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West Midlands Commissioning Support Unit Department of Public Health, Epidemiology and Biostatistics School of Health and Population Sciences

West Midlands Key Health Data 2010-11

Editor : Dr. Jammi N Rao FRCP, FFPH

Chapter contributions from: West Midlands Cancer Intelligence Unit Health Protection Agency West Midlands West Midlands Public Health Observatory West Midlands QI NHS Dudley Birmingham PCTs and Birmingham Public Health NHS West Midlands


Foreword Data, information and intelligence about the health of the population – these are indispensable tools for rational decisions in health service planning and management. Public health information specialists make a tremendous contribution in turning routinely collected data into useful information and usable intelligence. Often, the analysis raises new questions that spur further effort to discover the answers. The intelligence that skilled analysis generates is vital also for monitoring progress in health improvement and inequalities reduction. Annual publication of the Key Health Data series has continued for just over a decade. It has evolved over the years, changing with technology, working with new collaborators, and keeping up with re-organisations. This year’s Key Health Data comes amidst yet another reorganisation of the NHS. But the need for, and the value of, good health intelligence remains as necessary as ever. Some of the chapters reflect these changes and signal the way in which public health information needs to adapt if we are to influence the health service of the future. Quality in general practice, providing information on cancers to future commissioners of services, changes in demography due to migration, growth in the use of antipsychotics, the distribution of hot food takeaways – these are some of the chapters that feature in this collection of contributions. As in previous years, Key Health Data is what its contributors make it. Organisational change has resulted in some of our regular authors withdrawing from the task for this edition. Nevertheless, we have here 12 chapters that serve as a flavour of what public health intelligence professionals can produce. We are reminded that high quality intelligence comes from asking good questions, the application of rigour to analysis, as well as the interpreting and reporting of results by people who understand context and subject. With the availability of fast computers it is easy to be beguiled into thinking that it can all be done remotely by a few boffins in an ivory tower. But health intelligence is ultimately a human endeavour and it takes skilled, thinking humans to do it. In these times of cutbacks, we have decided not to spend resources on printed copies. So I am pleased to commend this electronic – only edition of Key Health Data, which can be downloaded from our website.

Dr Edwina Affie Director, West Midlands Commissioning Support Unit Dept of Public Health, Epidemiology & Biostatistics School of Health and Population Sciences College of Medical and Dental Sciences Public Health Building, University of Birmingham Edgbaston, Birmingham B15 2TT Website: http://www.haps2.bham.ac.uk/wmcsu/


Contents

Chapter A new health geography

1

Epidemiology of migration in the West Midlands

5

Providing cancer information for commissioners

25

Measuring quality in general practice

33

Bowel cancer screening in the Black Country

41

The ten most common cancers in the West Midlands

56

Prevalence of coronary heart disease in Birmingham and Solihull 65 Abortions trends in the last decade

75

HIV and AIDS in the West Midlands

81

Spatial planning decisions and obesity

102

Antipsychotic prescribing 2007-11

110

Smoking cessation in West Midlands

119


Contributors Victor Aiyedun, Specialist registrar in Public Health Medicine Health protection Agency West Midlands 5 St Philips Place, Birmingham B3 2PW Victor.aiyedun@hpa.org.uk Yasmin Akram Public Health Registrar (ST1) Birmingham East and North PCT, Birmingham, B7 4AA y.akram@doctors.org.uk Andy Baker, Public health Scientist Birmingham Public Health, CIBA Suite 203 146 Hagley Road, Edgbaston Birmingham B16 9NX Andrew.baker6@nhs.net Helen Bagnall Epidemiological Scientist Health Protection Agency – West Midlands 5 St Philips Place, Birmingham B3 2PW

HIV infection and AIDS in the West Midlands

The epidemiology of migration in the West Midlands

Spatial planning and obesity

HIV infection and AIDS in the West Midlands

Helen.Bagnall@hpa.org.uk

John Broggio Cancer Registration Information Manager Cancer Intelligence Unit Public Health Building, University of Birmingham B15 2TT John.broggio@wmciu.nhs.uk Felix Burden Clinical Director Heart of Birmingham Teaching Primary Care Trust Bartholomew House, 142 Hagley Road Birmingham, B16 9PA a.burden@nhs.net Diane Edwards GIS Specialist Cancer Information West Midlands Cancer Intelligence Unit Public Health Building University of Birmingham B15 2TT Diane.edwards@wmciu.nhs.uk Obaghe Edeghere LocumConsultant Regional Epidemiologist Health Protection Agency – West Midlands 5 St Philips Place, Birmingham B3 2PW Obaghe.Edeghere@hpa.org.uk

