Knowledge Matters Volume 8 Issue 6

Volume 8 Issue 6 February 2015 Welcome to Knowledge Matters Well it’s been an interesting 10 years I have been working for the NHS and there have been a lot of changes , but one thing that has been a constant is change! PCT mergers, SHA mergers, the grand Lansley plan with its initial mergers, and then subsequent disbanding of old and creation of new organisations along with more than a soupçon confusion and still it goes on.

The QO is hosted by Central Southern CSU and you may have heard that CSCSU is now merging with South and South West to create a new larger, more competitive organisation called South, Central and West CSU. Of course there is also the looming general election and one thing you can say is that regardless of your political persuasion, and whoever actually is elected, it’s obvious that yet more change will be on the way very soon after. Interesting and challenging times are ahead but it’s important not to lose sight amid all the political and organisational upheaval of what is important; patients and the quality of their care. That’s certainly what we will be focussing on while working with our customers over the coming months!

This month we have articles from Asthma UK on their Time to Take Action on Asthma Report, an article from Samantha Riley on Patient Centred Outcome Measures, an update on the FFT, an article on dealing with the inevitable challenge to the validity of your data and a handy guide to the various methods of automatic updating chart ranges, with their pros and cons.

So take a moment to sit down, make a brew and enjoy!

Inside This Issue : Making Connections—Asthma UK

2

Making Connections—Introducing Patient Centred Outcomes

10

Update on the Friends and Family Test

5

When People Question the Validity of your Data

12

Skills Builder—Dynamic Charting to Index or to Offset

6

Ask an Analyst—Working Out Census Hours

14

twitter.com/SECSHAQO issuu.com/SECQO http://www.networks.nhs.uk/nhs-networks/sec-qo www.QualityObservatory.nhs.uk

2

Asthma UK’s time to take action on Asthma report

By Dr. Carine Lewis, Senior Analyst, Asthma UK Asthma is the one of the most common long-term conditions in the UK, affecting almost 1.1 million children and 4.3 million adults – that’s 1 in 11 people. Every 10 seconds someone is having a potentially life threatening asthma attack,while more than 70 children are admitted to hospital because of their asthma every day. As a result, asthma has a significant impact on school absences and lost working days across the UK. Every year, asthma costs the NHS more than £1.1 billion in hospital admissions, drugs, and over 3.7 million GP visits.

Yet despite this, in May 2014 the first ever National Review of Asthma Deaths found that two-thirds of asthma deaths could be prevented with better routine care. Shocking patient safety concerns were also identified in the cases of those who died, with prescribing errors found in almost half of all deaths from asthma in primary care.

To help health services detect signs of poor asthma care and encourage them to act by implementing the standards, Asthma UK conducted a survey of more than 6,500 people across the UK to find out how the standard of asthma care they receive compares to what they should expect, as recommended by the BTS/SIGN Guideline. These are standards which acknowledge the urgent need to improve asthma outcomes and provide guidance on how to achieve this.

Asthma UK then presented these findings in a report which can be found here: http://www.asthma.org.uk/takeaction

What did we do?

Asthma UK carried out a survey, asking about the basic elements of clinical asthma care as outlined in the BTS/SIGN Guideline: diagnosis, annual reviews (including questions of control and inhaler technique), written asthma action plans, accurate treatment following admission, and appropriate discharge from hospital. According to people’s answers, their care was rated as green (excellent), amber(satisfactory) or red (poor). For care to rate as excellent (green) people had to report receiving care that included all of the basic elements of care outlined in the BTS/SIGN Guideline. Satisfactory care (amber) required more than half of the basic elements to be included. Poor care (red) meant half or less of the basic elements were included.

What did we find?

We found that only a fifth of people with asthma are receiving all of the basic elements of clinical asthma care.

Furthermore, four out of five children are not receiving all elements of basic clinical asthma care.

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3

Just under a quarter of people told us they had not had their inhaler technique checked, or had an asthma review in the last year. Shockingly, less than a third said they have a written asthma action plan. These are the three key aspects of routine asthma care where only a quarter had received all three of them. Research has shown that people who do not have a written asthma action plan are up to four times more likely to be admitted to hospital for their asthma. We are therefore calling on local NHS decision-makers across the UK to ensure every person with asthma is given care that meets basic clinical standards, including an asthma action plan.

