Analysts who believe that Pie Charts are never to be used because they fail to convey any information. Happy to say that we are not a member of either group although the former has now got this author thinking hmm! — more on this later. As mentioned in Volume 4 Issue 5, Pie charts are not popular here at The QO HQ because of their limitations and they are very open to abuse but that being said Pie Charts like other graphical representations, do have their place. As Wikipedia puts it, Pie charts can be an effective way of displaying information in some cases, in particular if the intent is to compare the size of a slice with the whole pie, rather than comparing the slices among them. Since Pie Charts cannot be totally abolished, if and when using Pie charts, below are a few tips that would help reduce the amount of abuse Pie charts are currently subjected to. Tip 1: First of all, ask, would this be better simply as a Data Table, Bar Chart, Line Chart...any other charts apart from Pie Chart. This is particular so if the chart is intended to show changes over time (many Pies will be needed). Tip 2: Be careful not to use too many segments in the Pie Chart. More than about six and it gets far too crowded. The example here is a chart from Wikipedia illustrating the United States population by state.

Tip 3: Avoid forcing comparisons across more than one Pie Chart. This particular chart suppose to show how people spend their free time from 2005 to 2010. As people at Peltiertech.com have highlighted, that despite their proximity, each Pie is a separate entity, and reader would have to look at one of them, load that into short term memory, then look at the other, then look back. This is something they compared to a game of Ping Pong.

Tip 4: Like with other graphical representations, avoid unnecessary effects such as 3-D, drop-shadow or lighting. One might ask, why stick to a simple 2-D Pie chart when a third dimension of depth can be added and maybe add a few lighting effect especially since all these features are readily available within the Microsoft Suite or any other Software Package. Answer - Overusing these features more often than not will result in a completely useless chart as the example here shows.

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Tip 5: Never try to do more with pie chart than the Pie could handle. One of the most reasons for misuse or abuse of a Pie Chart is when the Pie is being made to show a lot more information than it can handle. Another example here is from an article called “Saved the Pies for Dessert”, this chart is suppose to show two levels of part-to-whole relationships at one time: one per country (the slices) and one per product type (the circular bands of colour within each country). The author of this article rightly explained that it would be impossible to compare quantities of a product type between countries, given how differently they are shaped.

Tip 6: As mentioned earlier, Pie charts are best when trying to compare parts of a whole and as such the data in a Pie Chart must add up to some meaningful total (i.e. 100% of what you are trying to describe!). This image here is one that have been used in Knowledge Matters before to depict a bad example of pie charts but worth another show. On closer inspection you will find this “pie” is only representative of 67.5% of the whole!

There are so many other tips which the space here does not allow but the very first tip will serve you well. As ever, there is always those friendly neighbourhood Analysts at The Quality Observatory ready to help when deciding the best type of chart for your data.

Back to Pie Bashing…… For the curious Knowledge Matter reader, here are the Rules of International Pie Bashing Club (which currently has 15 members). Please note that we are not advocating joining or participating in Pie Bashing, so much so that we have not provided a web link—you just have Google it yourself if you are that interested... 1. The Umpire's word is final. 2. Official Pie Bashing is a single player sport played against one other opponent. This can obviously translate into a tournament...(there is room for expansion into areas such as communal pie bashing, lone pie bashing and team pie bashing) 3. Bashers must use the same regulation bashing utensil. This should be a value roll of Aluminium tinfoil preferably of the Happy Shopper variety, however it is permissible on themed events such as Moulin Rouge hen night to use a more event sensitive bashing utensil such as a French Stick. The important thing is they are both the same, giving neither basher an unfair advantage. 4. Pies must be of the same size, shape and consistency. By this we do mean to infer that basher can not experiment with different pie suppliers and in fact different food stuffs. 5. Bashing lasts for exactly 10 seconds. Bashers commence and finish on the umpire's signal. False start and failure to disengage bash will result in disqualification. 6. Only bashing and bashing alone is allowed. No flipping, swatting, mashing, squishing, rolling, stabbing, splogging. 7. Pie remnants bashed off the matting area will result in lost points.

