Knowledge Matters Volume 4 Issue 6

Volume 4 Issue 6 February 2011 Welcome to Knowledge Matters Hello everyone and welcome to the final edition of volume 4—that means that we have published six issues of Knowledge Matters each year for 4 years!! You can do the math in terms of number of issues and pages….Luckily I am recently returned from holiday (see page 19) and am pretty relaxed so I’m not going to get stressed about getting old etc…..

It won’t come as a surprise to you that we have spent a considerable amount of time over recent months learning more about the needs of GP commissioners. A couple of years ago we developed a web-based QOF tool which enabled GP practices across England to benchmark their performance against practices within their PCT, region or nationally. We are currently finalising an enhanced tool (again web-based) which provides the ability to benchmark a wider range of practices and see progress over time (which of course is extremely important as benchmarking has its limitations). In addition, we have worked with a number of GP practices across Surrey to develop dashboards which are meaningful and useful to GPs to cover a range of topics relevant to quality, outcomes, long term conditions and activity. See pages 10-11 to learn more about the detailed work that has been undertaken for COPD. Over future months we are keen to engage with a wider GP audience regarding information needs—if you are interested please do get in touch!

Over previous years we have provided a range of benchmarking tools relevant to acute Trusts. We are currently enhancing and updating existing tools and developing a new suite of tools utilising acute Trust data. If you have ideas or requests regarding which tools would be most useful to you please do let us know. In the next issue you can read about the national benchmarking tools that we have developed in collaboration with the National Technology Adoption Centre. If you can’t wait until then you can visit our stand at the Innovation Expo next month (see page 19) or of course get in touch with me directly (samantha.riley@southeastcoast.nhs.uk) See you next time with a new outfit (hope you like the Quality Observatory branded kit this time—thanks as always to my creative and wardrobe team) !!

Inside This Issue : Making the case for self care education

2

Primary Care Commissioning Application

8

The National Hip Fracture Database

14

The outcomes framework

3

Analysis, Ancient & Modern

9

The Pareto Matrix

16

NHS Networks—FAQs

4

COPD—breathing life into the data

10

Christmas Quiz Answers

18

Skills Builder—Forecasting

6

Ask An Analyst

12

News

19

http://nww.sec.nhs.uk/QualityObservatory Quality.Observatory@southeastcoast.nhs.uk

Page 2

Making the case for self care education

By Roger Halliday, Policy Analyst, Department of Health When people take an active role in managing their health, this tends to lead to them having better health, better experience of care and using fewer healthcare services. This finding seems intuitive and indeed is backed up by a significant body of research. The challenge is how to make this happen. If you are struggling with this challenge, this product may be something to help.

This free to use product gives local commissioners the likely demand for, costs, cost savings and patient benefits of self care education, tailored for their area. It makes the business case for you and indicates the best value spend on this theme given local circumstances. It uses the latest national and international research combined with local data, though you can change the assumptions to explore options.

Background There are a number of evidence based interventions that are known to activate patients, one of which is self care training programmes. These are typically face to face courses with 6-8 sessions, but can be online. They can be targeted at generic self management skills like Expert Patient Programme or disease specific courses like DESMOND for diabetes.

Over the last few years I have tried to understand, given quite good evidence of their cost effectiveness, why more people aren't using them. I did a piece of work last year with a range of NHS stakeholders to identify barriers and potential solutions. This work concluded there were three main barriers 1.

The majority of patients didn't know about it and therefore weren't demanding it (see chart below)

2.

Some frontline clinicians were unconvinced about the clinical benefits and reluctant to put people on courses (see chart below) Engagement of people with LTCs in supported self care, England July 2009 50%

I am aware that this is something I can do to manage my condition

% of people with Long Term Conditions

45%

I have been encouraged to do this by a doctor or nurse

40%

I have done this

35%

Doing this was helpful in managing my condition

30% 25% 20% 15% 10% 5% 0% Read and use information about your condition

3.

Read and use information about the choices you have for care from doctors and nurses

Attend a training course on your condition

Attend a support Have equipment fitted network of people with into your home a long-term condition Source: Primary care tracker survey, July

Many commissioners were unaware of the value of the courses and were reluctant to commission these courses

Feedback from the NHS was that without addressing all three barriers, there wouldn't be a significant expansion of these courses and realisation of benefit. Work is in hand on the first two barriers. This work attempts to break down the third.

The product Alongside colleagues in Expert Patient Programme, commissioners and 3rd sector orgs, we developed and tested this model, which is now available for free via the link http://www.selfmanagement.co.uk/resource-library.

Page 3 You select your organisation (GP pathfinder, PCT or GP practice) and type of course you are considering. It gives you information about likely number of people interested. A report is then generated showing costs, likely cost savings and patient benefits with some basic return on investment figures.

Making the case for self care education in South East Coast SHA Type of course Number of people to commission training course for

Asthma Management Handbook 4,046

To run this self care training course for this number of people would cost (per year) This would result in the following financial savings and patient benefit:

GP visits Nurse visits All GP practice cost savings A and E visits Inpatient admissions Outpatient visits Medication costs All commissioner cost savings QALY gains Social Return on Investment Total Patient Benefits

Saving in activity 11,332 8,103

£

Unit cost £52 £11

174.8 32.6 33.1

£110 £1,427 £126

80.9

£30,000

404,613

Cost Saving £589,273 £89,128 £678,401 £19,223 £46,548 £4,165 £95,701 £165,636 £2,427,677 £5,073,845 £7,501,521

Total gross benefits

The net benefit of running this self care course is Which equates to £1963 per person with LTC This equates to a return on investment of

£8,345,558

£7,940,946 20.6 to 1

The assumption made is that the saving will happen in the year following training. Evidence is mixed about effects after one year. However, for illustration, if 50 % of the year 1 benefits were realised for a second year, there would be additional savings in year 2 of: Primary Care £ 339,201 Commisioner £ 82,818

You can tweak assumptions and enter local data. You can also enter in a total budget for self care education and the tool will suggest the most cost effective way of spending this money, given local population characteristics. All research and data references are included.

If you have any feedback or want further information, get in touch with Roger: roger.halliday@dh.gsi.gov.uk or 0113254-6160.

The Outcomes Framework The NHS Outcomes Framework was published on 20th December 2010. This important document builds on proposals and responses from the consultation Transparency in outcomes—a framework for the NHS. The framework is intended to provide national accountability for the outcomes that the NHS delivers and once the NHS Commissioning Board is formally in place subject to parliamentary approval) the framework will form part of the broader mandate set for the Board.