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4

Asthma UK’s time to take action on Asthma report (continued) Quality Observatory Asthma UK asked the Quality Observatory to provide local data spreadsheets breaking down the survey results in order for people to see the local standards in their area and the potential cost savings that could be made.

These interactive charts enabled providers and commissioners to see the quality of asthma care, as reported by patients, for a number of different areas where NHS data is unavailable. As a result, we can see some indications of where improvements could best be made at a local level. Asthma UK is therefore calling on all CCGs in England, Health Boards in Scotland, ICPs in Northern Ireland and Local Health Boards in Wales to ensure every person with asthma has a written asthma action plan, and deliver care which fully meets the BTS/ SIGN Guideline to improve outcomes for people with asthma.

You can find the charts, the data and good practice tools to help improve local asthma care at http:// www.asthma.org.uk/takeaction-hub

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5

Friends and Family Test Extends

By Trishna Julha, Programme Support Analyst, Quality Observatory The atmosphere within the Friends and Family Test (FFT) collaborating team at the Quality Observatory was rather atypical at the beginning of the year – due to novelty in the FFT it was all excitement, although the elders would recommend a slow but steady start of the year!

After GP practices, it was now the turn of NHS funded community and mental health services providers to start implementing the Friends and Family Test (January 2015).

All patients/service users, including children and young people, receiving treatment in mental health wards, or receiving medication, counselling or therapy for conditions such as dementia, stress and alcohol addiction, have the opportunity to provide anonymous feedback on the treatment or care received. Patients who receive care or treatment in their own homes or local community are also able to comment. It reinforces NHS England’s commitment to give every patient the opportunity to provide feedback on the care they have received in order to highlight and address concerns faster than more traditional survey methods.

The first submission of data for these organisations, including early implementers, takes place in February 2015, relating to responses received in the month of January.

Since its introduction in April 2013, millions of patient responses have been gathered nationally, with continuous extension to cover most NHS funded health care settings. It started in NHS Trusts’ Inpatient and A&E services to gradually extend to Maternity. As at 2014, more than 4.5 million responses were collected in Inpatient and A&E services, and over 500,000 in Maternity services. The table shows 2014 figures.

More excitement indeed at the Quality Observatory, but there is also an even greater determination to sustain the quality of service offered, as more is expected in the coming months for the FFT programme. In April 2015, FFT will be rolled out in outpatient, ambulance and patient transport services, and dental practices. Day cases will also be covered and the data included within the submission of Inpatient FFT data.

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6

Dynamic Charts - To Index or To Offset

By Amit Chavda—Specialist Information Analyst Before we start going through formulas and how to develop graphs, let’s explain what a dynamic chart is and why do we need it. A dynamic chart is one that adapts to a data range that changes in size. A dynamic chart expands automatically to data that is entered. Once it has been set up, all you need to do is add data into your table and the graph will adapt to your data.

Let us first begin by providing an explanation of Offset and Index.

Offset: Returns a reference to a range that is a specified number of rows and columns from a cell or range of cells. The reference that is returned can be a single cell or a range of cells. You can specify the number of rows and the number of columns to be returned. (Office Online, 2014)

Index: Returns a value or the reference to a value from within a table or range. There are two forms of the INDEX function: the array form and the reference form. (Office Online, 2014)

Both Offset and Index are powerful functions within Excel. However, Offset does have one downside, which is that it is volatile. What we mean by this is that Offset will recalculate the entire array or functions associated with that cell to give you a value. So, for example if the cell uses another function and calculation on another sheet within your spreadsheet, it will recalculate all of these to achieve the desired value in the selected cell. This therefore can slow the spreadsheet down and make is more vulnerable to errors. Also, the user has to ensure that any changes that are made in any previous cells work so that they do not conflict. Index on the other hand does not require all these steps to make it work. Index uses that value within the cell and doesn’t require recalculation.

So does it matter which one you use to Dynamic chart?

No it does not. The thing is that you are comfortable with what you use and understand how it works.

The OFFSET function:

OFFSET(REFERENCE, ROWS, COLS, [HEIGHT], [WIDTH]) The INDEX function:

INDEX(ARRAY, ROW_NUM, [COLUMN_NUM]) OR

INDEX(REFERENCE, ROW_NUM, [COLUMN_NUM], [AREA_NUM])

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7

Dynamic Charting using OFFSET .

Date Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 Oct-12 Nov-12 Dec-12

Sales £123.00 £456.00 £789.00 £963.00 £852.00 £741.00 £147.00 £258.00 £369.00

Let us assume the data set to the left. This can be sales data for a period of time, a year for example.

