data for chronic obstructive pulmonary disease (copd) and asthma: making a real difference

NHS Improvement - Lung

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Data for chronicobstructive pulmonarydisease (COPD) and asthma: Making a real difference

CONTENTS

How to use data to improve primary care

How to use data to improve acute care

How to use data to improve home oxygenservice assessment and reviews (HOS-AR)

How to use data to improve asthma care

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Data for chronic obstructive pulmonary disease(COPD) and asthma: Making a real difference

Data for chronic obstructive disease (COPD) and asthma: Making a real difference

NHS Improvement has worked with primarycare sites across England, to explore howsupported self-care and regular review canbest be delivered in order to improve theoutcomes and quality of care offered topatients. This includes how to optimisemedicines use and reduce waste.

Are we using all the data we are collecting to improve patient care?

Why access primary care data?• We spend one billion pounds a year on

respiratory inhalers. Our project work has identified that there is often prescribing outside of guidance – often patients on incorrect medication, too much or too little, and our project sites have improved compliance and reduced waste, reducing their spend on monthlyprescribing costs. Can you identify patients who are on medication, but without a diagnosis?

• The 2010 NICE guidance for COPD recommendsthat medications are given in line with lung capacity and patients with lower lung function are reviewed more frequently – does this occur in your practice?

• Can you notice subtle changes to your patients’ condition? Ensure that you are capturing data on lung function, exacerbations, admissions and medicines use accurately and consistently. Reviewing this information can help optimise treatment and timely intervention

• Can you identify patients with multiple long term conditions? Prevalence data from Birmingham suggests 32.8% of COPD patients have hypertension, and 26.5% have CHD. Couldyour practice be more efficient by managing multiple conditions together, reducing duplication of tests and appointments?

• When do your annual reviews take place? COPDis a very seasonal disease, and often we have noticed that reviews occur in response to the QOF deadline, or increase during winter. It mightbe possible to be more proactive, and consider reviewing patients during the summer months when patients are more likely to be well and able to attend.

• Often we collect good data, but fail to act on it. For example, measures such as %FEV1 predictedor MRC dyspnoea score should help us target appropriate treatment and risk stratify patients to ensure they are on the best treatment for their needs. Without this information it is difficult to optimise treatment in line with the national guidance or track changes that allow usto support patients appropriately

• Recording of exacerbations is inaccurate – less than a quarter of patients have their number of exacerbations recorded nationally

• By identifying more of your undiagnosed population you may increase QOF income

• There are various tools to help practices identify which patients are at high risk of admission, or who need more interventions, both at population and individual level. These tools can help identify which patients you may want to review or manage differently one such approachis the DOSE index (covering dyspnoea, airflow obstruction, smoking status and exacerbations).

Our service improvement projects in primary carehave all recognised the essential role data has inmonitoring how we are improving towards ourimprovement targets, identifying patients withincreasing risk or incorrect medication, and formonitoring compliance with guidance. Our siteshave used data to help achieve:• Reduced monthly spend on medication • Reduced rates of admission to hospital• Improved patient satisfaction and improved

management of breathlessness.

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Query Primary Care systems directlyIf you work in general practice, you are probablyalready familiar with your practice database,however you may need some support tounderstand the data you can access.• Most practice databases include the functionality

to search your population, and return lists of patients meeting selected criteria.

• There may be a number of existing database queries. It is often straightforward to access a listof your COPD population, often from QOF related queries.

• The PCRS have produced an excellent summary of the commonly used Read Codes for COPD, which might be useful in constructing queries in your practice. Consistent use of Read Codes allows you to record, track and respond to changes in your patient’s condition, their health care use and outcomes of the care you provide. www.pcrs-uk.org/copd_nice/ read_code_table.pdf

• Training is available in querying your primary care data from your system suppliers, and your local PCT/CCG may have expertise in using data.

• Organisations exist that specialise in getting the most value from your data. PRIMIS were established to deliver consultancy and training inaccessing primary care data, and provide supportin using your data. www.primis.nottingham.ac.uk

Use nationally available benchmarking dataSometimes, just a simple view of the nationallyavailable data may be good enough to startimprovement work by highlighting where youmay be an outlier, or raising questions about whyperformance is where it is:• APHO Practice profiles for respiratory disease

cover Prevalence, performance on QOF, and data on your local population and patient satisfaction. www.apho.org.uk/PracProf

• INHALE – This new national service provides a PCT level summary of national indicators across admissions, readmissions, total spend, and across various outcome measures. www.inhale.nhs.uk