The framework covers 5 domains which each contain a range of indicators. Whilst some indicators are clearly defined with data sets already in place to support measurement, for others a significant amount of further work is required to develop robust indicators and data collection processes. The domains are: -

    

Preventing people from dying prematurely Enhancing quality of life for people with long-term conditions Helping people to recover from episodes of ill health or following injury Ensuring that people have a positive experience of care Treating and caring for people in a safe environment and protecting them from avoidable harm

The Quality Observatory intends to provide regular benchmarking on the indicators that are currently measureable (some are already reported on a regular basis). For further details see a future edition of Knowledge Matters.

If you are interested in learning more about the framework, use the following link. A really useful summary of indicators appears on page 33 http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/PublicationsPolicyAndGuidance/DH_122944

Page 4

NHS Networks: FAQs

By Julian Patterson, Development Director, NHS Networks Julian answers the frequently asked questions about NHS Networks.

What is it?

Since 2005 NHS Networks has been a rallying point for networks -- or communities of interest. Since February 2010 it has also been an online hub offering free web space, collaborative tools, and means for networks to enrol, manage and stay in touch with their members.

What’s it for?

At its simplest, Networks exists to enable people in the NHS to get on with their jobs more efficiently and effectively. Working virtually has obvious cost and time saving advantages over face-to-face meetings.

The greater significance of networks is in the spread of innovation. The NHS achieves fantastic things but is much less good at making them widespread and systematic. Part of the problem is cultural and behavioural, but part of it is about the lack of systems that make it easy to share intelligence.

Who uses it?

Managers, clinicians and other professionals, but there is no restriction on who you are or what you do. The site is intended for anyone in the NHS, but that will be a broader family in future so we expect to see social care and other networks join the growing NHS Networks community.

How many users are there?

Networks now has more than 22,500 members and new ones are joining at a rate of about 50 each week. You have to be registered to use the service, but registration only requires a user name and password – we don’t require inside leg measurement or any of the other profiling detail designers of forms are so fond of. We also publish a weekly newsletter which has nearly 15,000 subscribers. The newsletter plays a key role in driving traffic back to the site.

Why are networks so important now?

Networks are always important, but there are two reasons why they have special significance in 2011.

1. The QIPP agenda depends on cutting the cost of what we do and finding ways to improve patient care and use of public resources in a funding environment that is shrinking in real terms. Networks are key to making this happen. We often quote the following lines from a piece written in the HSJ last year by Jim Easton, the NHS director of improvement and efficiency: “We need to create and join networks that create innovation at scale, if we are to meet the quality and productivity challenge.” Jim develops this theme in a video interview which you can find on the NHS Networks channel on Youtube: http://www.youtube.com/user/NHSNetworks#p/u/31/AIeFRevRvnE 2. The NHS is undergoing enormous change which will profoundly affect the way we work – and in many cases whether we have jobs. Whenever institutional change occurs, people seek other ways of staying connected and regrouping. People will resort to formal and informal networks, but NHS aims to be a platform to support the transition to the “new” NHS. How will NHS Networks survive the changes to the NHS? NHS Networks is hosted by Primary Care Commissioning. PCC is an NHS organisation working in parallel with a social enterprise. PCC earns its income through subscription and contracts to support policy implementation and is well placed to survive the changes in the NHS. PCC is committed to keep supporting NHS Networks.

Page 5

How do networks change the way we work?

There are many different kinds of networks, but the reason so many exist in the NHS is because it is an inherently hierarchical environment. There is nothing wrong with hierarchy since any system as large as the NHS with a mission to provide critical and long-term care has to be organised. But hierarchy also gets in the way. Networks allow people with shared interests in particular conditions or topics to work together and share ideas across organisational boundaries. They overcome the problem of silo working.

How do you stop networks becoming the new silos?

Not all networks are good or necessary. People like to form clubs and sometimes these are needlessly exclusive.

There are currently more than 500 networks registered on NHS Networks but not all of them are active and not all of them will end up doing something useful. NHS Networks won’t be twice as successful when there are a thousand networks. Less is more.

To assist this process, we try to encourage people to join existing networks rather than start new ones. This is simply to avoid duplication of effort. Ultimately, though, it’s none of our business. We provide the platform. It’s up to users what they do with it.

How do you measure the success of networks?

Networks need to justify their existence like everything else in the NHS. Everyone talks about collaboration and sharing but what can they actually show for it?

We are starting to develop evaluation tools for networks to help them provide evidence of success. What has the network done to improve processes, reduce costs, increase productivity, enrich our collective knowledge and ultimately benefit patients? If we can’t answer the last question, we shouldn’t be doing it.

What’s the toughest challenge for NHS Networks?

Getting people to take part. Collaboration is work.

Sharing documents, answering questions from colleagues, writing blogs – all these take effort. Our job is to reduce the effort as much as possible, but we can’t eliminate it altogether.

Engaging people in discussion forums is a real challenge. We haven’t cracked this yet. It’s partly a marketing problem. Forums will take off when we achieve a critical mass of traffic.

What’s next for NHS Networks?

We have an ambitious development plan to improve the user interface and the user experience. A lot of these are small changes, but a big one is the introduction of personal profiles. These will enable us to start making richer connections between people – by understanding who they are, what they do and what their professional interests and passions are, we can form much richer, more dynamic networks.

Check out NHS Networks for yourself: www.networks.nhs.uk

Page 6

Skills builder—forecasting

By Katherine Cheema, Specialist Information Analyst Welcome to this final part of the forecasting skills builder. Last time we looked at the concept of error and how it can help us decide the best forecasting method and discussed some simple forecasting methods based on stationary data with no seasonal variation. This time, we’ll have a peek at the application of exponential smoothing (remember that from last time?) to data with seasonality and describe the methods known as decomposition, which can be applied to seasonal data that shows an upward or downward trend (emergency admissions anyone?). Once again, we’ll use error calculations throughout to see just how accurate our forecasting methods are.