If we look at the Offset formula and break it down: Reference: is the starting point for the range of data, so on our data we want the cell that reads January 2012.

Rows: the number of rows we want to go up or down, which for our dynamic chart we don’t want to. So how this works is, if we put 1 the equation will move one setup down - so to February 2012. So we leave this as blank as by default it is zero just press comma to move onto column.

Also remember that with Offset, the reference starts as 0.

Cols: the number of columns we want to move to the right or left. Right is a positive number and left is a negative number. However: this can become confusing. It is therefore important to place/setup the data in a way that will make it easy for you. For our example we don’t need to move from our starting position so leave it blank as by default it is zero just press comma to move onto Height.

Height: is the total number of rows we want to capture or go down. So what we want to use here is the COUNT formula as each cell has a serial number, which counts the number of rows down. We do this by highlighting the rows we want to include. In this DO NOT just put $C:$C this will count the entire million rows. Just use what is required, so for three years’ worth use 36 rows.

Width: the number of columns we want to include in our formula. For our example we do not want to so we leave blank and close parenthesis Anchor all cells by pressing F4.

The formula should look something like this: OFFSET($B$4,,,COUNT($B$4:$B$21))

Dynamic Charting To turn this formula into a dynamic graph we need to name a range. To name a range in Excel 2010, click on the “Formula” icon on the ribbon at the top and click on “Name Manager”.

Click on “New” and give the data a “Name” for example “Date”.

In the “Refers to:” paste our Offset formula into this box. Excel will put speech marks around the formula. Remove these, you will see these in the box above.

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8

Dynamic Charts - To Index or To Offset

By Amit Chavda—Specialist Information Analyst The formula should like the below image.

Click “OK” and “Close”

Now, repeat the whole procedure again for Sales and do not forget to anchor the formula as you go along. Once you have done all this, you can see that the named range works by going back to the named range box, clicking on the formula and you will see the little ants moving around the selected box. To build a dynamic chart it is important to know that the equations work. IF they do not, go back over the steps to ensure they do.

Once all is working we can build our charts.

The easiest way to build a chart is to press ALT+F1 or click on the “Insert” tab on the ribbon at the top of the screen and select the type of graph. To get to the box you see here, right click on the chart and click on “Select Data…” and the box above will appear. Click on “Add”.

This box will appear. Don’t worry too much about the “Series name”. All we want is the “Series Values”. Remove everything in the “Series Values” box. Click anywhere on the active spreadsheet.

You will notice that in the “Series Values” box something will appear like in the example.

What is IMPORTANT here is the Sheet3! bit as it links the data to the right tab.

Delete the $G$16 bit and press F3.

So, by pressing F3, this box will appear, what has essentially happened is that you called for the list of named ranges we produced earlier, such as Date, Sales, Offsale etc.

Click on the data you want to chart, so in this case we want the Y-axis to be the sales, so we would click on “Sales” from the list and OK.

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9 You will see that “Sales” will replace the $G$16 in the Series Values box. Click OK. For the Date in the “Select Data Source” box click on “Edit” under the “Horizontal (Category) Axis Label” and follow the steps as above.

Make sure you have =Sheet3! in the box, press F3 and from the named range list select “Date”.

Dynamic Charting using INDEX Let’s go through the formula.

Date Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 Oct-12 Nov-12 Dec-12

Sales £123.00 £456.00 £789.00 £963.00 £852.00 £741.00 £147.00 £258.00 £369.00

Array: the range of cells we are interested in, so we are interested in the cells from Jan-12 to Dec-12.

Row_num: the number of rows you want to go down. Again, by putting a number here like 7, will go down to Jul-12 and will not include the other months. Thus, we would use the same as in Offset the COUNT formula. COUNT(ALL THE CELLS THAT YOU WANT TO BE USED IN THE DYNAMIC CHART). So, for our example from Jan-12 down to Dec-12.

Column_num: the number of columns you want to include.

IF we leave the formula like this it will retrieve the last cell in your range so we need to do AN IMPORTANT STEP we need to turn the index into a cell reference. We do this by building a formula that starts at our first cell (Jan-12) colon the index formula. This in turn will deliver the values with in our data range.

The formula would look something like this. Starting at B3:Index formula.

=B3:INDEX(B$3:B$40,COUNT(B$3:B$40))

Again, remember to do smart Excel and only include the cells that are required and not $A:$A.