• The project in Sheffield found many benefits from simple practice benchmarking data for admission rates, medication rates, and QOF scores, using NHS Comparators. This site gives everyone access to local admissions data in an easy but comprehensive way. www.nhscomparators.nhs.ukSheffield case study: http://system.improvement.nhs.uk/ImprovementSystem/ViewDocument.aspx?path=Lung%2fNational%2fwebsite%2fManaging_COPD_publication%2fSheffield_Target_support.pdf

• Medicines spend data by category, practice and cluster is available for practices to use from ePACT. Even simple summary data was enough for our Victoria practice project to demonstrate a reduction in medicines spend of over £1,000 per month. For more information, the case studycan be downloaded at: http://system.improvement.nhs.uk/ImprovementSystem/ViewDocument.aspx?path=Lung%2fNational%2fwebsite%2fEarlier_diagnosis%2fAldershot.pdf

Data for chronic obstructive disease (COPD) and asthma: Making a real difference 5

Consider pharmaceutical industry supported toolsThese tools can provide simple dashboards of yourcurrent performance against guidance, suggestareas for improvement, and may bring nursesupport for implementing changes:• GlaxoSmithKline POINTS tool – this powerful

tool has been used already in around a third of practices in England, and provides a useful dashboard overview, but also detailed files showing the quality of care for your patients based on compliance with national guidance

• Astra Zeneca and other pharmaceutical companies can provide a wealth of useful information on quality and cost indicators, in an easily interpreted and usable form.

Advanced tools for accessing data In our project work we have come across manyadvanced tools which allow for whole clusters orPCTs to access data, analyse medicines use, andvisually present data across their whole area.Some examples include:• Eclipse Live – This new, innovative tool, is being

developed by Prescribing Services Ltd by Dr Julian Brown, and piloted by the service improvement project at the Isle of Wight, It allows for detailed medicines management questions to be answered with comparisons to both local and national medicines use levels, andfor Read Coded primary care data to be analysed across a PCT or CCG level area. https://www.eclipsesolutions.org/EclipseInfo/AboutUs/

• MSD Informatics offer solutions for accessing data across PCTs, and provide data extraction tools to support clinical audit and assessing clinical risk, with implementation in our Coventry improvement site.

• Apollo SQL Suite (www.apollomedical.com) is a commercial tool that can provide a number of queries that help support you to achieve your QOF measures, but also to review your COPD population health. In Hammersmith and Fulham, a whole PCT dashboard was created using data from Apollo and a data warehouse created the information experts at their PCT. Fulldetails are in the lung improvement case study: http://system.improvement.nhs.uk/ImprovementSystem/ViewDocument.aspx?path=Lung%2fNational%2fwebsite%2fEarlier_diagnosis%2fData_warehouse.pdf

• Optimal Patient Care worked with Leicestershire PCT to extract data from all practices, and identified wide variation in medicines use, and many indicators of quality care that could be fedback to individual practices to support improvement. www.improvement.nhs.uk/lung/NationalProjects/ManagingCOPD/CasestudiesinCOPD.aspx

Web links and more informationFor case studies and more information onaccessing data -www.improvement.nhs.uk/lung/RespiratoryResources/Guidetodataforlungimprovementprojects.aspx


Case for changeThe Right Care atlas of variation for RespiratoryDisease shows us that there is unwarrantedvariation in COPD admission rates, even whendeprivation factors are considered, and thatoutcomes in terms of length of stay, mortality, andoverall spend vary across the country.

Our analysis has shown us that the average lengthof stay was 6.6 days, yet there is a two-folddifference between the best and worst PCTs forCOPD length of stay. If the length of stay forabove average Primary Care Trusts was reduced tobe in line with the national mean, this would savethe NHS approximately £14 million, and 65,000bed days. Reducing the length of stay to the levelof the PCTs in the top quartile increases thepotential saving to £32 million and 146,000 beddays.

These are crude estimates, but we know that wehave already seen a 16% reduction in the numberof bed days, and a reduction in the mean lengthof stay by one day over five years, and that thereis still more that can be done in improvingservices, such as improving access to seven daycare, use of inpatient and discharge care bundles,and improving self-management to preventadmission. Evidence from our project sites andfrom published evidence has shown that there isthe potential to reduce admissions by 20% ormore, in a short time scale.

These savings often require a whole pathwayapproach, including community wide COPDreviews, with investment and support forincreased community based services. However,even on our more focused acute projects, we haveused data to identify and drive savings in length ofstay and readmissions.

