Volume 5 Issue 4 October 2011 Welcome to Knowledge Matters You may notice a slightly different look to Knowledge Matters this time……… On 3rd October, NHS South East Coast, NHS South Central and NHS South West clustered to become NHS South of England. I have been lucky enough to obtain a really exciting role within the new organisation as Director of Information for Service Improvement. This new role provides a great opportunity to spread a number of key tools that have been developed in different parts of the South over recent years to a wider geography and increase our opportunity to benchmark against a greater number of organisations. Along with colleagues in South Central and South West we are currently in the process of gaining access to SUS for the whole South which will enable future updates of selected tools and products to cover the whole of the SHA Cluster. Early priorities will be identifying where duplication of effort currently exists and sharing skills and expertise between the pooled analytical resource across the South to ensure that we maximize this expert team over the coming 18 months. Lots of activity is currently underway to provide information and analysis to inform a number of ‘stock takes’ focused on a range of clinical and geographic areas. Over the coming weeks, I will be identifying with colleagues based in Newbury and Taunton the quality and safety indicators which are currently utilised—this in turn will inform work to specify a balanced set of quality and safety measures for regular review. The Quality Observatory were of course very sad to bid a fond farewell to Candy Morris who has been a greater supporter of the work of the Quality Observatory over recent years (and an avid reader of Knowledge Matters). To mark Candy’s departure, a special Quality Observatory mug was ordered for Candy and a good bye poem constructed by our in-house poet which appears on the back page. Thanks Candy—we will miss you! Key points to draw your attention to in this issue are: the publication of the Summary Hospital-Level Mortality Indicator, the current consultation on the Fundamental Review of Data Returns, the launch of free-to-use on-line learning resources for knowledge management and the recent launch of a mentoring scheme for informatics professionals. And for those of you intrigued by my unusual September holiday, turn to page 9!
Inside This Issue : Summary Hospital-Level Mortality Indicator Published
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Skills Builder
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Ask an Analyst
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Variation in Outcomes Competition Results
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Jailbreak—the Prison Health Dashboards
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Tip of the Month
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VTE Dashboard
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Enhancing Quality Update
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Calling Informatics Mentors and Mentees
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Knowledge Management Modules
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PbR Benchmarker Update
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Analysis Ancient & Modern : Farr-sighted
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Summary Hospital-Level Mortality Indicator published By Samantha Riley, Director of Information for Service Improvement The new Summary Hospital-Level Mortality Indicator (SHMI for short) was published by The Information Centre on Thursday 27th October. The SHMI was introduced following the recommendations of the Francis Inquiry, after an independent working group was established to review the methodology for calculating Hospital Standardised Mortality Ratio (HSMR). A number of organisations were involved in developing the SHMI, including the Academy of Royal Colleges, the Care Quality Commission, the NHS Confederation, Dr Foster Intelligence, CHKS and the National Patient Safety Agency. The new indicator is different to other mortality indicators that you may be familiar with (e.g. HSMR and RAMI) in that it covers all deaths of patients admitted to hospital that occur in a hospital setting, and those that occur up to 30 days after discharge from hospital. The Information Centre published the SHMI data on it’s website and will be updating and publishing the data on a quarterly basis. Information can also be accessed via the NHS Choices website. The SHMI is being published as ‘Experimental Statistics' which are new Official Statistics that are under going review. Like all indicators managed by the NHS IC, the SHMI will be subject to continuous review, using the Indicator Assurance Process. What is really important is that the SHMI is not used in isolation. Instead it should be used alongside a balanced set of quality and safety indicators to provide a broad picture of the quality and outcomes of care delivered within a hospital. Clearly a ‘poor’ SHMI will require further analysis to gain a greater understanding of what is driving this—it should be a starting point for discussions rather than cause for an immediate judgement to be made. Another way in which the SHMI should definitely not be used to compare hospitals in a ‘league table’. Over the coming weeks there will no doubt be lots of work undertaken to compare the results of the SHMI with mortality information which was previously used. The Quality Observatory will be undertaking an analysis of SHMI results for all Trusts in the South of England—we’ll include an article on our findings in the next edition of Knowledge Matters. For those of you wanting to compare existing mortality information that you may have access to compared to SHMI, you may find it useful to know that back in January Dr Fosters published a guide to SHMI which can easily been found via Google. In addition, CHKS have developed a 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 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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Innovation in Outcomes Competition Results By Samantha Riley, Director of Information for Service Improvement Back in March, the Health Secretary, Andrew Lansley, launched the Innovation in Outcomes Competition. The purpose of the competition was to stimulate discussion and gain ideas about new indicators which provide meaningful information about health outcomes. There were clear criteria applied to the judging of competition entries—one of which was that the burden of collecting additional information should be minimal, and ideally indicators would be constructed from existing electronic data sets. By launching the competition, it was hoped that entries would be received which filled some of the current gaps in the Outcomes Framework. For those of you who have read the document in detail, and are familiar with the datasets which are currently available to describe NHS care, you will be aware that there are in fact a relatively small number of outcome indicators which can currently be populated from electronic data sources. A priority for the competition was to identify ways of measuring two key outcomes : improving people’s recovery from stroke, and improving children and young people’s experience of healthcare. The Quality Observatory submitted 12 entries to the competition (just over 80 entries were submitted in total) and I am pleased to report that we were a contributor to the winning indicator for stroke. The following organisations were part of the collaborative winning entry: -
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the British the British Association of Stroke Physicians the Stroke Improvement Programme the Intercollegiate Stroke Working party the Royal College of Physicians of London Joint Specialty Committee for Stroke Medicine the South East Coast Quality Observatory, and the Cardiac and Stroke Networks in England
The winning entry (which will become part of the routine data collection for stroke) proposed that the Modified Rankin Scale (mRS) should be developed as an indicator. This indicator uses the mRS to assess the patient’s recovery from stroke after six months. The winner for the ‘children and young people’s experience of healthcare’ category was the Picker Institute Europe, and involved using the Children’s Outpatient Experience Indicator. The indicator will measure the recent hospital outpatient experience of children aged 8 to 17 years and will compute a single indicator score from responses to questions about aspects of the hospital outpatient experience. All entrants to the competition were invited to a reception on 10th October at Church House Conference Centre in Westminster which was also attended by the Health Secretary, Andrew Lansley. A number of members of the Quality Observatory attended the reception and had the opportunity to discuss with Mr Lansley the vital role that Quality Observatories across the country play in measuring health outcomes. You may notice that Mr Lansley is holding the August edition of Knowledge Matters—it remains to be seen whether we have gained a new reader! Further work will now be undertaken by the Department of Health to consider which other entries should be incorporated into the Outcomes Framework—we’ll feature further detail in Knowledge Matters on this as and when it becomes available. Both the stroke entry and the children and young people entry will now undergo some additional technical work to ensure they can be included in the national NHS Outcomes Framework.