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The Winter Dashboard By James Beyer and Alistair Hewson, NHS South of England (West) Each winter, the NHS comes under increased operational pressures and any poor performance or operational difficulties caused by the weather result in increased media and ministerial interest.

To help early identification of rising winter pressures, the Department of Health collect information daily throughout winter on a number of aspects of performance and activity ranging from the number of beds available to the number of operations cancelled; from the number of beds closed due to norovirus (or norovirus like symptoms) to the number of ambulance handover delays.

To assist with monitoring and help pinpoint where the pressures are within our hospitals, we have produced a winter dashboard covering the South of England to bring together all the recognised and measurable pressures within the system.

By bringing together a number of data sources from Unify, Immform, the Met Office and the Health Protection Agency, we were able to create a dashboard that not only shows not only where the operational hospital pressures are, but also an indication of pressures in the wider community, for example Influenza GP consultation rates, and Syndromic speedometers for fever and vomiting (what we like to call the vomitometer). Met Office Cold weather alert status and flu vaccination rates are also presented within the dashboard.

A part of the high Level summary for NHS South of England

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9 The dashboard takes specific measures, such as bed occupancy, cancelled operations, delayed transfers of care and ambulance handovers from the daily winter SITREP, plots the performance over the winter and measures it against the previous year’s performance. GP sentinel data on influenza vaccination rates

The dashboard displays the data at several different levels in order to drill down to any trusts that may be showing signs of worse than expected performance. At the summary level the dashboard looks at NHS South of England performance. The next level down shows a summary of performance issues in each of the component Strategic Health Authorities. Finally, it is possible to drill right down to individual Trusts specific data.

The Trust level summary page

There is also a daily summary page (see above) that lists performance of the key measures, by NHS Trust and NHS Foundation Trust and highlights potential areas of concern in red.

The dashboard is available through the NHS South West performance intranet site: http://performance.xswsha.nhs.uk/SoEWinterDashboard.asp You can sign up to get daily e-mails to tell you when the dashboard is updated by signing up to the mailing list.

The “vomitometer”

If you have any queries or suggestions with regards to how the dashboard could be enhanced further, please do not hesitate to get in touch! James.beyer@southwest.nhs.uk or Alistair.hewson@southwest.nhs.uk

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Innovation Health and Wealth By Samantha Riley, Director of Information for Service Improvement On 5th December, ‘Innovation Health and Wealth, Accelerating Adoption and Diffusion in the NHS’ was published. The demands on and expectations from the NHS are forever increasing, however the current financial climate means that these need to be met without increases in funding whilst at the same time maintaining (and hopefully improving) the quality of care provided to patients. A key focus for the NHS therefore needs to be finding new and different ways to do things and (this is the bit we’re not generally good at) quickly adopting and spreading best practice where evidence demonstrates improvements in cost and quality. Here at the Quality Observatory we know all too well that significant variation still exists across pretty much all areas of services—and of course a key role for us is evidencing this variation so that individuals and teams can reflect on and adapt their practice. A good example of a technique which can improve the quality care received by patients, reduce mortality and save money is Fluid Management Monitoring Technologies (you may know this as oesophageal Doppler monitoring). If this technology were introduced to all eligible patients, it is estimated that approximately 800,000 patients would receive higher quality care and the NHS would save at least £400 million. This technology was recommended by NICE in May 2011 and a guideline published. Here’s the link http:// www.nice.org.uk/nicemedia/live/13312/52624/52624.pdf The Quality Observatory already have a suite of tools which evidence variation in length of stay, and mortality for procedures for which Doppler would be an appropriate technology. These tools are national, were developed in collaboration with the National Technology Adoption Centre and have recently been updated (see page 5 for details of how to access the tools and to learn about future developments. Sir Ian Carruthers led the Innovation Review and the final report sets out a delivery agenda for spreading innovation at pace and scale throughout the NHS. The report also identifies the key barriers to innovation in the NHS (see below). It is interesting to see that a key barrier remains poor evidence to evidence, data and metrics. Although there are no doubt some areas where is it very difficult to measure the impact of different ways of working due to lack of available data sets, I do believe that in many instances there is data which is already collected and which is ‘good enough’ to be used as a starting point for discussion when is comes to delivering services in a different way. Clearly there are many other factors that hamper the diffusion of innovation as even where there is good evidence that a technique or technology works, and data exists which evidences significant variation in quality, efficiency and outcomes (Doppler being a good example), this technique is not universally adopted. This report is very much about action and requires all NHS organisations to build the actions set out into their planning processes, for 2012/13. Page 29 of the report summaries the actions which will be required/taking place over the coming months across a range of headings.