Key facts • Total number of COPD admissions has been

consistent at around 100,000 per year for five years, at a total cost of £236.6m, but with an eight-fold variation in the rate of admissions from PCTs.

• The number of bed days has reduced by 16% over the last five years.

• The number of 0-day admissions without an overnight stay has doubled from 5,000 to 10,000 over five years.

• Only 50% of patients are managed by a respiratory clinician.

Key learning• See where you are compared to others by

looking at National available data . INHALE – This new national service provides a PCT level summary of national indicators across admissions, readmissions, total spend, and across various outcome measures, and can help identify areas for improvement in your trust. www.inhale.nhs.uk. Also, the Right Care NHS atlas of variation in healthcare for people with respiratory disease provides a clear overview of the difference in outcome, and how your area compares to others. www.rightcare.nhs.uk

• Understanding the patterns of demand and capacity within your area can help you plan and organise services effectively. Review variation in demand by day and time of admission, day and time of discharge and time of year, to help you understand what your service looks like and identify what improvements could be made.

• Sites have used demand and capacity effectively through matching the time when they aim to discharge patients to the peak times when patients are admitted. This ensures specialist beds are available in time for new patients to be admitted, which reduces ‘outliers’ – i.e. patients on incorrect wards.


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• Mean length of stay is used nationally as a statistic for comparing length of stay in acute providers, however when describing the distribution of length of stay, mean is not alwaysthe most helpful statistic to use. Nationally, the distribution of length of stay shows us that we have many short stay patients, but the average isaffected by the very sick patients in our hospitalsand those whose discharge may be delayed while they wait for appropriate social care to be provided.

• Statistical Process Control (SPC) is a technique which plots either averages, or individual results over time, alongside control limits, that demonstrate when a process is controlled and predictable, and which results are outside these predicted limits. This helps you to identify and understand the variation in your system.

• Get to know your trust analysts, performance managers and coders, as these people will be able to access and show you how best to use the data to answer your questions.

• How your data is coded may vary in your local area, so often looking more broadly than ‘primary COPD’ in your questions can be helpful.Also, consider if your improvement work is focused on a particular disease group, or on a particular ward within the hospital, as you may wish to look at patients in the respiratory ward beds, who do not have a respiratory diagnosis. You will need to use a variety of data, often using terms such as HRGs, and secondary diagnosis, to get a picture of patients who may need to be under your care.

• Capturing your interventions along the patient pathway is important. Care bundles are a good example of ensuring core components of care are implemented and continually monitored for their effectiveness and impact Auditing their use can provide useful process data. Respiratory care bundles have commonly been used for COPD, asthma and pneumonia.

• When presenting data, make sure it is presentedin a format that your audience understands, anddon’t try to include every data item you have: having too many measures can be very confusing.

Understanding length of stayMean length of stay (LoS) is a nationally usedmeasure used to compare trust performancenationally for a range of conditions, however it isa crude indicator and doesn’t help us tounderstand how the hospital beds are being used.By breaking down LoS data to provide more detailwe gain a clearer understanding of theadmissions, and what the mean LoS reflects.

Figure 1 shows us the percentage of patientsstaying for each length of stay. We can see that10% of patients have ‘0 day’ LoS, 15% have aone day LoS and so on. The graph is ‘trimmed’ at20 days and the small number of patients whostay longer than 20 days have not been included.


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Figure 1: Percentage of all admissions

Figure 2 shows us the cumulative proportion ofadmissions with a length of stay of equal or lessthan that number of days. We can see from thechart that 50% of patients have a LoS of 3 days orless and 80% of patients have a LoS of 8 days orless. Only 6% of patients stay for more than 20days.

Figure 3 shows us the proportion of bed daysaccounted for by these patients. Remember that50% of patients have a LoS of three days or less:we can see that these patients account for about12% of hospital bed days. The 80% of patientswho have a LoS of eight days or less account for40% of hospital bed days for COPD. Rememberthat 6% of patients who stayed for more than 20days? They must account for the remaining 28%of hospital bed days.

Many differences can be observed in the shape ofthe data across your trust, when compared to thenational averages.

• Many short, zero day length of stay, could indicate that you are either having too many unnecessary admissions, or discharge patients more quickly than most. Nationally, around 10%of admissions are sent home in less than one day.

• A high proportion of long staying patients can have a big impact on your mean length of stay, and could indicate issues around discharge processes or transfer to social care. This will be shown as a ‘long tail’ in your data. By splitting your data into proportions for example those patients who stay longer than seven days and analysing these separately can help you identify where your service improvement work will have the biggest impact.