First of all then, lets look at exponential smoothing with seasonal data. Seasonality is where your data has a regular pattern; every day (e.g. peak queues in the post office at midday), every week (e.g. peak appointments with a GP on a Monday), every year (e.g peak sales of pumpkins in October). We can use variants of the naïve forecast and moving average if we like, applying the methodology to each time period. For example, to forecast the number of patients coming through a GP door on a Monday we use the moving average of the previous 3 Mondays; do the same for Tuesdays and the rest of the week and you have accounted for the seasonality in the data. The concept is similar when using the exponential smoothing method; essentially you create a smoother series for each day/month/quarter. For space reasons, let’s use quarterly data as an example: You can see here that we actually need Table 1: Seasonal exponential smoothing with alpha at 0.7 three years worth of data to get a reasonA B C D E F G Forecast Absolute Error able forecast. α is set at 0.7 which is quite Actual attendances error Percentage squared high and indicates that in order to get a Week attendances (ES) Error (B-C) (abs(D)) error (E/B) (E x E) good fit the forecast has to be quite 2008/09_Q1 30 31 -1.0 1.0 2008/09_Q2 31 31 0.0 0.0 reactive in order to reflect the substantial 2008/09_Q3 45 31 14.0 14.0 peaks in each Q3. One way to get around 2008/09_Q4 33 31 2.0 2.0 0.1 4.0 this might be to set α differently for each 2009/10_Q1 32 30.3 1.7 1.7 0.1 2.9 quarter (so Q1 series set at 0.1, Q3 series 2009/10_Q2 29 31 -2.0 2.0 0.1 4.0 set at 0.7 for example). With more data 2009/10_Q3 46 40.8 5.2 5.2 0.1 27.0 2009/10_Q4 31 32.4 -1.4 1.4 0.0 2.0 this will probably smooth out a bit more, 2010/11_Q1 30 31.49 -1.5 1.5 0.0 2.2 but a forecast isn’t very useful if it requires 2010/11_Q2 33 29.6 3.4 3.4 0.1 11.6 lots and lots of data to become 2010/11_Q3 44 44.44 -0.4 0.4 0.0 0.2 reasonable; ideallly we want to start using 2010/11_Q4 34 31.42 2.6 2.6 0.1 6.7 2011/12_Q1 32 30.447 1.6 1.6 0.0 2.4 the data as soon as possible, not wait for it 2011/12_Q2 31 31.98 -1.0 1.0 0.0 1.0 to build up!

2011/12_Q3 ?

31

Totals MAD = Σ I et l / n = MSE = Σ et2 / n = MAPE = Σ(l et/yt l) / n =

22.7

0.7

63.9

1.62 4.56 4.71%

This method assumes that there is no trend up or down; so we have seasonality in our data but no increases in overall demand

One method we can use where there is seasonality and trend is called decomposition. There are two types of decomposition, additive and multiplicative. Which one you use depends on the variability of the seasonality; for example there is a peak in quarter three in emergency admissions (which also show an overall upward trend) each year. If this peak is of about the same amplitude each year then you would use the additive technique; if it increases each year then you would use the multiplicative version. Have a look at chart below, which should illustrate the point.

The process is the same for both methods and goes like this:

70 60

1.

Estimate the trend

2.

Remove the trend to make seasonality stand out

40

3.

Find the seasonal factors

30

50

So the model for our admissions example would be:

20 10

Forecast admissions = Trend + Seasonal variation See, easy.

0

Additive

Multiplicative

Page 7 Lets go through this in more detail with an example; we’ll stick with our fictional emergency admissions and we want to forecast quarterly numbers for the next financial year. First of all, plot your data to see what patterns emerge. Let’s assume for now that we’re looking at seasonal data with trend but no significant change in amplitude. First step then is to estimate the trend. We do this by using centred moving averages and then forecasting this through the time periods we want to forecast for. In the table 2 below, we’re doing this in columns D-F. Calculate the moving average for the first 4 quarters (period 1-4 in columns B&C) and put this against period 2 (column D). Do the same again and put it against period 3 (column E); in both cases copy the formula down until you run out of four period groups. Then average the contents of columns D&E (column F); this gives you your centred moving average. If for some inexplicable reason you have five periods in a year, you won’t need to do the averaging bit as you have a centre point (period 3) but as most seasonal data will run over four quarters or twelve months this process will be more usual.

In column G the trend is shown; where there is a centred moving average calculated this is used as the trend. This needs to be forecasted through using Excel’s =TREND() worksheet function. This uses ’known y’s’, which the trend you have already calculated (column F), ’known x’s’, which is the period numbers you have actual trend figures for (column B), and your new x which is the time period number you are forecasting. This is where it is important that you have numbered your time periods! Excel has good on-screen help for this Table 2: Additive decomposition A B C D E F G H I J K function so we won’t do a Quarter Period Admissions 4 Q moving 4 Q moving 4Q centred Trend Seasonal = Average Forecast = Error tutorial on it here, but it effecaverage average moving projected Admissions - Seasonal Seasonal + tively forecasts trend using centred at centred at average using Trend Term Trend period 2 period 3 =TREND() linear assumptions. Linear regression, that’s what it is!

12 2008/09 Q1 1 2008/09 Q2

2

15

15.75

2008/09 Q3

3

16

16.25

So that’s step 1 dealt with, we have an estimated trend.

20 17 2008/09 Q4 4 16.25 16.625 3.38 -1.04 14 18 2009/10 Q1 5 17 17.5 17.5 -3.50 -3.81 13.69 0.31 Next up we remove the 18 19 2009/10 Q2 6 18 18.5 18.5 -0.50 -0.38 18.13 -0.13 trend. In an additive model 20 19.75 2009/10 Q3 7 19 19.375 19.375 0.63 0.21 19.59 0.41 we simply take the trend 24 20.75 2009/10 Q4 8 19.75 20.25 20.25 3.75 4.41 24.66 -0.66 17 21.5 2010/11 Q1 9 20.75 21.125 21.125 -4.13 -3.81 17.31 -0.31 away from the actual admis22 23 2010/11 Q2 10 21.5 22.25 22.25 -0.25 -0.38 21.88 0.13 sions (column C– column G).

23 2010/11 Q3 11 23 22.99 0.01 0.21 23.20 -0.20 In a multiplicative model we 30 2010/11 Q4 12 23.89 6.11 4.41 28.30 1.70 would DIVIDE these instead.

2011/12 Q1 13 ?

24.79 -3.81 20.97 What we are left with then is 2011/12 Q2 14 ?

25.68 -0.38 25.31 2011/12 Q3 15 ?

26.58 0.21 26.79 just the seasonality.

We 2011/12 Q4 16 ?

27.48 4.41 31.89 then calculate the average MSE 0.49 seasonal term (column I). To do this, simply take the average of the value in column H for each quarter (e.g. the three values for Q3 in column H. In this example, that would be the average of 0.00, 0.63 and 0.01, which equals 0.21). Because you are using the same data effectively for each year, the average seasonal term will be the same for each Q1, each Q2 etc.