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Here are a few examples of actions which have been identified: -

• • • •

The introduction of a NICE Compliance Regime to reduce variation and drive up compliance with NICE Technology Appraisal; The alignment of financial, operational and performance incentives to support the adoption and diffusion of innovation; The launch of a national drive to get full implementation of oesophageal Doppler monitoring or similar fluid management monitoring technology, into practice across the NHS; From April 2013, compliance with the high impact innovations will become a pre-qualification requirement for CQUIN.

I would encourage you all to read the report which is available to download from the Department of Health website http://www.dh.gov.uk/prod_consum_dh/groups/dh_digitalassets/documents/digitalasset/ dh_131784.pdf

Meet the Observatory— Sister Safety interviews Kiran Cheema So Kiran, how long have you been working at the Quality Observatory? I Joined the SHA around 5 years ago in 2007 from the NHS Work force Review Team. We were the SEC Knowledge Management Team at the time, a lot as changed since then! However I have worked in a lot of different jobs in the NHS! My very first NHS job was working in the Laundry dealing with everything from sheets and blankets to surgical laundry, and occasionally having to doge the instruments that were left in the bags! I have also worked in a Hospital Kitchen organising meal orders and doing the washing up, as a porter and in a national blood service processing lab! And which specific areas of work have you had responsibility for? I am the Workforce Analyst here so have overall responsibility for human bean counting! I manage Aleksandra who now does most of the regular reporting. I have a number of areas of responsibility which are not traditionally related to a Workforce analyst role, I manage the QO budgets, buy the tech, organise training courses, deliver Excel and Access Training and Mentor Analysts “out in the patch”, lead on all our web development, create websites and database applications, maintain our servers, create maps, do most of the QO design work and share the QO Information Governance responsibility with Rebecca…. And probably some other stuff too! What has been your biggest achievement? I like to think that my biggest achievement is yet to come! I ‘m never quite satisfied and am always looking for ways to improve and do things better! It has been a hard lesson to learn but I am now able to put things down and comeback to them later! I had some nice feedback a few weeks ago when I was told that a vba training session I had run had made a huge difference to the teams efficiency and productivity. What do you do when you’re not crunching data sets at QO HQ? Mostly playing with my boys! I seem to be spending a lot of time recently climbing trees, building with Lego, or building train tracks around the house! I do enjoy Mountain Biking and Hiking when I can get away.

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Quality Observatory Christmas Appealâ&#x20AC;&#x201D;please give generously...

Adopt an Analyst Your adoption will include

A gorgeous soft toy of your analyst

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Provide help to a beleaguered analyst from as little as two pints (or wine equivalent) per week. In an increasingly information driven world, your donation can ensure that no analyst goes without love and cake. Remember, an analyst is for life, not just for board reports.

To adopt an analyst, or to find out more about what an analyst can do for you, contact:

And loads more fun & interesting

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Christmas Crossword This Year we have devised a fiendish Christmas Crossword with a Twist! Take the letters in the yellow squares and Un-Jumble them to reveal a Quality Observatory Yuletide Tool! The First person to e-mail back the answer wins a Prize ! 1

4 5 6

7 8

10 11 12 13 14 15

CLUES : 1. 2. 3. 4. 5. 6. 7.