• The majority of bed days are taken up by longer staying patients. This may seem like common sense, however often the focus of improvement work is on short stay patients. Figure 3 shows usthat over 50% of bed days are for the patients staying at least 11 days, therefore initiatives focussed on short-stay patients may have limited impact on total bed days or length of stay for COPD.


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Figure 2: Percentage of all admissionsthis duration or less

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Figure 3: Percentage of bed daysaccounted for by patients with thisLOS or less

Source: HES, Primary diagnosis COPD, Finishedadmissions, 2010/11.

• Improvement may be shown by the peak of the curve shifting to the left, indicating a reduction in the length of stay for the majority of your patients.

Questions to ask when reviewing variation in length of stay• Look at the LoS by the day of admission. You

may notice peaks in LoS on certain days. • What is different about these days? • Do you have daily ward rounds?• What is your clinical decision making

process like?• Do you have nurse led discharge?• Do you have seven day working?

• Compare the number of admissions by the time of day. When do your peak admission and discharge times occur?• Are patients waiting on other wards for a

specialist bed?• Do your patients have to wait for tablets?• Do you have a discharge lounge that you

could use / do you use your discharge lounge as much as you could?

• Does length of stay vary over the year, particularly during the winter period? Ask why, and identify what your teams do differently during these times.

• How long do patients stay in A&E and medical assessment / decision wards?

• Does your trust aim to admit all COPD patients direct to a specialist ward?

• For patients requiring longer term recovery, are different types of beds often used? e.g. community hospitals, which can take patients elsewhere.

• Are COPD patients frequently admitted to wardsother than respiratory wards? What are the reasons for this?

• What process do you have in place to ensure that appropriate patients are seen by a respiratory specialist?


Some key terminology for hospitaladmissions data• PAS – Patient Admission System – this is

the generic name given to systems in hospitals that capture hospital data.

• HES – Hospital Episodes Statistics is the national activity statistics that are collected and presented, based on data from A&E, inpatient and outpatient care.

• HRG – Healthcare Resource Group, this is a standard group of clinically similar treatments used as a common grouping of hospital care, and are used to set the standard price of care in Payment by Results and the Tariff. The main COPD HRG range over severity of COPD, with or without NIV, and with or without complications.

• Diagnosis, recorded by ICD-10 code, is the latest version of the International Statistical Classification of Diseases and Health Related Problems, a comprehensive classification of all diagnoses. Each admission will have several diagnoses coded to it when the patient is discharged from hospital.

• OPCS Classifications of Interventions and Procedures (OPCS-4) are used to define and categorise procedures in hospital, such as non-invasive ventilation

• The British Thoracic Society has producedan excellent guide to data coding, which is available online at: www.brit-thoracic.org.uk/Portals/0/Delivery%20of%20RespCare/RespiratoryCodingUpdateJUN2011.pdf

Using Statistical Process Control (SPC) within acute careWe all know that measurement is integral toimprovement methodology in healthcare but howdo we know whether or not we have actuallymade a difference and if the care being deliveredis getting better, staying the same or gettingworse each year? What we do not always takeinto account is the variation in the way thatservices are delivered – by individual departments,people and even different types of equipment. Allof these differences in the way things are donelead to differences in the way services aredelivered.

The main aim of using statistical process control(SPC) is to understand what is ‘different’ and whatis the ‘norm’ within a process. By using SPC, wecan then understand where the focus of workneeds to be concentrated in order to make adifference through service transformation work.We can also use SPC charts to determine if animprovement project is actually improving aprocess and also use them to ‘predict’ statisticallywhether a process is ‘capable’ of meeting a settarget.

The inherent strength of these charts is that theyprovide a visual representation of the performanceof a process by establishing data comparisonsagainst calculated limits (known as the ‘upper and‘lower’ control limits). These limits, which are afunction of the data, give an indication via signalsor chart interpretation rules as to whether theprocess exhibits either ‘common cause’ or ‘specialcause’ variation. The charts also visuallydemonstrate the inherent width or spread of thevariation being generated within any givenprocess.

In simple terms, improvement efforts would firstseek to remove special cause variation in order tocreate a stable and ‘in control’ process. This wouldbe followed by efforts to reduce the spread (orwidth) of the common cause variation. Processesthat are in control provide natural process limitsthat can be compared to specifications, outcomesor standards with corrective action being taken asrequired. Comparisons between specificationlimits and process performance enables thecalculation of system capability i.e. the ability ofthe process to meet customer and businessrequirements. Information of this type isfundamental in guiding process improvementstrategies.