Providing cancer statistics for commissioners

Prevalence of Coronary Heart Disease in Birmingham and Solihull

A new health geography Providing cancer statistics for commissioners

HIV Infection and AIDS in the West Midlands


Tim Evans Cancer Registration Information Manager West Midlands Cancer Intelligence Unit Public Health Building University of Birmingham B15 2TT tim.evans@wmciu.nhs.uk George Fowajuh Public Health Information Specialist West Midlands Public Health Observatory Vincent Drive, Edgbaston Birmingham B15 2SQ gfowajuh@nhs.net Suzanne Holt, Public Health intelligence Analyst (Primary Care Commissioning), Dudley Public Health, St Johns House, Union Street, Dudley DY2 8PP suzanne.holt@dudley.nhs.uk Sadia Janjua Research Reviewer and Analyst West Midlands Commissioning Support Unit Public Health Building University of Birmingham B15 2TT sjanjua@bham.ac.uk John Kemm Formerly Director West Midlands Public Health Observatory Vincent Drive, Edgbaston Birmingham B15 2SQ jkpublichealth@btinternet.com Amanda Lambert Head of Healthcare Information Birmingham Public Health Barthlomew House 142 Hagley Road, Birmingham B16 9PA a.lambert@nhs.net Gill Lawrence Director West Midlands Cancer Intelligence Unit Public Health Building University of Birmingham B15 2TT Gill.lawrence@wmciu.nhs.uk Hashum Mahmood Public Health Epidemiologist NHS Birmingham East and North Birmingham Hashum.mahmood@nhs.net

Most Common Cancers in the West Midlands

The epidemiology of migration in the West Midlands

Bowel cancer screening in the Black Country

Abortion trends in the last decade

The epidemiology of migration in the West Midlands

Prevalence of Coronary Heart Disease in Birmingham and Solihull

Providing cancer statistics for commissioners

Smoking cessation in the West Midlands


Kate Martin, Information Scientist (HIV and STI Surveillance), Regional Epidemiology Unit Health Protection Agency West Midlands Birmingham B3 2PW katherine.martin@hpa.org.uk Angelique Mavrodaris Division of Mental Health and Wellbeing Warwick Medical School, Gibbet Hill Campus University of Warwick CV4 7AL A.Mavrodaris@warwick.ac.uk Angela Moss, Senior Public Health Intelligence Specialist Dudley Public Health, St Johns House, Union Street, Dudley DY2 8PP angela.moss@dudley.nhs.uk Jammi N Rao Consultant in Public Health Medicine West Midlands Commissioning Support Unit, University of Birmingham, B15 2TT

HIV infection and AIDS in the West Midlands

Trends in the use of anti-psychotic drugs

Bowel cancer screening in the Black Country

Editor, Key Health Data Abortions trends in the last decade

Jammi.rao@gorwayglobal.co.uk

Yasmin Rehman Epidemiological Scientist

HIV Infection and AIDS in the West Mildands

Regional Epidemiology Unit Health Protection Agency West Midlands Birmingham B3 2PW Yasmin.rehman@hpa.org.uk

Richard Seal MSc MRPharmS Programme Consultant in Medicines Management, NHS West Midlands St Chads Court, 213 Hagley Road Birmingham B16 9RG richard.seal@westmidlands.nhs.uk Antony Stewart Professor in Public Health Staffordshire University Stoke-on-Trent ST4 2DF Antony.stewart@staffs.ac.uk Kyle Stott, Health Improvement Specialist Birmingham Public Health CIBA Suite 203 146 Hagley Road, Edgbaston Birmingham B16 9NX Kyle.stott@bhwp.nhs.uk

Trends in use of anti-psychotic drugs

Smoking cessation in the West Midlands

Spatial planning and obesity


Catherine Tomaney Health Improvement Specialist NHS Birmingham East and North Waterlinks House, 2nd Floor Richard St, Aston Birmingham B7 4AA Catherine.Tomaney@benpct.nhs.uk Sally Vernon Deputy Director West Midlands Cancer Intelligence Unit Public Health Building, University of Birmingham B15 2TT Sally.vernon@wmciu.nhs.uk Richard Wilson Head of West Midlands QI NHS West Midlands, St Chad’s Court 213 Hagley Road Birmingham B16 9RG 0121213 1987 Richard.Wilson@westmidlands.nhs.uk

Smoking cessation in the West Midlands

Providing cancer statistics for commissioners

Measuring quality in general practice


1

1.