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VTE Dashboard By Adam Cook, Specialist Information Analyst The South East Coast patient safety programme focuses on working with all areas of healthcare provision and commissioning to ensure safe care for all patients and support organisations in their ongoing improvement work. Part of the programme focuses on the effective use of measurement and information to assist all stakeholders in identifying areas for improvement, sharing best practice and recognise success. One aspect of this is the data generated by the local VTE dashboard. This looks at the data that has come out the clinical coding that goes from the trust PAS, then into SUS, and ultimately HES, feeding PbR on the way. The VTE dashboard can be viewed either by trust or by indicator. There are 4 indicators that make up the data collection 1. Rate of VTE: all episodes that have a VTE coded in any of the first 16 diagnostic positions are shown as a rate per 10,000 total episodes 2. Deaths in episodes containing VTE: this shows all episodes with a coded VTE (as above) which also have a discharge method code of “4� (died). Again this is shown as a rate per 10,000 episodes 3. Average episode duration: The difference between episode start and end dates is calculated for all episodes with a VTE. Then the mean episode duration is shown. 4. Average PbR value per episode: The episode HRG is used, in combination with admission method and length of stay, to calculate an episode tariff for each episode containing a VTE. The mean episode PbR value is then shown. For each of the above 4 measures the South East Coast value is also displayed along with 95% confidence limits around this value. Seen in pink in the charts below. All data is sourced monthly from the SUS extract mart. The alternative view shows all 12 acute trusts on one page and can be used for benchmarking. Episodes were chosen rather than spells as the unit of measurement because it was recognised that VTEs can develop within any episode and it many could potentially be missed if spells were used. In theory there are limitless numbers of diagnostic positions that it would be possible for a VTE to be found in however on initial analysis it was discovered that there were none beyond the 16th diagnostic position. This was therefore decided to be the cut off point in order to reducing some of the processing time of the analysis. Also there are so few episodes with any diagnosis at all beyond this point that the risk of missing any future VTE episodes is negligible. ICD-10 clinical codes were used as a basis for this analysis. This list of these codes were taken from a list that was on the website of Lifeblood: The Thrombosis Charity. They are as follows: I260 I269 I800 I801 I802 I803 I808 I809 I821 I828 I829 O223
Pulmonary embolism with mention of acute cor pulmonale Pulmonary embolism without mention of acute cor pulmonale Phlebitis/thrombophlebitis superfic vessels low extremties Phlebitis and thrombophlebitis of femoral vein Phlebitis/thrombophlebitis oth deep vessels low extremties Phlebitis and thrombophlebitis of lower extremities, unspec Phlebitis and thrombophlebitis of other sites Phlebitis and thrombophlebitis of unspecified site Thrombophlebitis migrans Embolism and thrombosis of other specified veins Embolism and thrombosis of unspecified vein Deep phlebothrombosis in pregnancy
The dashboard is available from our website. If you have any queries, please do get in touch! adam.cook@southeastcoast.nhs.uk
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Knowledge Management modules By Katherine Cheema, Specialist Information Analyst Here at Quality Observatory Towers we always espouse the view that ‘Knowledge’ is much more than just the numbers and that statistics and quantitative analysis are but a part of the whole knowledge management picture. But often we find that the term Knowledge Management becomes confused with information management and analysis. The recent launch of the free-to-use Online Learning Resources for Knowledge Management will banish this confusion forever! The resources have been jointly developed by the Department of Health Informatics Knowledge Management Team and NHS Library and Knowledge Services, Kent, Surrey and Sussex and are suitable for use by all NHS staff and are designed to help:
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Develop a strategy for knowledge retention and sharing Plan how an individual, team or organisation can learn from the experience of others Capture, share and preserve resources from individuals or teams Record and share learning and experience gained from projects or work Understand how knowledge management techniques have helped other organisations
Any individual can select the modules that most suit their learning needs and interests. Each module lasts between 15 and 40 minutes, so the entire content can be undertaken at a pace that suits you! There are 12 modules available, some of which include contributions from the Quality Observatory, which include:
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Introducing Knowledge Management Introducing the Knowledge Management Framework After Action Reviews Building Knowledge Through Connecting People Knowledge Harvesting
I feature in two videos—one describing the Quality Observatory approach to measuring quality and the other describing joint work undertaken between the QO and the Library Team at Maidstone and Tunbridge Wells Trust on MRSA. The easy to use front end (just point and click!) enables users to access learning content through a range of formats including video and slide shows, with a few familiar faces on the bill! To access the resources on offer, simply point your browser to www.ksslibraries.nhs.uk/elearning/km to get started straight away. Each module provides a feedback form so you can share your immediate thoughts and suggestions with the development team. www.QualityObservatory.nhs.uk
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“A picture is worth a Thousand Words” By Kiran Cheema, Workforce Analyst PART 2 - Keeping it simple—the Importance of style When presenting ideas that include references to data, it can be helpful to make the point using a graph or table. These visual methods can make the point much stronger than simply describing the data. Charts can help people understand data quickly, making comparisons, showing relationships, or highlighting trends, they help your audience "see" what you are talking about. While they can be powerful methods, they also have the potential to convey the wrong message or they confuse the audience. In the last issue we looked at choosing the right type of graph for the data you are looking at, this issue we will be looking at something just as important … styling your graphs. It may seem obvious but if your graph looks easy to understand and interpret people will engage with the data you are trying to display. There are a number of different models that have been developed to help us understand how people interpret data , and if we can get to grips with them should help us to present our data in a way that engages our audience.