SPC charts are therefore used:

• As a simple tool for analysing data – measurement for improvement.

• As a tool to help make better decisions.• As a tool for the ongoing monitoring

and control of a process.• To distinguish special cause from

common causes of variation as a guide to management action.

• To focuses attention on detecting and monitoring process variation over time.

• To help improve a process to perform consistently and predictably over time.

• To provide a common language for discussing process performance.

Natural (common cause) variation• Is inherent in the design of the process.• Results in a stable – IN CONTROL – process

because the variation is predictable.• Is due to random or chance causes of

variation.

Special cause variation• Is due to irregular or unnatural causes that are

not inherent in a process - extrinsic.• Results in an unstable – OUT OF CONTROL –

process because variation is not predictable.• Is due to non-random or assignable causes of

variation (i.e. a signal that the process has ‘changed’).

• Process improvement work will inadvertently introduce special cause variation for these reasons.

• For a more comprehensive overview and further resources, please refer to the NHS improvement website.

• www.improvement.nhs.uk/lung/ServiceImprovementTools/StatisticalProcessControl/tabid/96/Default.aspx

Within acute respiratory wards, there can be abroad variation in the severity of the disease inpatients who are admitted for COPD, so there isoften large variation in length of stay.

• Your trust may require you to split the data into the different parts of your pathway, from medical assessment wards, to respiratory specialist wards, or rehabilitation wards – there’srarely a one-size-fits all approach, so you may need to consider individual steps within your pathway.

• Consider looking at both patients with a primary diagnosis of COPD, and all respiratory diagnoses.

• Sometimes reviewing all admissions for all conditions within a single ward is useful, and can show change which may not be observed within the data that looks at a diagnosis across the whole hospital.

Figure 4: Example of an uncontrolled processwith two points above the upper control limit

Figure 5: Example of a controlled process


• Sometimes, different types of SPC chart are more appropriate. For example, when comparing monthly sampled data with high variation, such as length of stay for COPD, an X-Bar S chart (see page 14) may be appropriate, so that you review both the variation in the process each month, to the change to the mean.You may need support from an analyst or statistician to ensure you are using the correct technique for your data.

• For simpler processes such as time to receiving non-invasive ventilation (NIV), or time on an acute medical assessment ward, you can plot individual results on an SPC chart.

The chart below shows the results of our workwith the Eastbrook Ward in Worthing – theydecreased their average length of stay by one daythrough a number of small improvements to careand bed management. They also increased controlover the variation, resulting in a more predictablemean length of stay. This allowed for morerespiratory patients to stay on the ward in thefollowing year, increasing the number of COPDpatients able to be seen by a specialist.


Figure 6: SPC chart showing reduced variation in length of stay in an acute trust

The chart below shows an example of the XBar-Schart. This ward appears to have a fairly wellcontrolled mean length of stay, however theexcessive variation in the sample standarddeviation, shown as the uncontrolled process inthe second chart, indicated that there is aninherent variability in the process we aremeasuring, and suggests that it may be anuncontrolled process.


Figure 7: X bar - S chart of length of spell nights - Sort by discharge


The example below shows the number of daystaken for patients to arrive at the respiratory wardfrom their arrival at hospital. Typically, patientsarrived quickly, however some patients wereadmitted to other wards. You would want toreview these outliers.

Figure 8: Days from admission to respiratory ward (patients who attended ward)

Patient number (by admission rate)


Home oxygen is an area of the NHS that has awealth of data available, including invoice data,supplier concordance reports, and local caseloaddata. Data is provided as large spread sheets, isavailable regularly, and is provided to thecommissioners.

However, often Home Oxygen Service Assessmentand Reviews (HOS-AR) services lack usefulinformation to help them inform their servicedelivery. The huge spread sheets can be difficultfor a non-expert to use and interpret. There is somuch data that it is difficult to identify an area tofocus on. There are no key metrics to driveimprovement work. And often data doesn’talways get to the HOS-AR teams.

The importance of data for HOS-AR• There’s huge importance in using data to drive

improvement. While sites often thought that they understood their services well, the data often identified hidden issues, and enabled the sites to provide evidence of improvement to themselves and their commissioners

• Choose a few, focused metrics to drive improvement.

• Be pragmatic – it’s not easy to get perfect data, and often simple data is more useful

• Present the data in a simple way that makes the progress and goals clear. We found a dashboard was a helpful tool.