Unwanted side effects of a medical or surgical intervention Discharge destination= 4/admissions Ratio of leavers to staff in post All the returns are brought there together on this Department of Health website The county with the biggest population in NHS South of England Visualization of data Which former South Central PCT did not merge into South of England, but instead became part of NHS Midlands and East 8. Relationship between 2 sets of variables 9. National dashboard including data on pressure ulcers, falls, catheters and VTE 10. Number of Specialist Analysts in the Quality Observatory Team 11. The â&#x20AC;&#x2DC;Vâ&#x20AC;&#x2122; in BCBV indicators 12. Director of Information for Service Improvement for South of England SHA 13. Normal distribution 14. One of two basic data categories/types used in analysis 15. The number of acute trusts in the new South of England cluster (not counting Mental Health, Community or Ambulance trusts)

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Predicting Patient Flow By Jim Hatton, Deputy Director of Information, Nottingham University Hospitals NHS Trust The Nottingham University Hospitals Trust Emergency Department (ED) is on the Queens Medical Centre campus in Nottingham. The department exists to undertake the prompt diagnosis and treatment of all acute emergencies. It provides unscheduled care for an average of 400 patients per day making it one of the largest emergency departments in Europe with over 159,000 attendances per year. In order to assist with discharge and workforce planning, as well as the overall hospital flow, the Trust decided to develop a real time activity prediction tool. To initiate the development of the tool a small analytical team brainstormed the possible factors that could be used to predict attendance at the ED department. These factors included the weather, e.g. mean temperature, ice, snow, fog; air quality e.g. humidity, pollution; seasonality, the day and time; large national events, e.g. the world cup or smaller events, such as the Download festival at Donnington Park. We created a complex regression model using SPSS to test the significance of these factors against attendances to ED. The only significant factors were the day and time. Weather did have an effect, but it was difficult to calculate. For example when the weather is very cold the immediate effect are fractures, then over time more respiratory conditions arrive at ED. Therefore, we decided to look back over 5 years of data and see what proportion each day made of the whole year. Rather than comparing the actual dates, for example the 1st March with the 1st March, we looked at the day number, for example the 1st Friday of the year or the 32nd Tuesday of the year. This gave us the following findings: Figure 1—Normal Day Proportions

Day Number Fri1 Fri10 Fri11 Fri12 Fri13 Fri14 Fri15

2006/07 0.265% 0.283% 0.267% 0.273% 0.268% 0.276% 0.269%

2007/08 0.264% 0.274% 0.264% 0.269% 0.263% 0.261% 0.256%

2008/09 0.267% 0.279% 0.260% 0.272% 0.259% 0.269% 0.270%

2009/10 0.281% 0.265% 0.279% 0.248% 0.260% 0.265%

2010/11 0.263% 0.277% 0.264% 0.272% 0.284% 0.264% 0.271%

Average 0.265% 0.279% 0.264% 0.273% 0.264% 0.266% 0.266%

Standard Deviation 0.00% 0.00% 0.00% 0.00% 0.01% 0.01% 0.01%

For all but a few days there was very little variation between the years. Where there was significant variation we looked to see if there were any other factors that may have influenced the number of attendees. For the table above, the missing date for the 1st Friday in 2009/10 was New Years Day. Therefore, for these ‘special events’ we also looked at the proportions going back 5 years. Figure 2—’Special Event’ Proportions Special Event 2006/07 2007/08 2008/09 2009/10 2010/11 August Bank Holiday 0.269% 0.270% 0.277% 0.278% 0.265% Bonfire Night 0.285% 0.283% 0.271% 0.270% 0.267% Boxing Day 0.269% 0.242% 0.249% 0.292% 0.284% Christmas Day 0.207% 0.219% 0.210% 0.218% 0.213% New Years Day 0.338% 0.301% 0.314% 0.323% 0.335%

Average 0.272% 0.275% 0.267% 0.213% 0.322%

Standard Deviation 0.01% 0.01% 0.02% 0.00% 0.02%

Again for these days, there was very little variation. We are continually adding new special event days, where we find out about local events that may influence the attendances. This enabled us to produce a model based on the previous year’s daily proportions. The data table looks similar to this: Figure 3—The Predictor