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people reading the graph must cycle between the different parts in order to understand it.
This makes some sense: to answer our question you'd have to look back and forth between the legend ,the axis and the colours on the graph.
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how we read graphs depends on the question we are trying to answer
We'd answer a “WHAT is the” or “HOW many X” question differently than "How is X distributed across the groups or HOW does X compare to Y". The first question just asks graph readers to extract information from the graph, while the second question demands that readers integrate information from the entire graph, building an understanding of relationships between its parts. Research has been carried out looking at the way people interpret information. One study lead by Raj Ratwani showed people graphs and asked them to talk through the answers to a number of questions, they also used eye tracking to look at the way eyes move when reading graphs, counting the number of movements it takes to read different types of graph and timing how long it takes to interpret the data. The study found that reasoning was indeed different for different types of questions. For questions that required extraction of basic facts most people could answer straight away, or with some searching the graph before answering. For questions that required integration of data very few people could answer straight away, most people spent time getting more information, building patterns and rethinking their answers. The study also used eye tracking to understand what people were looking at when they answered the questions. This showed that for simple questions the majority of eye movements (around 50%) were spent moving between the data series and the legend with only 5% of movements between data series. With more complex graphs and integrative questions the total number of eye fixations increased; the percentage of data series to legend movements had reduced slightly to 40% with the number of movements between data series increasing to 20%. This research concluded that graphical interpretation occurs in 2 stages. The first is visual integration : figuring out what each bit of the graph is. i.e. which data series go together with which legends. The second stage is cognitive integration which is figuring out the relationship between each data series.
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7 QO Rules of Thumb . . . Spend Time:- It's worth spending some time on as there is more than a little art to it and your approach will vary with the data and what you are trying to communicate.
Think about Colours:- Use colour schemes that make the differences between groups clear: Use lots of different colours, not just shades of grey to indicate different groups. Shades of the same colour (colour ramps) could be used to clearly indicate varying degrees of more than one variable on the same graph, colour ramps should be used with care since a portion of your audience will be colour blind. Remember to use a different colour scale per variable! Try to choose schemes that will read reasonably well in colour, in black and white, and possibly for the colourblind (3 different issues).
Some Colour has meaning :- One very well understood colour scheme is Red Amber Green. These colours have meaning! i.e Red is Bad and Green is Good! Try and avoid these unless you are trying to get this point across!
Keep it consistent:- Make the relationship between the legend and the items on the graph obvious using consistent colours throughout. That is use the same colour for that variable. Or if you are creating a variety of graphs showing, for example, actual values and plan values use the same colours on each graph.
ONLY SHOW WHATS IMPORTANT !:- Remove extraneous markings and colours . While it is easy to add borders, background colours, 3D effects, multi-coloured bars and interesting marker points to your graph these will all impact in the time taken to interpret the data. If you have put a green background on the graph your reader will need to interpret and understand the meaning of the green background and if it has no meaning and is purely decorative, why use it at all? 1 0.9
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A few references for further reading ‌ http://www.typesofgraphs.com/ http://www.mindtools.com/pages/article/Charts_and_Diagrams.htm http://www.upassoc.org/usability_resources/conference/2007/prp_049.pdf http://www.statcan.gc.ca/edu/power-pouvoir/ch9/5214821-eng.htm Raj M. Ratwani, J. Gregory Trafton, Deborah A. Boehm-Davis (2008). Thinking graphically: Connecting vision and cognition during graph comprehension. Journal of Experimental Psychology: Applied, 14 (1), 36-49 DOI: 10.1037/1076898X.14.1.36 Tufte, E.R. (1983) The Visual Display of Quantitative Information. Cheshire, CT. Graphics Press.
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Jailbreak—the Prison Health Dashboards By Adam Cook, Specialist Information Analyst The NHS has a commitment provide quality healthcare for everyone in the community, and that includes those people who are currently serving time at Her Majesty’s pleasure. For healthcare the prison population is quite different to that of the wider community, the male to female ratio is vastly different, they are more likely to suffer from drug and alcohol dependency problems, and there is a greater proportion of people with mental health difficulties, and these things are on top of the normal physical health problems that can afflict any of us at any time. There is a tool for measuring the quality of prison healthcare which has been running for a few years now. This is called the Prison Health Performance and Quality Indicators – The PHPQI. Initially this was made up of about 30-40 indicators. These were asked annually and graded according to very specific criteria on a Red Amber Green scale. More recently a couple of quarterly additions have been made to the collection. These detail a number of measures around Hepatitis B and Hepatitis C vaccinations, and also around Mental Health. Although quarterly the vaccinations data is broken down by month which enables a much more granular view of the information. The data for both of the quarterly submissions is less complete, but whether that is down to poor data quality, or the prisons in question not providing these services is still something that needs to be examined in more detail. Across Kent, Surrey and Sussex there are 18 prisons. They hold a variety of categories of prisoners, although none of them are high security. There are a couple of the 18 that house young offenders, and 4 that are for women. One of the prisons is privately run. Using the aforementioned PHPQI data we have built two dashboards that display the data. One dashboard enables the user to select a prison and the range of indicators will be displayed for that prison. The other dashboard is for benchmarking purposes and enables selection of a single indicator displayed for all 18 prisons.