To make the dynamic chart you do exactly same as you did for the Offset; paste the formula in the “Name Manager”, give it a name and make sure it works.

Follow the steps as in the Select Data bit for the graph.

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10 Introducing Patient Centred Outcome Measures (PCOMS)

By Samantha Riley—Director of Insight NHS England Hello everyone, with the Friends and Family Test programme pretty much finalised, over the past couple of months I have been working on a new and exciting project – Patient Centred Outcome Measures.

In December, NHS England launched a bidding process to access funds to develop Patient Centred Outcome Measures (PCOMs) for conditions affecting Children and Young People. PCOMs is a relatively new concept which involves putting patients at the heart of the development of measures rather than what has traditionally happened with clinicians agreeing on what are the most important outcomes for patients and then consulting with patients. PCOMs should therefore reflect the most important outcomes for patients living with condition/symptoms.

48 bids were received which were reviewed by a multi-disciplinary/multi agency panel including voluntary sector representation and a parent on 16th January. Each bid was scored against the a range of criteria including impact, involvement and sustainability.

Funding was available to support 7 sites across the country – details of the successful projects appear below. NHS England will be monitoring progress with each of the projects and intends to hold a learning event late autumn.

•

Great Ormond Street Hospital for Children NHS Foundation Trust: To develop Goal Based Outcomes for psychological interventions as part of a child’s medical treatment, across a wide range of ages and medical conditions. The medical conditions will include all those within the specialties of General Surgery, Craniofacial anomalies, Cleft Lip and Palate, Plastic Surgery (hand, ear anomalies, birthmarks, vascular malformations), Urology, Cochlear Implant, Spinal Surgery, Orthopaedics.

•

Evelina London Children’s Hospital, part of Guy’s and St Thomas’ NHS Foundation Trust: This bid builds on ground breaking work already undertaken to develop online mechanisms to engage with children. This project will involve the development of an online animated PCOM which will allow children aged 5-10 with chronic conditions who require admission to hospital to: a) identify the most important outcomes for them, and b) record how effective their treatment is in delivering these outcomes.

•

Alder Hey Children’s NHS Foundation Trust (linking to other hospitals across England): Three strands of work are included in this bid:

◊

PCOM to evaluate the impact of respiratory problems on children with severe neurodisability, and their families (such as Rett’s syndrome and Downs syndrome);

◊

PCOM for children and adolescents with Primary Ciliary Dyskinesia (an inherited lung condition for which there is no cure);

◊

Development of the “The Adolescent Driven Outcome Measure (ADOM)”. To be designed by individual adolescents with chronic conditions, who populate it with the items that are specifically important to them, and who themselves determine how improvements (or detriments) are scored.

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11 •

University of the West of England, Bristol (working with University Hospitals Bristol NHS Foundation Trust, Children’s Hospice South West and Palliative Care Working Group): This project will provide robust and meaningful patient centred outcome measures for children and young people receiving palliative care services by collating interactive electronic communications between patient, family and professionals via a new and innovative tool that has already been developed.

•

Nottingham University Hospitals NHS Trust: This bid is focussed working with children and young people to define the domains for a Patient Centred Outcome Measure (PCOM) in children and young people admitted for self-harm injuries or eating disorders.

•

North of England Commissioning Support (working with the Experienced Led Commissioning Support Programme and other voluntary and community sector organisations): This project will focus on developing a PCOM for children living with asthma. This PCOM will help commissioners understand how people feel about treatment, what outcomes matter to them most and how outcomes change over time. It will support the development of outcomes based commissioning and contracting for asthma care in children.

•

Shropshire CCG (working in collaboration with a range of voluntary sector organisations): The aim of the project will be to improve outcomes for young wheelchair users through devising and implementing a PCOM for wheelchair and posture services in Shropshire. This includes children and young people with long term disabilities, neurological conditions, congenital conditions or those who have an injury/disability

It has been really interesting to see people’s reactions to PCOMs. Some people believe that PCOMs are the same as PROMs. I disagree. I think that this is a fundamentally different approach. Others oppose the concept as PCOMs are not prescriptive – this is not about utilising existing validated tools – this is about breaking new ground and in some cases working with children who have previously not been able to express a view on their treatment and outcomes.

Another camp do not support PCOMs as they are person centred and we therefore are unlikely to end up with data that is comparable.