15.75

16

16 16.625

0.00

0.21 4.41

16.21 21.04

-0.21

Right, home stretch. We’ve just done steps 2 and 3 in one go. Last step then is to create the final model which is just adding the seasonal factor we just calculated to the trend we identified earlier (column G + column I = column J). If we were using the multiplicative method we would at this point MULTIPLY the seasonal factor with the trend value. We now have a completed forecast through each quarter of the next financial year, accounting for seasonality and trend. Good eh?

Finish it off by calculating error so you can assess the accuracy of the model. Here the MSE is only 0.49. However, as this author wrote these examples, she became uncertain as to whether the additive model was really the best one to use; so she ran the multiplicative one as well and ended up with an MSE of only 0.17, so it was a better fit. That will teach me not to plot the dots first!

This series of skills builders has looked primarily at time series data where we haven’t accounted for underlying causes or drivers; for example we have forecast emergency admissions based on previous data but haven’t accounted for, say, increasing numbers of COPD patients or reductions in staffing levels, as a variable that might influence the final forecast.

This is causal forecasting and if you want to know more we can arrange a training session. In the meantime, if you want to see the spreadsheets behind the examples here, just drop us a line at the usual address.

Page 8

The Primary Care Commissioning Application (PCCA): Supporting the commissioning of primary medical care and consortia development.

By Tanya Powell, Primary Care Improvement Analyst, Department of Health The commissioning of Primary Medical Care is challenging and collating all of the information needed to inform decisions from the wide range of data sources can be demanding. Tools like the Programme Budgeting suite, Spend and Outcome Tool (SPOT) and the Quality and Productivity Calculator (QPC) can highlight areas for investigation.

The Primary Care Commissioning Application (PCCA) provides a unique functionality that allows primary care commissioners to drill down and compare key performance indicators. The application collates, benchmarks and analyses a wide range of primary medical care data at PCT and practice level, including QOF, GP Patient Survey, Workforce, financial and public health data (Figure 1).

Figure 1: The PCT profile shows the PCT benchmarked against all PCTs for the full indicator list

Simple analysis can be undertaken to assess relationships between indicators, e.g. the relationship between access (GP patient survey) and A&E attendances, and changes in the indicators over time such as improvement in QOF achievement or falls in the ACS admission rate (Figure 2).

A new version of the PCCA (v82) will be released in early March with increased flexibility and capacity. The number of locally defined indicators that can be added has been increased from 10 to 20, and it now allows up to 20 ‘practice baskets’ or groups of practices. Reflecting the ongoing development of emerging GP consortia, you will now be able to include practices from outside a PCT area.

The current version of the PCCA (v81.1) can be downloaded from the PCC website (www.pcc.nhs.uk/pccs-application), and is currently being used by PCTs to:



benchmark themselves nationally and against ONS groupings



benchmark their practices on key indicators against their PCT peers and those with a similar deprivation level



Identifying good practice and potential clinical leaders to support clinical improvements



act as a basis for their performance management structure



target areas for intervention, e.g. diabetes care



highlight practices for support and development



engage with their practices and PBC groups for peer review

Figure 2: PCT dynamics chart showing the change in the ACS admission rate from the previous year. Those at the top right are above average and increasing (worse for this indicator), whilst those at the bottom left are below average and decreasing (better for this indicator).

The PCCA is continually updated and developed by a small team at the Department of Health, who work with NHS stakeholders. The primary medical care analytical team will continue to support PCTs, both as commissioners and as facilitators of emerging GP consortia. They will ensure that the PCCA supports these groups by adding new, relevant indicators and by further developing the consortia functionality during 2011.

The DH team is available for demonstrations of the tool and training sessions with PCT teams and local GP groups. To arrange a visit or to contribute to the further development of the PCCA, please contact us at PCIteam@dh.gsi.gov.uk

Page 9

Analysis, Ancient and Modern—thank you for not smoking

By Katherine Cheema, Specialist Information Analyst

We’re getting a bit more up to date this edition with a review of one of the most important pieces of analysis undertaken in the 20th century, from the perspective of public health. Between 1922 and 1947, the annual numbers of deaths due to carcinoma of the lung increased from 612 to 9,287 (about 15 times). Not just in England and Wales but across Northern America and Europe as well.

Despite furious discussion around the role of atmospheric pollution from cars, industrial plants, coal fires and even road laying, the smoking of tobacco couldn’t be ignored as a possible contributory factor. The first paper, published in 1950, that really laid out the impact of tobacco on lung cancer incidence was co-authored by a statistician called Austin Bradford Hill (later ‘Sir’ A.B.Hill). After an initial bid to become a doctor, put paid to by a bout of TB contracted during WWI, Hill trained as an epidemiologist and statistician and took up a Professorship at the London School of Hygiene and Tropical Medicine in 1947; so far, so academic.

What made the study on the relationship between tobacco use and lung cancer so compelling as a piece of analysis as far as this author is concerned is two-fold; firstly, it was displayed simply and efficiently, using the data to support the argument throughout the paper without statistical jargon. The fact that this analysis was carried out using a calculating machine (see picture) in the days before computers makes it all the more impressive. Secondly, the analysis is between two groups; an experimental group and a control group; this was among one of the first control trials, something we can’t conceive of not using today (RCTs are considered high quality evidence).

So whilst this piece of analysis may not be the most flashy, the most romantic or even the most pretty, it is one that absolutely underlines the importance of the analysis becoming a compelling tool in telling the story.

Sources: The Science Museum, London Doll, R and Hill, A.B. (1950), Smoking and Carcinoma of the Lung, British Medical Journal, 2, 739-748.

Page 10

The COPD Dashboard: breathing life into the data

By Nikki Tizzard, Quality Innovation & Productivity Analyst What exactly is COPD? Chronic Obstructive Pulmonary Disease is a term used for a number of respiratory conditions including chronic bronchitis and emphysema. It cannot be cured once you have it but it is preventable and treatable.

About 861,000 people in England have been diagnosed with COPD1 and it is estimated that another 700,000 people have the condition but have not been diagnosed2. 1 in every 8 emergency hospital admissions is due to COPD3 and in 2009/10 this cost the NHS in England an estimated ÂŁ230 million4. At least 23,000 people die each year as a result of COPD in England5 and it is the only major cause of death which is on the increase6.

The South East Coast Respiratory Programme In March 2010 the Respiratory Programme was launched in our region with the aim of working collaboratively across the spectrum of care providers to prioritise COPD and general lung health. The Quality Observatory were approached for help in providing metrics and evidencing best practice so that learning could be shared across the region.