For the annual PHPQI information the data is shown in the submitted RAG format, and can be viewed on one page showing the four years worth of indicators have been collected. This helps with evidencing improvement of services over time. Also on the Prison selection dashboard beneath the main table is displayed a link to the latest Inspection Report from HM Chief Inspector of Prisons, plus the summary paragraph from the health section of that report, which helps to provide deeper context for the data.
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9 The Hepatitis B & C vaccination return provides information on testing and vaccination uptake. There are 11 measures, which are comprised of the raw numbers and percentages derived from those numbers. The mental health returns provide quarterly numbers of people assessed and transferred, plus total numbers of prisoners on CPA.
Data for the Benchmarking dashboard is presented in a similar fashion – a table for the annual indicators and a suite of charts for the quarterly data. We are currently exploring the possibility of adding additional metrics from Drug & Alcohol Action Teams (DAATs) and from the National Offender Management Systems (NOMS).
Both dashboards are available now to download from the Quality Observatory resource catalogue on the website. http://nww.qualityobservatory.nhs.uk/ If you have any questions about this information then please contact me! adam.cook@southeastcoast.nhs.uk
Sam’s Unusual Holiday……. (…….. If you can call it a holiday!) At the end of September, Samantha spent five days at a fitness Boot Camp in Dorset run by an ex-Paratrooper. A range of challenging activities were experienced during the week (which by the way had perfect weather). Highlights included ‘casualty evacuation’, boxing (Sam reportedly has a very good upper cut so watch out!) and Cross Fit Challenge (don’t ask). Most days commenced with a run up a mountain and then an intensive session of circuit training.
Venue for Boot Camp
By the end of the week, Sam could run 1.5 miles in 10 minutes 30 seconds and complete 21 press ups in 60 seconds. Even better was the 1 cm reduction from each upper arm and an impressive 2 cm reduction from each thigh!! It wasn’t just about fitness, there were also sessions on nutrition and motivation, the former of which has transformed Sam’s eating habits and resulted in ‘snack corner’ becoming rather more healthy and the selection of herbal tea available to the team growing significantly. Caffeine and bread are now on the banned list! There is a short video of the week—here’s the link! http://www.youtube.com/watch?v=EQ0yY99AJW8&feature=share
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Enhancing Quality and Recovery Programme Update By Kay MacKay, Director, Enhancing Quality and Recovery I talked last time about the fact that it is relatively early days for the Enhancing Quality Programme. Success and impact can be measured by achievement on the following fronts. Clinical engagement and action Over 1000 clinicians have attended the EQ Collaborative learning events. There are clear examples of where practice and culture have changed. For example, at the beginning of the programme only 1:10 patients across South East Coast were receiving the full Heart Failure care bundle whereas by February 2011 4:10 patients received this care.
Validation and benchmarking of clinical quality Clinical care has been measured for more than 16,000 patients across Kent, Surrey and Sussex. The fact that EQ offers external validation and benchmarking of clinical quality is becoming increasingly valuable for Foundation Trusts as Monitor looks for this corroboration. Anticipating future priorities The national respiratory team has recognised the value of the EQ pneumonia data and especially the linkage between clinical measures and outcomes. Pneumonia is about to take centre stage as a top priority for respiratory teams. The national kidney team is very supportive of EQ’s latest pathway, Acute Kidney Injury (AKI), which shows massive potential to deliver the QIPP agenda. Highlighting and reducing variation Data analysis has clearly identified variations across the region on all care pathways for which data is being collected. This has shown that no single Trust appears in the top quartile for all pathways or the bottom quartile. This shows potential opportunities for higher performing teams to share their knowledge and experience with other teams as well as with other specialist teams across the region. The organisation and presentation of this data by the SEC Quality Observatory has been universally applauded. While at an early stage the comparative data and trends already becoming visible on outcomes such as length-of-stay, in-hospital deaths and readmissions, for example, are providing very powerful information for clinicians and senior executives to focus improvement efforts. Quality.Observatory@southeastcoast.nhs.uk
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11 Driving innovation and knowledge spread As a direct response to the EQ Heart Failure pathway clinicians working for Western Sussex Trust have been successful in establishing a dedicated heart failure unit. While not all heart failure patients will be situated within this unit all of the time it will provide a focus for activity. Sharing their achievement in setting up this unit at the 3rd Heart Failure Collaborative has provided the impetus for another cardiac clinical team to push forward for a similar dedicated unit. Another example of innovation is around the critical connections between settings an acknowledged weakness in the NHS. Ashford & St Peters Hospitals Foundation Trust held a 3-day Rapid Improvement event for Heart Failure along with Surrey Community Health. This has resulted in an agreement to produce an integrated care pathway for Heart Failure and to put forward a business case for recruitment of a specialist Heart Failure nurse. The event was so successful that a subsequent event is being planned for Pneumonia.
Meet the Observatory— Sister Safety interviews Simon Berry So Simon, how long have you been working at the Quality Observatory? I guess I'm the founder member of the Quality Observatory as I started working as a service improvement analyst at the SHA way back in 2005. There’s been lots of changes since but it’s great to be part of such a fantastic team. And which specific areas of work have you had responsibility for? What has been your biggest achievement? My current areas of responsibility include planned care and urgent and emergency care as well as a range of other things. It’s quite varied; one day I could be crunching big A&E data sets, the next building models to reflect the nuances of capacity management and patient flow. I’m not sure what my biggest achievement is, but I’m pretty proud of the A&E System for Optimisation of Performance (AESOP) which continues to be really useful to the service. I also really enjoyed creating the national analysis around Oesophageal Doppler for the National Technology Adoption Agency and of course the analysis suite around length of stay for hip replacement. What do you do when you’re not crunching A&E data sets at QO HQ? I enjoy cooking and have been known to indulge in a glass or two of fine wine. I also like to travel and have taken the opportunity to complete my fundamental scuba diving courses. With other members of the team I also provide mechanic services to Samantha when her car breaks down or lights need changing!