Date 01/04/2011 02/04/2011 03/04/2011 04/04/2011 05/04/2011 06/04/2011 07/04/2011 08/04/2011 09/04/2011 10/04/2011

Actual 426 449 491 463 447 443 443 441 482 538

Cumulative attends 426 875 1366 1829 2276 2719 3162 3603 4085 4623

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Day Number Fri1 Sat1 Sun1 Mon1 Tue1 Wed1 Thu1 Fri2 Sat2 Sun2

Prediction Proportion 0.265% 0.277% 0.301% 0.295% 0.272% 0.278% 0.276% 0.274% 0.295% 0.320%

CumProp 0.265% 0.542% 0.843% 1.138% 1.409% 1.687% 1.964% 2.237% 2.533% 2.853%

Yearly Total 160818 161538 162104 160781 161489 161133 161031 161029 161293 162046

Prediction 426 447 488 474 439 448 445 441 476 519

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15 In order to start the model off we used the mean number of attendances for the past 5 years, after this the model self adjusts based on the actual number of attendances. In addition, after each full year the model recalibrates to use the last years data. We are looking at weighting the model so that it uses the most recent years as a stronger prediction. Year to date the model is 0.86% different from the actual numbers of attendances, although some days do vary significantly. In addition to the daily predictor we have also used the same principle to predict hourly rates. We looked at the proportion each hour is of the full day, for each day of the year. The following table shows the proportions for the first 6 hours of the first Friday of the year. Using this information we can Figure 4—Hourly proportions predict the hourly attendances throughout the day and Day compare to the actual. Number

We have combined the daily and hourly predictor Fri1 2.64% 1.85% along with some real time information to provide a planning and operational tool that can be used by clinicians and managers.

02 1.85%

03 0.66%

04 1.19%

05 0.79%

06 1.98%

The top half of the dashboard contains information about the current day’s attendances. The green line in the chart gives the predicted number of attendances at the beginning of the day, the red line is the actual number of attendances and the purple line adjusts the prediction as the day moves on.

Figure 5—Hourly dashboard

Below the chart are a series of measures to show the speed of each flow through the department, in half hour segments. This gives managers information about whether the front or back end of ED is causing issues.

The bottom half of the dashboard is used as a planning tool, particularly for workforce requirements. It shows the predicted ED attendances and also the known elective admissions.

Figure 6—Daily planning dashboard

So…. How do we use the model? The Trust uses the model to plan staffing for busy days and to manage the elective caseload if there is a clash. The model has also been tested at Derby Hospitals and they are achieving very similar results. The model does have to be set up using local data because they are significant variations between Nottingham and Derby and the Trusts are within 20 miles of each other. And what difference has the tool made? Well, our aim was to develop a prediction tool that could be used to assist with long term planning and daily operation information to staff. The model has only been operational for 1 month, but already our performance has improved. The model has been accurate and therefore has been widely used. Further information is used in conjunction with the model, such as if there are going to be extreme weather conditions, but the tool gives a quick indicator to busy days. Next in development is to use the same model for the Medical Admission wards. In addition, we are also going to set up a series of thresholds based on information held in the dashboard and the ED system to automatically trigger an alert to a manager or clinician using Internet Protocol Technology. I’m happy to share the tool with anyone who is interested—here’s my e-mail address Jim.Hatton@nuh.nhs.uk] Merry Christmas everyone!

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Query Sorting 2003-2007 Migration Application: Microsoft Access Dear Quality Observatory I wonder if you can offer any assistance. We have now moved from Access 2003 to Access 2010 and although we mostly use SQL for our queries we still have some complex ones in Access. In some examples we were reliant on using the properties field to know which order to run a series of queries in, we used to be able to sort by property and so therefore effectively have a numbered list appearing on the screen (the comment beginning with the number) which we would use as a guide. In Access 2010 we can see the comment but can’t display them in order on the screen to make the process easy to run – does anyone know how we can do this? Nicola Roberts Information Analyst Information Services Department Musgrove Park Hospital

Solution: Complexity 2/5 — Intermediate Access knowledge

In Excel 2003 the Database Objects Explorer was in a pop out window, which allowed you to view Queries in “Detail View” which would allow you to view all fields in a tabular format

You could order the view by any of the available fields simply by clicking on the field header, which would allow you to order the field by the description field as well as the Query Name.