In the main, front line staff are really supportive and excited about the concept. This is another initiative which puts patients truly at the centre and gives them a voice.

Surely this must be a good thing? As ever, I’d be interested to hear your views! samanthajriley@btinternet.com

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I Don’t Believe It! – When people question the validity of your data.

By Adam Cook

So you’ve spent hours and hours on a piece of work, presented a series of tables and charts that meet the specification you were working to, and the reaction you get is a roomful of Victor Meldrews not believing the data that you have put in front of them. Clinicians take note – you’re the worst at doing this. As professional analysts we know you’ve got issues with the data and actually we normally understand what those issues are but your emphatic and often instantaneous, disbelief is so dispiriting. Please be a bit more thoughtful and tactful. Although we analysts are just as bad – my instinctive reaction to someone who says they don’t believe the data is to tell them that it originates with their organisation and to make sure that they are recording it correctly.

What happens now? Well I’ve seen projects, reviews, and even wholescale service redesigns stopped in their tracks simply because someone objects to the data. Even if it doesn’t come to that it can be a hindrance and a large factor in slowing down processes as data validation and reworking goes on.

It’s not wrong to question the data. In fact I would encourage anyone in receipt of data to scrutinise it thoroughly – after all, we can all make mistakes. However it is the out of hand rejection that is the real problem. How can we, as analysts, defend data against the likes of senior managers and consultants who have decided that their status means that they know best?

It’s a difficult situation to work through, especially as we are already acutely aware of the limitations of the data that we can get centrally. Let’s take SUS (and as a consequence HES) data as an example. We know that this is essentially an administrative dataset – yes it has clinical information on it, but that’s not the primary function of the data. Also it is one step removed from the care given – clinician notes have had to be interpreted by coders to turn those notes into information that can be used by the system.

It’s a favourite tactic of many people to blame the coding - it’s also a very unfair tactic. The coders are highly trained professionals, and whilst not being paid as much as the doctors, they know what they are doing.

Part of the blame must lie with those clinicians whose note-taking isn’t clear, consistent or complete. Already we’re at an impasse – the clinicians blaming the coders and the coders blaming the clinicians – when, in fact, it’s neither. The vast majority of coding is good, and the vast majority of note-taking is good. It’s just a first place to go to when you want to argue over the validity of the data.

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I Don’t Believe It! – When people question the validity of your data.

By Adam Cook This can be worked around, but it needs cooperation from all sides. I’ve recently been working on a project involving two trusts. My initial data from SUS was questioned by consultants and so the project group got the two trusts to pull the same data and EVAR (Endovascular AAA repair) compare it to what I had done. I had expected there to be differences – there always is, we’ve talked about the differences between PAS, SUS & HES data at length in the past – but I didn’t expect the differences to be quite as small as they were – an instance of one or two patients, and in some procedures it was spot on. In this case the project group accepted the SUS data and we were able to move forward.

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The other way to go forward with this, when aggregate numbers are called into question, is to break down the data into individual lines of data. Obviously we don’t have any patient identifiable data available but using admission and discharge dates, consultant codes, patient age, diagnoses, procedures and other such fields where the patients can be compared to local information. This can be time consuming, but it does work, and using this methodology can help refine the data. I’ve done this on several projects, with different results. On occasion the data is vindicated, and the initial gut reaction to it was wrong. Sometimes it has come down to definitions, and once we’ve had a look at individuals certain procedures or diagnoses are filtered out. (There’s a lesson there in getting the specifications of the job right at the outset!) Sometimes it is just down to data quality – one of my esteemed colleagues was working on data that was looking at transfers between trusts and the data didn’t add up, and when it was taken down to the individual record level it could be seen that some trusts were recording the transfers differently resulting in double count of episodes.

EKH

Medway

Another method of stopping the validity of data being raised in the first place is to take the data directly from the people who want the analysis themselves – then they know that the data reflects what they believe. This approach can have concerns from the analysts point of view – you need to be sure that you’re getting all the data that you need and it’s all specified correctly. It’s all very well them giving you the data, then a month down the line them saying that it’s great, but could you now split it by practice, but the original extract didn’t have practice on it. So it’s a balance between getting everything just in case, and getting the minimum that you think can predictably be useful.

I would conclude by saying that data validity is often used as a block in the system, and is frequently fought over as a contentious issue; however it need not be the case. The key factor is cooperation and understanding on both sides – as I hope I have shown, it is possible to rationally work through the issues and come to a consensus on what the data shows and how it needs to be interpreted.