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PbR Benchmarker update By Howard Davis, Senior Manager for Health Benchmarking, Audit Commission Over the last year the Audit Commission has updated its online tool with some powerful and exclusive analysis, writes Howard Davis. Having already provided over 60 PbR related indicators covering inpatient, outpatient and A&E data, we have added three reference costs benchmarking tools, and some unique population based analysis to benchmark volumes of activity. Our National Benchmarker is a powerful online tool that compares acute hospital activity data, clinical coding and Payment by Results (PbR) related measures with other organisations. Originally conceived to target the audits undertaken as part of the Commission’s PbR data assurance framework, the benchmarker can be used to inform many areas of your work: efficiency and productivity, contracting, information, service redesign, quality accounts and data quality in general. Our recently released volume analysis identifies exceptionally high or low volumes of hospital activity, and estimates the financial impact of this over or under performance. Whilst extreme outliers are often caused by clear data quality issues, this tool also provides intelligence to support commissioning decisions around potential over or under-provision of care. The volume analysis uses a PCT population to indentify outliers, and data can be viewed by PCT or by trust. We spotlighted the volume analysis in our latest benchmarking report, the PbR Data Focus Report. The report brought together the key messages from the different types of analysis available in the PbR National Benchmarker online tool and aimed to identify the key issues for a PCT by highlighting areas with high financial impact. An individual report was sent to each Director of Finance at PCT and trust in the country. Feedback to the report has been very positive. One assistant director of commissioning said, “I have to say this is one of the most useful reports that I have ever received - just what we need. We were discussing the other day how we could produce something very similar – now we don’t have to!” We also released a suite of reference costs benchmarking tools. This analysis was used by auditors to target their investigations during our national audit of reference costs last year. One of the main causes of poor reference cost identified in our audits was the lack of checking submissions against comparative sources. In our annual report we recommended that trusts and PCTs use the National Benchmarker to explore costs and activity to ensure the levels of activity they are commissioning are reasonable for their population, and they are receiving value for money in their local contracts. The tools we have provided are: Cost variance tool - looks at differences between reported and expected unit costs for each treatment area.
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13 Activity reconciliation tool - compares activity data submitted in reference costs to activity reported in Hospital Episode Statistics (HES). Activity share tool - looks at whether a trust is undertaking its expected share of activity for its size. The national benchmarker is freely available to all NHS organisations in the country. It provides detailed analysis of hospital data to allow local health economies to compare themselves against an expected level of activity based on the type of patients they have. It is user-friendly and easy to use, providing access to detailed analysis in a simple format suitable for all staff types: analysts, managers and clinicians have all benefited from using the national benchmarker. We know the benchmarker is valued by its users. FTs have used the tool to identify where the failure to code pathology tests was leading to an under-payment for general medicine. PCTs have used key indicators not available elsewhere to identify data quality issues which, when resolved, have substantially reduce contract payments. And clinicians have integrated the use of the tool into the training of junior doctors to help them understand the importance of accurate coding for funding and epidemiological purposes. Last year we conducted a survey of users approximately a year ago aimed at identifying how often they used the benchmarker, what they used it for and identifying areas for improvement. Of those who responded, 50% said they used the benchmarker regularly (quarterly, monthly or weekly). More than 50% of users rated the benchmarker as a 4 or 5 on a scale of 1-5 for effectiveness in helping them with their work (where 5=excellent). 90% rated it 3 or above. We will continue to maintain and update it as long as the PbR assurance framework is in existence
For more information and to request a log-in just visit www.audit-commission.gov.uk/pbrbenchmarking. If you would like to discuss how the benchmarker could provide further benefit to your organisation please feel free to email me at h-davis@audit-commission.gov.uk.
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Advanced Filtering Application: Microsoft Excel Dear Quality Observatory I need to filter out certain rows from a large spreadsheet of data using three different criteria. Using Custom AutoFilter in Excel 2003 will only allow for two to be entered. Is there a way to filter the data on more than two criteria? An Administrator A Trust in South East Coast
Solution: Complexity 2/5 — Intermediate Excel knowledge Instead of using AutoFilter, try using Advanced Filter. Before you start, make sure all columns in your spreadsheet have headings that are unique and decide which columns you wish to use for your criteria. Here we will choose Month, Specialty and Hospital Provider. Copy those headings to a different part of the same spreadsheet and underneath enter the criteria you wish to filter on (the cells need to match exactly so it’s a good idea to copy and paste from your data table if possible, rather than type freehand). Let’s say we want to filter on Apr-11, ENT and Provider 4. This is what our ‘criteria range’ will look like:
You can add further criteria underneath and if, for example, you also wanted to see all details for Urology in addition to the above, just enter Urology underneath ENT. Excel will then filter out any rows containing Apr-11, ENT and Provider 4 and also all rows for Urology. You can also enter criteria such as “>=Nov10” but you need to make sure these appear in quotation marks, so that Excel doesn’t think you’re entering a formula. Now decide where you would like your filtered results to appear. This can be ‘in place’, similar to the way AutoFilter works, or you can ‘pull’ the relevant rows into a completely new table (leaving your main data table intact). To filter in place, click anywhere in your main data table and select Data, Filter, Advanced Filter and the following box will appear: You will see the List Range has appeared automatically. Now you need to enter the Criteria Range by clicking the select range icon and highlighting the range of cells where you previously entered your chosen headers and criteria. Click OK and only rows meeting your criteria will remain visible in your data table (to see all rows again, click on Data, Filter, Show All). To get your filtered rows to appear in a separate table, repeat the above steps but this time click on ‘Copy to another location’. If you click on the select range icon next to ‘Copy to’ and then onto the first cell where you want your results to appear, then all columns will be included in your result. If you don’t want to see all columns from your main data table then copy just the headers you need to the area where you want your results table to appear. When you have pasted all your chosen headers, this range of cells should be entered in the ‘Copy to’ field (using the select range icon again). Click OK and all rows matching your criteria will appear underneath your chosen headers. As always if you have any queries or need further help please contact us at: quality.observatory@southeastcoast.nhs.uk
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Tip of the month—the Stacked Bar Chart The stacked bar chart has its place in the analyst’s toolbox, however, it is also one of the most abused and misused, especially when combined with 3D. There is always a temptation to cram as much information into a chart and the stacked bar allows you to do this, unfortunately in the process it is very easy to actually obscure what you are trying to provide. Take this as an examADQ Usage Seretide inhalers Seretide Accuhaler 100mcg Total ADQ Usage Seretide Accuhaler 250mcg Total ADQ Usage ple…………………... Sertedide Accuhaler 500mcg Total ADQ Usage Seretide Evohaler 50mcg Total ADQ Usage Seretide Evohaler 125mcg Total ADQ Usage
Even simplifying the chart to show just one practice, the picture is clearer, but aside from being able to make some
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0 Practice A Practice B Practice C Practice D Practice E Practice F Practice G Practice H Practice I Practice J Practice K Practice L Practice M Practice N Practice O Practice P Practice Q Practice R Practice S Practice T Practice A Practice B Practice C Practice D Practice E Practice F Practice G Practice H Practice I Practice J Practice K Practice L Practice M Practice N Practice O Practice P Practice Q Practice R Practice S Practice T Practice A Practice B Practice C Practice D Practice E Practice F Practice G Practice H Practice I Practice J Practice K Practice L Practice M Practice N Practice O Practice P Practice Q Practice R Practice S Practice T Practice A Practice B Practice C Practice D Practice E Practice F Practice G Practice H Practice I Practice J Practice K Practice L Practice M Practice N Practice O Practice P Practice Q Practice R Practice S Practice T Practice A Practice B Practice C Practice D Practice E Practice F Practice G Practice H Practice I Practice J Practice K Practice L Practice M Practice N Practice O Practice P Practice Q Practice R Practice S Practice T Practice A Practice B Practice C Practice D Practice E Practice F Practice G Practice H Practice I Practice J Practice K Practice L Practice M Practice N Practice O Practice P Practice Q Practice R Practice S Practice T
This chart shows for 19 practices, across 5 financial years totals for 6 different items stacked. You can see that it is almost impossible to see what is going on in the noise! What does this tell you? Very pretty, but very difficult to conclude anything from this representation of the data……...
! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial ! Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial Financial ! Financial ! Financial ! Financial ! Financial 2006/2007 2006/2007 2006/2007 2006/2007 2006/2007 2006/2007 2006/2007 2006/2007 2006/2007 2006/2007 2006/2007 2006/2007 2006/2007 2006/2007 2006/2007 2006/2007 2006/2007 2006/2007 2006/2007 2006/2007 2007/2008 2007/2008 2007/2008 2007/2008 2007/2008 2007/2008 2007/2008 2007/2008 2007/2008 2007/2008 2010/2011 2010/2011 2010/2011 2010/2011 2010/2011 2010/2011 2010/2011 2010/2011 2010/2011 2010/2011 2010/2011 2010/2011 2010/2011 2010/2011 2010/2011 2010/2011 2010/2011 2010/2011 2010/2011 2011/2012 2011/2012 2011/2012 2011/2012 2011/2012 2011/2012 2011/2012 2011/2012 2011/2012 2011/2012 2011/2012 2011/2012 2011/2012 2011/2012 2011/2012 2007/2008 2007/2008 2007/2008 2007/2008 2007/2008 2007/2008 2007/2008 2007/2008 2007/2008 2007/2008 2008/2009 2008/2009 2008/2009 2008/2009 2008/2009 2008/2009 2008/2009 2008/2009 2008/2009 2008/2009 2008/2009 2008/2009 2008/2009 2008/2009 2008/2009 2008/2009 2008/2009 2008/2009 2008/2009 2008/2009 2009/2010 2009/2010 2009/2010 2009/2010 2009/2010 2009/2010 2009/2010 2009/2010 2009/2010 2009/2010 2009/2010 2009/2010 2009/2010 2009/2010 2009/2010 2009/2010 2009/2010 2009/2010 2009/2010 2009/2010 2010/2011 2011/2012 2011/2012 2011/2012 2011/2012 2011/2012
guesses over total volumes it requires some effort and concentration to actually see what is going on with individual items.