Working in close partnership with Rachel Collins, the Programme Manager and Dr Jo Congleton, Consultant Respiratory Physician, we came up with a list of measures which demonstrate where key improvements can be made in this area.

The aim was to develop a single tool to explore COPD in both the acute and primary care trusts and engage clinicians, community teams and commissioners. The result was‌

The COPD Dashboard First up is the acute sector. The opening page is a snapshot view of the last 12 months and focuses on three key measures; length of stay, 30 day readmissions and patients receiving non-invasive ventilation.

These measures, viewed simultaneously, can show an interesting picture.

For example, a low average length of stay may look good but obviously we would hope this is not resulting in higher readmission rates. Likewise, if a significant number of COPD patients are given ventilation treatment during their hospital spell, this would hopefully be reflected in a lower rate of readmissions.

We then go on to examine these and a few other measures to see the overall trends over time for each trust. The data is presented in two ways; one performance measure compared across all acute trusts in the region, and then all measures displayed together for one trust, allowing us to see a detailed picture for each.

We have also removed short-stay admissions from each measure and plotted it together with the total to see what impact this has. For COPD it can make quite a difference so this is clearly an area we should be looking at.

We also explore the issue of COPD patients who have been admitted and discharged on the same day, which might suggest levels of costly avoidable admissions. We are helping to evidence that an increased focus on selfmanagement of the disease, combined with community care and pre-hospital treatment by the ambulance service can all help to

Page 11

reduce these numbers in the acute sector.

We also analyse admissions, bed days, in-hospital mortality rates and patients who have been seen by a respiratory consultant during their hospital spell. We look at the latter as it is widely considered among consultant physicians that these patients are likely to receive better care and have a shorter length of stay.

Now onto primary care.

We use the same format here of analysing a 12 month snapshot of each PCT using three key measures, backed up by viewing a trend over time for several indicators.

We felt one of the most important things to focus on with the PCTs was reported vs expected prevalence of COPD. This compares the numbers of diagnosed patients reported by GP practices in the Quality & Outcomes Framework (QOF) with projected figures for our region that are more likely to reflect those undiagnosed patients mentioned above.

These projections are based on modelling work carried out by the Eastern Region Public Health Observatory7 and factor in things such as smoking status, rurality and deprivation.

We also include in our snapshot acute admissions per 1000 COPD population alongside QOF exception rates, as this could also be an indicator of COPD sufferers who may not be receiving vital primary care which, in turn, could have an impact on non-elective admissions to the acute sector.

Our trend charts deal with admissions, bed days and frequent flyers, where patients have been admitted as an emergency more than once in a year with a primary diagnosis of COPD. We also address end of life care in terms of deaths in hospital where the length of stay was less than 2 days, a situation ideally avoided, given the preference generally expressed by patients to die at home.

The 90 day readmission rates can be a gauge of whether patients have been able to self-manage their illness or perhaps whether they need further help from community teams following discharge from hospital. In general we noticed that these readmission rates are fairly high across our region so there is an opportunity for teams to work together to try and improve these.

Moving forward with the COPD dashboard We have now extended our analysis and the dashboard has spawned offspring at consortia and practice level, and also site level for the acute trusts. We have looked at areas like medicines management and we also provide support to various projects on our patch which are part of the National Lung Improvement Programme.

The SEC Respiratory Programme team have used the dashboard to highlight areas for investigation, generate actions for improvement and have helped to move COPD up the agenda in the South East Coast region.

If you would like more information on the SEC Respiratory Programme or the COPD Dashboard, please contact: Rachel Collins, Programme Manager : rachel.collins@southeastcoast.nhs.uk Nikki Tizzard, Quality Innovation & Productivity Analyst : nikki.tizzard@southeastcoast.nhs.uk 1

The Quality & Outcomes Framework 2009/10, 2,7www.erpho.org.uk, 3www.patient.co.uk, 4NHS Comparators https://nww.nhscomparators.nhs.uk, NCHOD Mortality from bronchitis, emphysema and other COPD 2008, 6www.lunguk.org (all accessed February 2011)

5

Page 12

Conditional Scatter Graph Application: Microsoft Excel 2003 Dear Quality Observatory 1

Just wondered whether you have a macro for changing the colours on a scatter plot according to its category? I want to create a series of charts where each point represents a practice, and to show the practices colour coded according to their localities. There is a way round it, creating separate series, but then you need to have three trend lines, which I’m not happy with.

Nina Churchill

0.9 0.8 0.7 0.6 0.5 0.4 0.3

Lead for Service Redesign

0.2

Knowledge Management

0.1

Surrey PCT

0 0

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Solution: Complexity 4/5 — Uses Macros HI Nina We can Definitely help you with this one!

Step 1:- organise your data, in this Example: Column A contains the X values Column B contains the Y values Column C contains the value that we want to differentiate by colour 1.2

Step 2:- Draw a graph create a scatter graph from the data in columns A & B. This should give you a standard Mono Colour series.

1 0.8 0.6 0.4 0.2 0 0

Step 3 :- Choose your colours To change the Colors of the Points on the scatter graph we will need to use an xlColorIndex constant the image on the right shows the default colour palette

0.5

1

1.5

Page 13

Step 5 :- Write the Macro open up Visual Basic Editor and create a new subroutine Sub recolor()

Note: To make this Macro available in Multiple workbooks save it to your “Personal.xls” workbook in the VB editor

ActiveSheet.ChartObjects("Chart 1").Activate ‘use this to reference the chart you want to manipulate if there is no active chart object the macro will fail alternatively you can leave this out and click on the chart you want to change before running this macro Set conditionRange = Application.InputBox(prompt:="select start of conditional range", Type:=8) ‘this sets the start of the conditional range, in this example C1 For i = 1 To (ActiveChart.SeriesCollection(1).Points.Count) ‘count the number of points in the data series logic = conditionRange.Offset(i - 1, 0).Value ‘reference the start of the range, i.e. Point 1 look at cell C1 for condition With ActiveChart.SeriesCollection(1).Points(i) ‘reference the first data point in series 1 of the Active chart object (this chart only has 1series) Select Case logic Case 1 .MarkerBackgroundColorIndex = 1 .MarkerForegroundColorIndex = 1 Case 2 .MarkerBackgroundColorIndex = 3 .MarkerForegroundColorIndex = 3 Case 3

Here we use the Select Case Statement to evaluate the contents of column C and change the data points based on it.

We need to use xlColorIndex constants to change the color of each point in the series

.MarkerBackgroundColorIndex = 4 .MarkerForegroundColorIndex = 4 End Select End With Next i ‘ loop to the next row in the series and continue the evaluation until we run out of data points End Sub

1.2

1

This should now allow you to create a scatter graph with different coloured points in a single series.