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14

Working out Census Hours ?

Application: MS Excel 2007 + Dear Ask an Analyst, I’m having problems with my spreadsheet, I have a dataset that includes patient arrival date and time and departure date and time in my department, I need to calculate the numbers of patients in the department at specific times 18:00 20:00, 22:00 and midnight, I can’t seem to get the numbers to add up, i’ve tried using if() functions which seem to work until the admission goes over 24 hrs Here is an example dataset: I hope you can help!

Arrival date 01/01/2015 01/01/2015 01/01/2015 01/01/2015 01/01/2015

time 22:21 22:56 23:54 18:00 22:21

Departure date 02/01/2015 02/01/2015 02/01/2015 02/01/2015 01/01/2015

Departure time 05:22 03:00 04:00 01:00 23:55

Cheryl Davis Business and Performance Manager- A&E Southampton University Hospitals NHS Trust

Solution: Complexity 3/5 — Date Time , arrays and IFS() Hi Cheryl Thanks for getting in touch.

Firstly let’s take a look at your data set : In your data you have arrival date and arrival time in separate columns.

You’ve been trying to deal with the date and time separately which is going to be difficult to deal with. And require lots of complicated Nested If statements!

With your current data structure you would need to do a 2 step process; first you would need to do a date check— Is my census date in-between the arrival and departure date, and then if True, do a time check—is my census time in-between the arrival time and departure time—it makes my head hurt just thinking about it!

What we would recommend is to merge your columns to create an Arrival DateTime field and a Departure DateTime field. This is really easy! Excel handles date and time really well! All you have to do is add the Time field to the Date field e.g: In cell E3 of our example the formula is ; =A3+B3

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Once we have created Arrival DateTime and Departure DateTime we can then use an If statement to indicate whether that patient was present at a specified Census DateTime. In the example below we use 1 to indicate present at specified date time and 0 if not. This allows us to then to a simple SUM() on the column to create our census value!

This is date and time of Census; make sure Here we can now use a simple If statement to return a value that the cell is time formatted — Excel should automatically format it, but best to check! we can count!

IF the Census DateTime is bigger (>) than the Arrival DateTime AND smaller (<) than the Depature DateTime =IF(AND(G$1>$E3,G$1<$F3),1,0)

Add up the column = SUM(G3:G10) You can obviously adjust the layout to suit ..,.. Now this can be adjusted to suit how you want to deal with people who are admitted / depart right on the census time? Are they in or out? Simply use >= / =< to suit your situation.

But wait ,we are not quite finished yet! It is also possible to go directly to the last step and do all the counting in a single formula! Now this is normally the bit where I would show off and start talking about array formulas! However if you are using Excel 2007 + there is the =COUNTIFS() function that can be used ,that builds on the Countif () function and allows you to use multiple evaluations, like in the example below.

=COUNTIFS($E:$E,”>=” & G$1,$F:$F,”>=“ & G$1)

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New Office News Big news this month! The QO’s new office fit out is finally under way at The Gables in Horley. After nearly 2 years of primarily working out of an office suitable for a maximum of 4 (currently shared between 14 of us) the light at the end of the tunnel can finally be seen. All cabling and partitioning works will be done by the 6th of March and hopefully we will be fully connected up to the N3 ready for a full move in by the end of March.

50 Shades of Safety...

Come close to me, my darling

I'll ensure infection

Sometimes I'll use a catheter,

There's no cause for alarm,

Will not find its way therein.

I've done it many times before,

If you remember the Safety word, I'll give you just the footwear You will not come to harm.

So you don't slip or trip,

I will be most hygienic, And try not to leave you sore.

If you're scared of falling, The dangers are inherent,

I'll give you something to grip.

The risks have been assessed,

There's no cause for alarm,

I'll make sure there is no harm

I may require you to stay in bed

Once you are undressed.

For long periods of time, I'll turn you and I'll clean you

There may be an injection,

So, come close to me, my darling If you remember the Safety word, You will not come to harm.

To stop the sores and grime.

A prick against the skin,

Simon says…….

Did you know grapes are diamagnetic? What does that mean? Well they are repelled by both north and south poles of a magnet.

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: Hosted by: Central Southern Commissioning Support Unit

E-mail: info@qualityobservatory.nhs.uk

To contact a team member: firstname.surname@qualityobservatory.nhs.uk