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However with the change in styling and the “ribbon” view that was introduced in office 2007 the database objects Viewer no longer opens as a window, but has been redesigned into a sliding side bar. (personally I don’t like it but hey!) This redesign means that the view layouts have changed and you can only sort by the fields that the developers have decided that you can sort by. That is Name, Type, modification/ creation dates.

You can however still view the queries in “Detail View” However this is no longer in a tabular format, instead access 2010 uses an extended list style view to display the information.

The best thing to do (and this is best practice too!) when you have several queries that need to be run in sequence is to preface their names with a number, and use the description field for further information. This can be problematic if done retrospectively as you may have forms and other queries that reference each other etc. In this instance where re-naming could be problematic, I would recommend that you look at creating a macro (2010-> create menu -> macro) this will allow you to add actions (in this case OpenQuery) and will apply these actions in sequence which will allow you to run your query sequence with a single click.

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Analysis Ancient, Modern and Future By Katherine Cheema, Specialist Information Analyst The internet is a constant source of wonder and there are loads of tools available through it that can help with so many aspects of analysis, from calculating a chi-square statistic through to finding historical information on deaths. My new favourite analysis gadget is from Google Books; the Ngram viewer lets you chart the incidence of certain words from a body of books (such as British or American English, French, German, Chinese etc.) that the Google Books people have OCR’d, over a prolonged period of time. Enter phrases into the Google Books Ngram Viewer and it displays a graph showing how those phrases have occurred in a corpus of books (e.g., "British English", "English Fiction", "French") over the selected years. Yes, yes, I know that it’s just a sample, that it may not be representative of the whole corpus and that OCR technology isn’t always 100% reliable but stick with me, it’s fun! In the spirit of the season, let’s have a look at ‘Christmas’; the chart above shows y-axis shows is this: of all the phrases (a single word phrase like ‘Christmas’ is called a unigram) contained in Google’s sample of books written in English, what percentage of them are "Christmas”? Looks like authors have been getting more and more Christmas crazy since 1800 but the 60s and 70s rather sapped the festive spirit. Let’s have another play and see if ‘Santa’ shows the same trend. Well, it’s fairly similar but with definite peaks in the 1850s, 1890s, 1910s and 1940s.

I’ll let you draw your own conclusions as to how this reflects on English literary society, and leave you with a chart that goes to show just how important the ‘geeks’ and ‘nerds’ of the world have become in recent decades, or at least more written about; like you didn’t know that already! Have a play with the Ngram viewer yourself at http://books.google.com/ ngrams, the results for ‘NHS’ and ‘healthcare’ are interesting to put side by side, but obviously the possibilities are endless! Quality.Observatory@southeastcoast.nhs.uk

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NEWS Planning Round 2012/13 This year’s planning round is nearly upon us. Local templates have already been sent out to collect high level activity, Finance, Workforce and QIPP plans and these are due back on 6th January. The national templates for performance plans, as detailed in the 2012/13 Operating Framework, will also need to be completed and uploaded to Unify2 by 13th January prior to SHA sign-off on the 27th January. The full technical guidance and list of plans to be collected is now available on Unify2, with a link to all the planning documents available on the front page. Example templates are available on Unify and upload templates with full upload functionality will be available in early January. There will be an opportunity to fully refresh all of the Unify plans in March. If you have any queries on the planning round please email rebecca.matthews@southeastcoast.nhs.uk in the first instance. Enhancing Quality Ist year results celebration On 25th January, the Enhancing Quality Programme will be celebrating their 1st year results. Further details can be obtained from Kay MacKay (kay.mackay1@nhs.net) Olympic torchbearer A member of the Quality Observatory has been selected to be one of the Olympic torchbearers. The individual (who needs to remain un-named at the current time) was nominated as a result of their ‘great leadership, drive and creativity in helping the SHA achieve the Silver award for the NHS challenge and the Inspire Mark.’ Said individual was also commended on their suggestion of the Physical Activity Dashboard to record the efforts of all staff, whatever their chosen activity or ability, to go that extra mile for the NHS. The Quality Observatory is delighted to be part of such an exciting occasion which will of course provide an ideal photo opportunity for a future edition of Knowledge Matters!!!! We hope to be able to provide further details of who the lucky torchbearer will be in the February edition of Knowledge Matters.