You could extend this to include a colour picker userform to dynamically assign colours … but that is for another day!

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Page 14

The National Hip Fracture Database

By Maggie Partridge, Project Manager, National Hip Fracture Database The National Hip Fracture Database (NHFD) is a web-based, clinically-led continuous audit that seeks to improve the clinical care and rehabilitation of patients with hip fracture; and to improve secondary prevention in order to reduce the risk of future fracture.

The NHFD has expanded rapidly since its launch in 2007 to achieve national coverage. It is jointly sponsored by the British Geriatrics Society and the British Orthopaedic Association, the professional associations of the main clinical specialties involved in hip fracture care; and is complemented by the jointly sponsored Blue Book on the Care of Patients with Fragility Fracture1.

The NHFD documents case-mix, care and outcomes of hip fracture, and also measures compliance with the six clinical standards set out in the Blue Book. These are: prompt admission to orthopaedic care; surgery within 48 hours; the prevention of pressure ulcers; access to ortho-geriatric medical care; assessment for bone protection therapy; and falls risk assessment.

As a web-based, clinically-led audit, the NHFD provides continuous clinician-friendly feedback through monthly online reports to participating hospitals. This enables clinicians and managers to monitor their caseload and care processes, allowing them to compare their performance against regional and national benchmarks, and to monitor and evaluate the impact of clinical or service management initiatives aimed at improving patient care.

The NHFD has achieved a 100% hospital registration rate in England, Wales and Northern Ireland with 91% regularly submitting data. We currently hold >117,000 case records submitted at the rate of c. 4,300 per month (74% of all hip fractures – based on an estimated 70,000 hip fracture cases per year).

The existence of the NHFD, and its use by all eligible hospitals in England, has greatly facilitated an important Department of Health initiative, the innovative Best Practice Tariff (BPT) for hip fracture care.

Best Practice Tariff for hip fracture The 2008 the ‘High Quality Care for All’2 report first set out the vision to make quality the organising principle of the NHS and introduced the development of the Best Practice Tariff (BPT) to be focused on clinical areas in need of improvement; where there was high volume and unexplained variation in practice; and where there was already an excellent source of clinical data: in this instance, respectively, hip fracture and the NHFD. The key quality standards for hip fracture care defined by leaders in the field and measured by the NHFD for the purposes of the BPT, are:

 

Surgery within 36hrs Orthogeriatrician involvement  Admitted under the joint care of a Consultant Geriatrician & a Consultant Orthopaedic Surgeon  Admitted using an assessment tool agreed by geriatric medicine, orthopaedic surgery and anaesthesia  Assessed by geriatrician in perioperative period (defined as 72hrs of admission) (Geriatrician defined as Consultant; NCCG or ST3+) Postoperative Geriatrician-directed:  Multi-professional rehabilitation team  Fracture prevention assessments (falls and bone health)

Only cases in which all the above standards are met are eligible to receive the enhanced Best Practice Tariff. The standards are monitored by the NHFD on a case-by-case basis, with a 5% additional case tariff – currently £445 which is paid when all standards are met.

The tariff is structured and priced in order both to incentivise and adequately reimburse the costs of high quality care.

However, when standards are met care is also likely to be more cost-effective, with prompt care and rehabilitation reducing length of stay – the major component of the overall cost of care.

Page 15

At a national level, improvements in care have been demonstrated by a comparison of compliance with Blue Book standards across the 2009 and 20103 NHFD reports. There was a 5% increase in the proportion of patients undergoing surgery within 48 hours; a 21% increase in preoperative assessment; and bone health assessment and treatment and falls assessment rose by 15% and 19% respectively.

The 2010 report also documents how individual hospitals have used the NHFD to achieve substantial improvements in care, for example:



In Mayday University Hospital, Croydon, a trauma group was set up to improve the hip fracture care pathway; average pre-operative time fell from 59 to 29 hours, and acute stay from 32.6 to 22 days



The Royal Surrey Hospital brought in joint orthogeriatrician /surgical care, additional trauma lists, and daily orthogeriatrician ward rounds. Acute stay fell by 6 days, mortality by 3%. While implementation costs were £220,000, savings in costed bed days amounted to £450,000.

Participation in BPT since its launch in April 2010 has been enthusiastic, with 55% of hospitals achieving the standards for varying proportions of their patients, and 25% (2,187/8,885) of all cases submitted meeting all the BPT criteria.

South East Coast SHA – Best Practice Tariff attainment This chart shows that 60% of SE Coast hospitals achieved the enhanced tariff for between 22% and 73% of their patients in Qtr 2 – an encouraging improvement on Qtr 1. However the wide variation of care nationally, also illustrated in the 2010 National Report, is reflected here and across all SHA areas, with 40% of hospitals yet to achieve BPT for any of their patients. There remains work to be done!

What we can do to help: The NHFD website www.nhfd.co.uk is full of useful information for both professionals and the public. A rolling news section is regularly updated and holds such information as up and coming meetings of interest and new issues concerning the care of hip fracture patients.

The resource search within the website aims to support effective participation in the NHFD, and thus enable Trusts to improve care and meet the criteria of the Best Practice Tariff initiative. The documents are arranged to reflect the hip fracture patient’s journey of care. They provide practical advice on improving clinical care and secondary prevention, on service organisation; and on how to make a case for the posts and resources necessary for the delivery of high-quality, cost-effective care.

A literature registry holds hundreds of articles spanning a decade of hip fracture care. The registry is divided into 3 chapters: Improving Hip Fracture Care; Secondary Prevention and High Quality Information.

Our E-Learning programme aims to assist users in identifying ASA Grade; bone protection medication; fracture types and operation performed using a step by step algorithm, thus helping with greater data accuracy.

The above resources are available at www.nhfd.co.uk and are not password controlled so do go in and take a look at what it has to offer.

NHFD contacts: Maggie Partridge, NHFD Project Manager: Maggie.fractures@ucl.ac.uk Andy Williams, NHFD Coordinator (South): Andy@nhfd.co.uk Fay Plant, NHFD Coordinator (North): fay@nhfd.co.uk References 1.

2.

3.