• Data is an essential part of HOS-AR – without it, we do not know our patients

Project learning - Derby HOS-AR teamThe team had developed a trainingprogramme for GPs, based on long termconcerns over inappropriate prescribing andhad been delivering this for over a year.

The data on who commenced oxygen toldus that the proportion of GPcommencements had decreased, andaccounted for under 10% of the initiatedhome oxygen, indicating that the schemehad been successful.

However, the data identified that 30-40%of patients were having oxygen initiated byhospital clinicians. Although the team hadthis data, they had not observed that theinitial problem had been successfullyresolved and that the opportunity for furtherimprovement of the service now lay inaddressing hospital prescribing.

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Key learning from our service improvement projects• HOS-AR has the potential to save money

alongside improving quality.• Use concordance data, but not in

isolation. We found that looking at the waste through using the concordance data was an excellent start, but combining this alongside looking at quality of prescribing enabled us to identify many areas for improvement.

• Who prescribes oxygen is a good process measure. In some areas with lowspend and well managed oxygen use, we found that over 90% of commencements had been initiated by aspecialist from their HOS-AR team.

• Review how many patients are supplied oxygen outside of guidance, where it may not be clinically appropriate.

• Review how HOS AR teams use their time – often surprising results were discovered in inefficient administrative processes, and time managing oxygen supplier relations.


Figure 9: HOS-AR dashboard

Example service improvement measures• Who completes the HOOF?• How many patients have potentially clinically

inappropriate supply, for example?• Over four hours of SBOT• Under eight hours of LTOT• Over or underuse of prescribed oxygen

• How much is spent on oxygen supply per month?

• How many patients receive oxygen each month?• What is the service activity – e.g. How many

commencements and removals?


Showing spread of good practiceThe respiratory atlas of variation provides maps ofcomparative oxygen spend across England.

Source: www.rightcare.nhs.uk/index.php/atlas/respiratorydisease

Figure 10: NHS Atlas of Variation Map


We have mapped the spread of services across each SHA.

Metrics for commissionersThe service specification in the Home OxygenAssessment and Review Commissioning Toolkitsuggests these metrics for commissioners.• The percentage of eligible people booked for

their HOS assessment who attend their appointment• puts onus on team to spread the gospel with

local clinicians and patients• The percentage of people prescribed oxygen

therapy who have a follow up home visit within four weeks• measure of the value-added by the HOS-AR team who can do environmental risk assessment

• The percentage of people on long-term oxygen therapy who have had a review in the last 9 months• another value-added measure – team can

ensure therapy still effective and matches patient’s potential changed condition

• The number of inappropriate oxygen prescriptions identified on assessment• will change over team lifecycle, initially high

but should reduce as HOS-AR established locally.

Figure 11: HOS-AR Coverage: West Midlands


Asthma is a respiratory condition that affectsapproximately three million people in the UK.Recorded prevalence is around 5.9% butestimates suggest the true figure could be nearer10%, one of the highest in the world. The cost to the NHS is put at around £1 billion with themajority of the spending on respiratorymedications and about £61 million on emergency admissions.

There is a 3.2-fold variation in the rate ofemergency admissions to hospital across England.Some of this can be explained by differences inthe local population, but much is due todifferences in the quality of asthma care.

An emergency hospital attendanceor admission represents a seriousloss of control of a person’sasthma. Admissions are sometimesnecessary… but it has beenestimated that three-quarters ofadmissions are preventable.”

NHS Atlas of Variation for people with respiratory disease.

NHS Improvement worked in partnership with anumber of sites over a 12 month period toimprove the Asthma pathway and reducevariation in standards of care. The projectsfocused on four key areas of work:

1. Diagnosis and medicines optimisation2. Chronic disease management3. Transforming acute care4. Integrated pathways.

We found that having a systematic approach toreviewing your data was an essential part of theimprovement process. Our projects reviewed thedata available in their areas to identifyimprovement priorities, create clear baselines andtargets for improvement, and through continuedmeasurement over a period of 12 months,achieved reductions in A&E attendance, reducedreadmissions, and improved quality of care.

A systematic approach to reviewing asthma data• Benchmark your service with others locally and

nationally.• Identify priorities for change, and collect relevant

baseline data. • Continuously monitor progress to evaluate the

intervention – this will help you to know if you are making progress towards your goal.

• Consider auditing patients case notes to gain understanding of the target cohort – data may indicate where your issues are, but a more detailed investigation can reveal the root cause issues

• Share data between clinical and managerial teams.