ADQ Usage Seretide inhalers Seretide Accuhaler 100mcg Total ADQ Usage Sertedide Accuhaler 500mcg Total ADQ Usage Seretide Evohaler 125mcg Total ADQ Usage
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Seretide Accuhaler 250mcg Total ADQ Usage Seretide Evohaler 50mcg Total ADQ Usage Seretide Evohaler 250mcg Total ADQ Usage
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Take for example the series in green, it looks like usage initially decreased a bit then increased a bit but it’s virtually impossible to infer some kind of trend. Bear in mind this has only 6 items on it, we have seen stacked bars with 10 or more items!! If you are trying to convey a message or assist your audience in drawing their conclusions this is exactly what you do not want. Instead you want to present the information in a manner that enables the end user to immediately see what is going on, not give them a headache and eyestrain!! In this case a more effective way of presenting the information would be perhaps to create a simple dashboard with 6 separate line charts for each item and the ability to select the practice of interest. A line chart is preferable in this case as we are dealing with a time series so it enables users to see more clearly where a trend may be developing (bar charts do make it harder for the eye to spot trends). 25000
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! Financial 2006/2007
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A stacked bar chart is appropriate when you have relatively few series to compare, perhaps 2 or 3, and for this dataset when you are comparing just a few practices along the X-axis (rather than a time series), no more than 5 or 6. If you want to know how to create your own simple dashboards in Excel we have provided a how-to in previous editions of Knowledge Matters or contact us via our email address quality.observatory@southeastcoast.nhs.uk If you come across a graph which you think could be presented more usefully please e-mail it to quality.observatory@southeastcoast.nhs.uk
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Calling Informatics Mentors and Mentees By Wendy Dearing, Director of Corporate Services and Service Development, Sussex HIS Following the launch of the British Computer Society ASSIST mentoring scheme at HC2011 in April, a number of mentoring relationships have started over the last few months and are starting to help health informatics professionals that have recognised the value of gaining input from someone outside their organisation with work based issues and their personal development. Mentoring schemes do exist in various parts of the country. This scheme is not intended to replace those but rather complement them and fill some of the gaps. The scheme is currently open to all BCS ASSIST members and we are now actively seeking both mentors and mentees to join the scheme. To be a mentor you simply need to be able to pass on your experience and advice to another individual on career development. Mentees should have identified a need for mentoring and have specific goals in mind that a mentor can help them with. The scheme is open to anyone with any level of experience and e-learning training and on-going support is provided to help people develop successful mentoring relationships. Mentoring is a long established and well regarded technique to support the personal and professional development of individuals’ careers. Mentoring involves a more experienced person (the mentor) who shares their knowledge and experience with someone who is less experienced (the mentee), in a relationship based on mutual trust. A mentor is an individual who passes on his or her experience and advice to another person on career progress. Mentoring provides help and advice to the individual but needs time and effort, needs commitment by both parties and is dependent on the personal chemistry between the two individuals.
Benefits to the mentor • • •
• • •
It gives experienced informatics staff the opportunity to “give back” to the NHS and help to develop the next generation of NHS informatics staff It allows mentors the opportunity to impart their experience and insights to others It give the opportunity to spend time (normally on the phone) on a regular basis with a mentee which will offer a different perspective to own reality and thus provide support and challenge It enables mentors to think more widely about their own work and performance It adds value to the process of management and to enhance managerial capability across organisations. It fosters mutually developmental partnerships.
Mentor Qualities The qualities of an effective Mentor are: • • • • • •
The right personal chemistry/ personality type Commands respect personally and professionally Good, active listener Interested Trustworthy Experienced
Benefits to the mentee • • • • • •
It provides individuals with the opportunity to spend time on a regular basis with a mentor who will provide support and challenge and a broader perspective on work issues. It focuses on enabling individuals to think more widely about their work and to take supported action to develop themselves. It acts as a safe and confidential arena to explore and build an understanding of the management of change. It adds value to the process of management and to enhance managerial capability across organisations. It fosters mutually developmental partnerships. It will create a greater self-awareness of the individual’s unique talents and identify gaps current skills sets.
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17 • • •
•
Eligibility of Mentees Use reflection to learn what works best on an individual level now and in the future. Mentoring is particularly supportive: during times of transition or change when new in role where the individual is uncertain of where to develop next or where their career development goals are
• • •
where the individual wants to be more effective or more motivated in their current role
Benefits of cross-organisational, crossprofessional and peer mentoring
•
Mentees should meet the following criteria: Have identified the need for mentoring, and have agreed specific goals for the mentoring process Be serious about managing their own development, having identified mentoring as appropriate through their organisational personal development planning process Be committed to the mentorship relationship, making time and space to attend sessions and ensuring all the follow up actions agreed are undertaken
Having a mentor from a different organisation and professional background facilitates new ways of working. It provides mentees with an opportunity to broaden their horizons and share experiences with someone from a similar organisational culture, but a different professional area and organisation. Consequently, both mentors and mentees are drawn from a wide range of roles and backgrounds. To find out more about how the scheme operates or to register an interest in taking part in the scheme, please see the ASSIST website or Wendy Dearing on 07770734725 at Sussex Health Informatics Service (HIS) who are administering the scheme on behalf of BCS ASSIST.
Stand at the safety conference On the 12th of October Adam and Kate were fortunate to attend the Safety Express Summit in London. The event set out not only to celebrate the success of the Safety Express programme in promoting patient safety and reducing harm, but also review the position the country is in with regards patient safety and look to the future and towards truly harm free care. The event was used to launch the first of a range of products in relation to harm free care; check out www.harmfreecare.org for more information. There were many inspirational speakers including Lloyd Provost from the Institute for Healthcare Improvement in the US, who treated us to a run through of the stages involved in accepting and acting on information (Stage 1: Denial!). Earlier in the day we all learned to ‘Tame Tigers’ with Jim Lawless, a truly motivational speaker who challenged the room to ’Act boldly today– time is limited’ and (Kate’s personal favourite) ‘Do something scary every day’. Combined with live action reviews of his time as a jockey, Jim’s session reminded us all of the importance of our own motivations and mindsets in improving the care for patients throughout the service. Adam and Kate (ably assisted by Kiran who drove all the kit through horrible London traffic!) manned a Quality Observatory stand, demonstrating the work the QO has undertaken on nursing measures and other quality metrics and tools. We had a great response from delegates across the country and were pleased to be exhibiting alongside fellow QOs from other regions. The QO is looking forward to the launch of future Safety Express products! www.QualityObservatory.nhs.uk
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Analysis Ancient and Modern : Farr-sighted By Adam Cook, Specialist Information Analyst
William Farr was a nineteenth century British epidemiologist regarded as one of the founders of medical statistics.. Mr Farr was one of the medical establishment that did not accept Jon Snow’s theory that the great Cholera outbreak was to do with water, but instead subscribed to the miasma theory. [See Knowledge Matters Vol 5. Issue 6, fact fans!] In fact in 1853 he collected mortality data to support his beliefs, it wasn’t until 1866, after Jon Snow’s death, that he came round believing it was contaminated water, and was one of the people who helped push through this belief into the establishment.