British Orthopaedic Association. The care of patients with fragility fracture. Br Orthop Ass 2007 available from http://www.boa.ac,uk High Quality Care for All: NHS Next/stage Review final report 2008 available from: http://cabinetoffice.gov.uk/media/cabinetoffice/ strategy/assets/publication/nhs_next_stage_review.pdf National Hip Fracture Database National Report 2010 available from http://www.nhfd.co.uk

Page 16

The Pareto Matrix

By Samantha Riley, Head of the Quality Observatory In the last edition of Knowledge Matters I reflected on some of the really useful approaches I had been reminded of whilst attending the Institute of Healthcare Improvement National Forum in Orlando in December. One of the best sessions that I attended was presented by Davis Balestracci—an American statistical guru. In this particular session, I was reminded of a very simple but effective approach to improvement by using a pareto matrix.

I had the pleasure of working with Davis some years ago when I headed up a whole system improvement programme in West London. The Trust had an extremely busy A&E department and for some time had experienced significant difficulty in achieving and sustaining the 4 hour target.

We had already started to use Statistical Control Charts (similar to the AESOP suite of tools developed by the Quality Observatory some years ago) to understand the variation in waiting times for individual patients and the ‘capability’ of the system to guarantee a 4 hour wait. Each day, there were a considerable number of patients breaching the four hour standard. Pre Davis, the approach adopted to improve the system and reduce waiting times was to undertake a detailed investigation of every patient breaching 4 hours. As you can see from the graph below—this approach could require a significant number of patient journeys to be reviewed. The graph shows the total time in department for every patient attending the A&E department on 23rd February 2004—those circled in red breached the 4 hour standard therefore required a thorough (and time consuming) investigation.

A&E All valid Attenders by Time in Department Mon 23/02/2004

Time in Department

20.00

Arrival Time 00:00 - 03:00 03:00 - 06:00 06:00 - 09:00 09:00 - 12:00 12:00 - 15:00 15:00 - 18:00 18:00 - 21:00 21:00 - 24:00

26.82 Mean 2.21

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Patient

The findings from these investigations were reported on a daily basis and actions agreed as a result. Everyone was therefore really disappointed when after some months, and after so much hard work, A&E waiting times and associated performance had not improved. That’s when we were lucky enough to work with Davis for a few days— he brought a fresh pair of eyes and a very different approach…..

Davis suggested that the approach that we were taking to improve waiting times in A&E was fundamentally flawed.

We were making the assumption that the patients breaching 4 hours were experiencing a different set of circumstances to everyone else (for those of you familiar with SPC charts—special causes). Davis suggested that if we were to improve the capability of the system to deliver a sustained and guaranteed maximum 4 hour wait for patients attending A&E, we needed to understand in more detail the process applied to all patients—he suggested that those breaching 4 hours were not different—they were simply experiencing a combination of processes which all patients were experiencing. It was pure chance therefore that some patients experienced a combination of ‘normal’ experiences that resulted in them breaching—we therefore needed to improve the key processes experienced by all patients—then all patients would benefit and improved performance could be sustained.

Page 17 We were advised to undertake a detailed retrospective audit of patients attending A&E for the period of a week. This was no small undertaking as well over 200 patients attended on a daily basis—it was however the most valuable exercise which resulted in us understanding the real issues which needed to be addressed to improve A&E waiting times.

Davis advised us to map out the different processes which a patient may experience through their A&E journey e.g. assessment by a Doctor, referral to a specialist, x-ray, pathology tests, admitted to a bed etc. When auditing our weeks worth of patients, we recorded on a database the different processes that each patient had experienced, which stream of patient they were (e.g.major or minor), which specialty they had been referred to, whether they went on to be admitted and how long they were in the department…..we recorded lots more information—but hopefully this gives you a flavour.

With this wealth of data now collected we constructed a pareto matrix (below) which enabled us to clearly see which processes were commonly experienced by patients waiting in A&E by time band.

Bloods?

< 12345-

X-ray?

Spec review?

Bed?

Ref to pysc team?

II

IIII

I

I

I

IIII

II

III

II

IIIII

II

IIII

II

IIIIIII

We learnt a huge amount from this exercise—we now understood which processes we needed to learn more about. The processes and timings associated with specialty review and admission were prime candidates. Interestingly our previous approach of investigating individual breaches had never identified these areas as requiring further investigation or improvement. Previously the fact that a patient maybe waited 2 hours for an x-ray or blood test results had resulted in these departments being focussed on (and often blamed). All this time we had been ignoring the key processes which were problematic and required improvement.

Ref to int care?

III I

IIII

IIIIIII

IIII

IIIIIII

I IIIIII

The matrix provided us with the evidence to investigate the areas which really mattered. Some areas proved to be unpopular with some groups of staff—having the evidence made the key difference to agreeing and implementing the plans that would make a difference to the flow through A&E. Regular measurement and feedback ensured that agreed actions had resulted in the expected improvement. The best example of a key issue previously unidentified relates to patients requiring admission to a bed……

TimeInDept

The porters had always been blamed for delays in patients being admitted. This analysis exposed the fact that very often the decision to admit was made very close to (or often after) 4 hours.

So whilst the portering processes may have required improvement, the key process requiring improvement related to the decision to admit.

TimeToRequestBed

TimeToAllocateBed

TimeToTransportPatient

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14.00

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10.00

8.00

6.00

4.00

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115

112

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106

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97

100

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55

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49

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31

28

25

22

19

16

13

7

10

4

1

Davis taught us a really simple approach which I am sure lots of you are already fa- 0.00 miliar with—we need to focus on the areas that are going to result in real and sustained improvements. It’s the 80/20 rule that we know and love. How many times though do we take this approach?? It’s too easy to rely on hearsay and spend huge amounts of energy, effort, time and money on trying to solve the wrong problems. In the current climate we need to ensure that our efforts are focussed on the right areas—if we don’t get this right QIPP won’t deliver.

If you would like to learn more about this approach, or would like a fresh pair of eyes to check out your QIPP/ improvement plans please do get in touch!! samantha.riley@southeastcoast.nhs.uk

Page 18

Just for fun: Christmas Quiz Answers.

Christmas Questions

Sci-Fi Questions

1.

6.What is the name of the ship's doctor in Star Trek Voyager? The Doctor

The 26th of December is traditionally known as:

St Stephen's Day. 2. In which year was The Queen's Christmas speech first televised? 1957

7.Which character or characters have starred in all 6 Star Wars films (and have been played by the same actor/ actress)? R2 D2 and C3P0 – played by Kenny Baker and Anthony Daniels

3. What is the definition of a white Christmas in the UK? A single snow flake (perhaps amongst a shower of mixed rain and snow) to be observed falling in the 24 hours 8. Mr Sulu was the helmsman of the U.S.S Enterprise, but which ship did he later go on to command? U.S.S. of December 25th.