Examples from project sites


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Validate your patient registersThe ESyDoc project found that ‘clean’ registers(e.g. diagnosed patients with correct read coding)are essential, in order to be able to run searches toidentify cohorts of patients, for example in orderto stratify into degrees of risk, call the correctpatient for their annual review and to analyse data for QOF purposes.

There are tools available to help you understandyour data. These are available frompharmaceutical companies or from local dataanalysts. ESyDoc looked at the number of patientson asthma medication without an asthmadiagnosis, patients using large volumes ofmedication indicating poor asthma control, andpatients with frequent admissions orexacerbations, to risk stratify their patients fortargeted reviews.

Find the root causeEarly in 2010, the respiratory nursing team atGuy’s and St Thomas’ NHS Foundation Trustundertook a snapshot audit of asthmaattendances to A&E, and this revealed asurprisingly high 30 day re-attendance rate of justbelow 30% and this highlighted a problem whichthey wanted to improve upon.

Areas for improvement were identified by theteam through in depth diagnostic work to revealthe causes of re-attendance through:• examination of A&E data to establish the

target cohort• an audit of A&E casualty cards• telephone interview with reattenders to

understand behaviours and motivators.

Both qualitative and quantitative data was key tounderstanding the problem and informingsolutions.

Present data wellSandwell has the third highest admission ratewithin the UK and a high prevalence rate ofasthma of 7.5% with approximately 21,233people having been diagnosed. Despite this lownumbers of referrals for asthma were beingreceived to the Community Respiratory Servicefrom GPs and secondary care. The team decidedthe time was right to heighten their profile forasthma and emulate the good work they alreadydid in other respiratory diseases.

The analyst helped the team to mine the data onlocal admissions, to support targeting GPs forawareness and referral support, and produced adashboard to help the team manage referrals andcore measures, which helped the team keep trackof progress.


Figure 12: Respiratory dashboard


Measures and information for primary and secondary careThe first step in reviewing your service is tobenchmark. See where you are compared toothers by looking at data available nationally. • INHALE – This new national service provides a

PCT level summary of national indicators across admissions, readmissions, total spend, and across various outcome measures, and can help identify areas for improvement in your trust. www.inhale.nhs.uk

• The Right Care NHS atlas of variation in healthcare for people with respiratory disease provides a clear overview of the difference in outcome, and how your area compares to others. www.rightcare.nhs.uk

• Analyse local data and understand the variation – within your trust or CCG there may be variation in performance metrics and outcomes at each practice, and looking at local data, such as that in the APHO practice profiles, can be a good start to view variation. www.apho.org.uk/pracprof

Monitoring change in primary careGuidelines for Asthma care, such as the 2011 BTS/ SIGN guidance (British Thoracic Society &Scottish Intercollegiate Guidelines Network), canbe monitored in primary care by looking in detailat your patient records. Our project sitesimplemented measures to identify and improvequality of care:

• Proportion of patients diagnosed using spirometry

• Proportion of patients with a self-management plan

• Proportion of patients with good inhaler technique

• Number of patients on practice caseload receiving asthma medication without asthma diagnosis

• Proportion of patients receiving asthma education.

Commercial tools are available that allow you toquery primary care databases to answer questions,and some pharmaceutical companies supportpractices in using these tools. Also, most generalpractice systems include reporting functionalitythat will allow you to create your own reports onthese measures.

Data on hospital activity is easily accessible forprimary care, particularly for numbers and rates ofadmission and A&E attendance. These activitymeasures are available to commissioners, or canbe accessed directly from publicly accessiblewebsites such as NHS comparators, to give apicture of the variation in activity in practiceswithin your area. This enabled our projects tofocus attention on practices with the greatestrates of secondary care activity, but also thegreatest number of patients, so to maximise theimpact of their improvement work.

Measure change in secondary careIn order to understand the reasons behind apatient’s admission or attendance, often it isvaluable to audit a sample of patient records.While quantitative data can be useful tounderstand activity, the qualitative data providedby an audit of a sample of records can also beuseful.

National audits, such as those run by the BritishThoracic Society, can provide a comprehensivereview of your adherence to national standards,and provide benchmarking data to show howyour hospital compares to your peers.


Care bundles can be a useful tool to ensure thatthe basics of good care are delivered every time. A care bundle is a simple check list thataccompanies the patient notes and can easily becollected and monitored to ensure good care isdelivered. For asthma, this could include timelyassessment, checking inhaler technique, deliveryof patient education, and follow-up with patientsand GPs. The measures included are similar tothose in national audits, however the continuousmeasurement approach helps you to monitor andmaintain the quality of care.