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Catalogue Updates: Registrations Open: We have now opened registrations on nww.qualityobservatory.nhs.uk, users can now sign up for an account. Signing up will allow you to use the new features that will be available in the new year site update including posting on the forums and signing up for e-mail alerts when your favourite tools have been updated. We made the decision not to migrate usernames and passwords from the Old KM site as very few seemed to be in active use! New Tools: SSC Tool Go Live : We went live this month with our NEW Data Collection and Analysis system! We have used the system to created the Safer Smarter Care tool, which allows trust users to directly submit data fields and provides instant dashboarding and analysis. National W/F Sickness Tool: We have created a tool based on the Information Centre publicly published Sickness rates data. The tool allows you to view data for all NHS organisations in england Ask An Analyst : We have loaded some of our most recent ask an analysts questions from our newsletter into a single area on our site. we plan to have all our “back issues” up early next year!

Drop In session Dates : The drop in session dates for the next few months are: 18-January 2012 15– February 2012 21-March 2012 18 April 2012 Sessions Are available to all NHS Staff Across the patch who want to improve their skills or need help with a development. Group or individual sessions are available. Worried about Travel? Don’t be we can do virtual “At Desk” sessions via Skype or WebEx! E-mail us to book your session.

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Quality Observatory Christmas outing….. On 16th December the Quality Observatory celebrated Christmas with a Christmas Treasure Hunt in the historic city of London. The two teams (led by Kiran and Fats) were required to work through a series of cryptic clues, collect a range of different items on route and take a variety of photos with members of the team in different poses. To the right we see ladies dancing, the photograph on the right depicts lords a leaping. Alex and Adam are on a scary sleigh ride….. And finally we see Mr and Mrs Cheema under the mistletoe (yes, that is a sprig of mistletoe in Kate’s hand!)

Mistletoe

Fascinating Facts

Hug an Analyst Today……... Have you seen your analyst looking all pale and wan, Affix'd to their computer, never seeing the sun, Gazing at their data, checking every number, Looking out for troughs and peaks, without recourse to slumber. Deadlines come and deadlines go - all met with charts and tables,

*********

All correct and proper with titles and with labels. Filling days with endless hours of tireless crunching data, From dawn to dusk running queries (sometimes even later!) Your analyst works hard to give you meaningful support, Facts for every meeting, and evidence for your report. To keep your analyst happy and from making a mistake, You must make sure they're fully fuelled with beer and with cake. Do not let your analyst feel glum or too downhearted, Give them something interesting, let them finish what they've started. If you see an analyst looking sad and worn away, Then you must do your duty and hug an analyst today!

Christmas can be a dangerous time of year according to RoSPA, 1,000 people a year are injured in Christmas Tree incidents, a further 1,000 also receive injuries from decorations. Fairy Lights alone account for 350 injuries a year! We all know there is a tradition of drinking a touch too much alcohol over Christmas – this isn’t a new phenomenon. Wassailling goes back to the Vikings and Normans. Initially an innocuous form of carol singing it grew into a tradition of bands of youths roaming from house to house drinking to the good cheer of the house-owners, (and demands for Figgy pudding). If only we had mediaeval daily SITREPs to show the burden on the health economy of the time!

Knowledge matters is the newsletter of NHS South East Coast’s Quality Observatory, to discuss any items raised in this publication, for further information or to be added to our distribution list, please contact: NHS South East Coast York House 18-20 Massetts Road Horley,Surrey, RH6 7DE Phone:

01293 778899

E-mail: Quality.Observatory@southeastcoast.nhs.uk To contact a team member: firstname.surname@southeastcoast.nhs.uk