Creditable though this change of heart was, it was for something else that we need to recognise Farr’s real breakthrough. In 1837 William joined the newly formed General Register Office for England and Wales (GRO). GRO records births, marriages and deaths, and it was deaths that were the real focus Farr’s attention. Farr was appointed as a medical statistician, and as part of this work he began to collect information on deaths – not a new thing in itself , but Farr was more systematic and considered in his recording of deaths and brought about a more uniform collection of data. He strived to push forward a unified, and international standard classification or morbidity and mortality. A report early on his career at GRO said:
“The advantages of a uniform statistical nomenclature, however imperfect, are so obvious, that it is surprising no attention has been paid to its enforcement in Bills of Mortality. Each disease has, in many instances, been denoted by three or four terms, and each term has been applied to as many different diseases: vague, inconvenient names have been employed, or complications have been registered instead of primary diseases. The nomenclature is of as much importance in this department of inquiry as weights and measures in the physical sciences, and should be settled without delay.” In 1853 the first International Statistical Congress asked Farr, along with another statistician, Marc d'Espine, to come up with a classification system that was robust and could be used internationally. Farr and d’Espine came up with two different systems, but after some revisions it was in the 1880’s that Farr’s system was more widely accepted. Over the years there have been many revisions and adaptations of his system, but were Farr around today he could go into many a healthcare analysts office and pick up a certain hefty green volume and recognise it as the fruit of the seeds he sowed nearly a century and a half ago. If any can be called the father of ICD (now in it’s 10th revision) then it must be William Farr.
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NEWS Daily Sitreps It’s that time of year again! Daily Sitreps start on Tuesday 1st November with the first submission to Unify to be completed on the following day, Wednesday 2nd November by 11am at the latest. Lorraine Lowes at the SHA will be chasing non-completers!
Unify 2 accounts Individual organisations are now responsible for the creation and management of Unify 2 accounts, including resetting forgotten passwords. To find out who is responsible in your organisation contact Rebecca Matthews.
Level 2 Award and Certificate in Health Informatics A standalone Level 2 Award and Certificate in Health Informatics has been launched and is available through City & Guilds, who are the awarding body. These qualifications aim to give recognition to those working in areas such as records and data management and to provide a spring board into a wide range of roles in and for the NHS where information handling is a key responsibility. The qualifications, for example, may be of value to Human Resources staff with an interest in workforce planning and to staff working in a wide range of service support roles. The qualification covers the following areas: • Input and handling of data. • Validation and quality assurance. • Production of reports. • Storage, security, disclosure and dissemination of information. You can get more information and find out if this qualification is offered by a City & Guilds learning centre in your region by going to: http://www.cityandguilds.com/60145.html
QOF 2010/11 data released The results from the annual Quality and Outcomes Framework submissions are now available on the Information Centre website www.ic.nhs.uk. QO members will be updating all relevant products with this data as soon as possible. Exceptions data from QOF will follow shortly. KH03– now with ROCR approval The quarterly KH03 return on bed numbers and occupancy now has ROCR approval and will continue to be collected for the foreseeable future.
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QO awarded tender to support IQP for the South Central PCT Alliance The Improving Quality Programme for the South Central PCT Alliance invited tenders for the provision of analytical services to the programme. The Quality Observatory are pleased to announce that they were the successful bidders and look forward to starting work with the team in South Central as soon as possible!
Fundamental Review of Data Returns The review of central data returns is now into a consultation phase. The recommendations in the consultation represent the outcome of a process that looked at over 330 data returns, covering 12 distinct themes, and involving contributions from a large number of individuals from within the Department, its Arms Length Bodies, the NHS and other organisations who generate or use the data. Recommendations have been made and are now out to consultation which closes on the 22nd November. If adopted the recommendations will mean a significant number of current data returns will be discontinued. All the relevant documents can be viewed at http://www.dh.gov.uk/en/Consultations We strongly encourage readers to take a look and take part in the consultation to make sure the voice of the service is heard!
Goodbye to Matt With a heavy heart we bid a fond farewell to Matt Read who has done sterling work alongside Aleks and Kiran on workforce planning and analysis. He returns to East Sussex with our best wishes for the future!
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Ode to Candy…..
Fascinating Fact
We'd like to thank you, Candy, for all of your support Given in the past few years, you've never fallen short. Your enthusiasm to help us and guide us on our way, Has helped us build up the team to what we are today. You've championed the way we work and let us innovate, Let us know what's happening and kept us up to date. Now you're in your new role we hope you'll still be able To peruse Knowledge Matters when it lands upon your table. For a CEO we didn't have just any old Tom, or Dick or Doris, The Quality Observatory salutes you - three cheers for Candy Morris.
Clusterin’ SHA
This is Romanesco broccoli– it is a fractal with a fractal dimension of 2.8.
(To the tune of Surfin’ USA (and with apologies to Chuck Berry & Brian Wilson)
The department had a notion To change the S.H.A. They decided that clusterin' Would be the way You'll see us working in clusters Like commissioners do, An early autumn debut, Clusterin' SHA You'd catch 'em clusterin' at North West And North East combine With Yorkshire and Humber Then down to the midlands East and West are one With East of England too. Everybody's gone clusterin' Clusterin' SHA
We'll all be planning the future That's gonna happen real soon We're fixing into a structure To which we can attune, Then at the end of the the summer We'll be clustered to stay Tell the DH we're clusterin' Clusterin' SHA All the way down south West, Central & East Coast Will be as one from Land's End to Dover All that's left is London As it was before. Everybody's gone clusterin' Clusterin' SHA Everybody's gone clusterin' Clusterin' SHA Everybody's gone clusterin' Clusterin' SHA
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