Comprehensive data on admissions to hospital iscollected in your hospital’s PAS (Patient AdmissionSystem) and you can access the informationthrough performance analysts and managerswithin your trust. You may wish to look at thelength of stay, readmission rates, different wardsattended, time to reach specialist wards, andproportion of patients able to access a respiratoryspecialist.

Top tips for improvement with data• Start simple, and use readily available national

data sources. The data provided by INHALE, the Right Care NHS atlas of variation in healthcare, and through practice profiles, is a great way to build a picture of the care in your area, and often simple data is good enough to start improvement work.

• Get to know your trust analysts, performance managers and coders, as these people will be able to access and show you how best to use the data to answer your questions.

• When presenting data, make sure it is presentedin a format that your audience understands, anddon’t try to include every data item you have: having too many measures can be very confusing.

• Use Statistical Process Control (SPC) charts. SPC is a technique which plots either averages or individual results over time, alongside control limits, that demonstrate when a process is controlled and predictable, and which results areoutside these predicted limits. This helps you to identify and understand the variation in your system, and instantly identify unusual cases.

• Use demand and capacity. Sites have used demand and capacity effectively to look at how their peaks of demand vary from their supply of capacity. This is useful in acute settings, through matching the time when they aim to discharge patients to the peak times when patients are admitted, or in primary care, where you can review how community team time is used.

• Our primary care data guide for COPD provides useful links to how to investigate your primary care systems, suggests helpful data and coding tools, and shows the benefits of accurate data.

• The how to use data for COPD in secondary careprovides a useful of the variation in acute COPD care and introduces how to use SPC, and understand your acute pathway data.


Hospital site

Guys and St ThomasNHS Foundation Trust

Mid YorkshireHospital NHS Trust

University HospitalsNorth StaffordshireNHS Trust

Sandwell

Durham Dales

ESyDoc

Data collected

Snapshot audit of asthmaattendances to A&E

Tracked readmissions withinone month and conducted anotes review

A College of EmergencyMedicine CEM 2009/10asthma audit.Data on attendees andreattenders and admissions.Patient focus groupsAudit of casualty cards

Local data on admissions,process mapping of referrals –all presented into adashboard.Review of case notes.

Identified patients whomissed annual review, or wereover-using reliever inhalers.

Practice registers weresearched to identify patientswho had received asthmamedication without anyrespiratory diagnosis, or witha need for a review from anasthma specialist nurse.

Aim

To reduce asthmareattendances at A&Ewithin 28 days by 20%.

Reduce readmissions within28 days by 20%.

Improve standards of carefor patients presenting toemergency departmentwith an acute exacerbation.

Increase number of asthmareferrals into the service by50%.80% of patients on asthmaregisters were managed inaccordance with theBTS/SIGN guidelines.

Educate pharmacists,improve practice andpharmacist relations,improve patient outcomesand ensure qualityprescribing.

Increase the recordedprevalence of Asthma, Introduce risk stratification, Optimise medicines use

Outcomes

Reattendances at A&E fell by 45%.

Introduction of care bundle 60% reduction in readmissionsImproved patient coding of data.

Asthma care pathway.Asthma data base of all patientsattending A&E.Training programme.

Reduction in admissions by 21%.Reduction in A&E attendances by 29%.Increased referrals to nurse specialists by 75%.Increase in self-management plans21%.Increase in asthma education by 16%Increase review of inhaler technique by 8.2%

174 Medicine use reviews completed• 60 patients were recorded as

non-compliant and pharmacist interventions were delivered.

• Patient education to 32% of patients.• Device check and advice - 32%

of patients.• 14% of patients were referred

back to GP.

154 new patients were diagnosed with asthma.454 patients had a self-managementplan.58 patients referred for smokingcessation.Improvement in adherence to national guidelines.

NHS Improvement3rd Floor | St John’s House | East Street | Leicester | LE1 6NB

Telephone: 0116 222 5184 | Fax: 0116 222 5101

www.improvement.nhs.uk

NHS ImprovementNHS Improvement’s strength and expertise lies in practical service improvement. It has over adecade of experience in clinical patient pathway redesign in cancer, diagnostics, heart, lungand stroke and demonstrates some of the most leading edge improvement work in Englandwhich supports improved patient experience and outcomes.

Working closely with the Department of Health, trusts, clinical networks, other health sector

partners, professional bodies and charities, over the past year it has tested, implemented,

sustained and spread quantifiable improvements with over 250 sites across the country as

well as providing an improvement tool to over 2,000 GP practices.

Delivering tomorrow’simprovement agenda for the NHS

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