Excelsior 4. Which well known actor died on Christmas Day in 1977? Charlie Chaplin 5. Where was it always winter but never Christmas?

Narnia

9.In which Sci-Fi series/ film would you find the character Slartibartfast? Hitch-hiker’s guide to the Galaxy 10. An episode of which television series featured Rasputin, Queen Victoria, Gandhi and Noel Coward among others? Red Dwarf

Name the Dashboard- see the charts below and match them to the dashboards listed.

NHS data and definitions 11.What NHS programme do the initials Q.I.P.P represent? 13 .If a hospital episode had an unbundled HRG code of ‘SB10Z’ what treatment would you expect the patient Quality, Innovation, Productivity and Prevention to have had? Chemotherapy

12.The following KPIs can all be associated with SEC QIPP 14. A patient has a discharge code of ‘19’ – where will they programmes – match the KPI to the programme: be going on leaving hospital? Usual place of residence Day case rates Number of NHS health checks delivered Women:midwife ratio

Planned Care Staying Healthy Maternity and Newborn

IAPT practitioners

Mental Health

Catheter associated UTIs

Safe Care

15. Which 3 waiting times targets were no longer monitored after 31st March 2010? Inpatients waiting longer than 26 weeks, outpatient waiting longer then 13 weeks, revascularisation patients waiting longer than 13 weeks

y

Page 19

NEWS Innovation Expo 9-10 March 2011

Update on daily sitreps

The Quality Observatory will be exhibiting at the forthcoming Innovation Expo on the 9th and 10th of March at ExCel in London. We will be at stand 08 where we will be showcasing a number of analytical tools including those supporting the normalising birth programme, short stay hip replacement programme and Doppler. Samantha Riley, Kiran & Kate Cheema and Simon Berry will be manning the stand for the two days—so come along and say hello .

The last day for the submission of daily sitreps was Friday 25th February 2010. Thanks to everyone for their hard work in submitting information to the team.

As well as the team from South East Coast, Quality Intelligence East will have a display on the stand and there will be information available from a number of additional Quality Observatories around the country.

Further details are available at http://www.healthcareinnovationexpo.com/ Don’t forget to use our special discount code EXQO.

Professionalising Health Informatics Survey It is now nearly two years since the last User survey of the Professionalising Health Informatics (PHI) online portal: http://www.connectingforhealth.nhs.uk/phi. To help measure the continued success to date of the portal and gather in some additional feedback users are invited to complete a short survey. It should take about 5 minutes and can be accessed via: http://www.surveymonkey.com/s/ LJBVC29

Health Informatics Congress 5-7 April The British Computer Society Health Informatics Congress will take place 5-7 April 2011 at the Birmingham ICC. HC2011 is the UK's largest, most powerful & rewarding event for health & social care informaticians, ICT professionals & clinicians.

Enhancing Quality update Data for July-September is now available. For further information contact fatai.ogunlayi@southeastcoast.nhs.uk

Celebrations A number of birthdays have occurred in since the publication of the last edition of Knowledge Matters. Kate celebrated her birthday in January with a surprise party in a Chinese Karaoke bar in London—attended of course by a number of members of the team…..

Adam also celebrated his birthday in January, and in February Charlene and Aleksandra celebrated their birthdays on the same day (sadly no photos to share….)

Samantha takes a break For two weeks in February, Samantha took a well earned break at an Eco Resort in Sri Lanka. As well as lots of reading and sunbathing, Samantha managed to fit in some cycling, dancing, canoeing, jewellery buying and the odd cocktail or two. Samantha returns to the team refreshed and invigorated!

The three day conference & exhibition, combined with an innovative range of events & opportunities, is designed to challenge & engage all those working in health informatics & social care, including commercial organisations & other major stakeholders.

QIPP Hop Update The Secretary of State for Health will be speaking at the conference along with a wide range of experts in health informatics. A specific session will jointly be run by a number of Quality Observatories across the country.

The theme for this year’s conference is ‘Right place healthcare—exploiting the informatics potential’. For further info see http://www.hc2011.co.uk/

Since the QIPP Hop video went live on YouTube in December 2010, there have been 282 views of MC AC and his Queens in Productive Performance. The most significant number of views have taken place in England, however QIPP Hop has also proved popular in the USA and Sweden. If you haven’t yet had a chance to have a look—here’s the link http://www.youtube.com/watch?v=NWoVIbC2-M

E-mail Intuition Constant little messages nagging at the bottom of the screen, A minute ago there was but one, now there's seventeen!

Things are getting out of hand, let's stop and give some thought, to etiquette around e-mails, so we don't get too distraught.

"Can you do this?", "You need to know...", "Can you help me, please!", "For your info...", "To confirm...", "We need your expertise."

First things first - why write it down, when you can go and speak, Look! See, they're over there, they're not playing hide and seek.

Go through them all, one by one, sorting bad from good, Read through them all, thoroughly, make sure they're understood.

"Prioritise that one", "That's meaningless", "This wasn't meant for me!"

"Do that later", "File away", "I'm sat where you can see!".

Reply to one, reply to all, follow a hyperlink, Save attachments, delete spam, make the inbox shrink.

Do you need to attach those documents of multi megabytes?

A little link can get you there, and put the world to rights.

That mailing list, that's full of names, must it go to everyone, Target the recipients, make it personal, to help get the job done.

Make it useful, make it relevant, don't use it out of fear, Be more thoughtful, be more sparing, keep it clean and clear.

E-mail is a useful tool for sharing thoughts and to keep in touch, But use it wisely and with care, don't use it as a crutch.

Welcome back …...

……...& farewell

The team were pleased to welcome back David Graham earlier this month who rejoined the Quality Observatory for his final placement on the NHS Informatics Graduate Scheme.

This month we bid Nia a fond farewell after two and a half years as a performance analyst, alongside Charlene and Rebecca, in the Quality Observatory.

David will be supporting work on the development of tools to support GP Commissioners, assessing and recommending changes to Quality Observatory business processes and supporting Samantha with national work on a strategy to improve data quality.

Congratulations to David who got married earlier this month and returns from honeymoon in early March.

Nia has covered a diverse range of work in her time here, from 18 weeks to HCAIs and will be missed by people both within the SHA and across the patch. David Harries will be taking over the work currently undertaken by Nia. If you have any queries e-mail him at david.harries@southeastcoast.nhs.uk Leaving presents are currently a secret at time of writing, but will be revealed next time along with photographic evidence!

Good luck Nia—we will miss you!

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