A New Health Geography

Introduction

This chapter provides an overview of the geographies that will become important for the provision of public health information as a result of the Health & Social Care Bill laid before Parliament in 2011. It is expected that Primary Care Trusts (PCTs) and Strategic Health Authorities (SHAs) will cease to exist in April 2013 and a range of new organisations take over these and other public health functions. The new organisations will include a new executive agency Public Health England, a new NHS Commissioning Board and associated local Clinical Commissioning Groups. Notice of a number of other geographical changes and new products are also signposted, not least of which are the anticipated outputs of the 2011 Census.

2.

Transition arrangements in Health

West Midlands Strategic Health Authority Since October 2011 the West Midlands SHA has been operating as part of a central „clusterâ€&#x; of SHAs with adjoining East Midlands and East Anglia to be known as NHS Midlands and East. The SHA clusters are providing strategic direction as SHA governance roles are handed over to the new NHS Commissioning Board, their public health roles to Public Health England and their quality assurance roles to NHS Quality all with an effective date of 1st April 2013. Primary Care Trusts The merger of three Birmingham PCTs reported in 2009/10 did not take place before the calling of the General Election in 2010. However the Birmingham PCTs are working together in a PCT cluster (see KHD 2010 for details) until the transfer of public health and commissioning roles are confirmed in April 2013. Solihull Care Trust reverted to PCT status from 1st April 2011 with a coding change from TAM to 5PW but no boundary change. All PCTs will be dissolved in March 2013 and their public health functions transferred to top tier local authorities (TTLAs) whose Health and Wellbeing Boards will become statutorily responsible for setting priorities for health across their areas from 1st April 2013. Early progress has been made with this transfer of functions to TTLAs in some areas of West Midlands. PCT commissioning responsibilities should transfer to the shadow Clinical Commissioning Groups (CCGs) during 2012 in preparation for assuming statutory responsibility on 1st April 2013. They will be governed by a new national NHS Commissioning Board.

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Figure 1. Map of the west midlands showing the top tier local authorities

Public Health England Wider public health functions currently provided by the Public Health Observatories, Cancer Registries, Health Protection Agency, NHS Screening Programmes and National Drug Treatment Agencies will be provided by a new Executive Agency „Public Health England‟. The structure and geographical arrangements of this organisation have not yet been defined so cannot be included in this year‟s report. Clinical Commissioning Groups (formerly GP Consortia) Late in 2010 the Department of Health invited groups of GP practices to nominate themselves as Pathfinder GP Consortia to investigate new routes to commissioning primary and secondary health services. Pathfinder GP Consortia were approved in phases from December 2010 to July 2011 and now include 80% of GP practices and 86% population of the West Midlands. Following the publication of the Future Forum report in June 2011 the term „GP Consortia‟ was dropped and replaced by Clinical Commissioning Groups (CCGs) to reflect the inclusion of other health professionals working alongside GP‟s to commission NHS services. DH Guidance to CCGs requires that they define the geographical area for which they will commission health services and that these areas should respect administrative boundaries. Geographical definitions are only loosely described in CCG declarations to date.

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Section 2 of this chapter details some preliminary work carried out by West Midlands Cancer Intelligence Unit to consider how the cancer registry might provide cancer information and statistics for CCGs in the West Midlands.

3.

Other geographical changes

Local Government 2010 saw the abolition of the Regional Development Agencies (RDAs) and the Government Office for the Regions (GoRs) across England. Advantage West Midlands (AWM) and its West Midlands Regional Observatory (WMRO) began windup activities in October 2010 and their last vestiges will be wound up by 31st March 2012. Office for National Statistics (ONS) will continue to use the areas previously defined as GoRs in their statistical reporting. Parliamentary Constituencies In September 2011 the Boundary Commission for England began a process of consultation on parliamentary constituency boundary changes to secure a reduction in number of MPs in parliament from 533 to 502 before the next general election or 2015 whichever is the earlier. In West Midlands they propose a reduction in parliamentary constituencies from 59 to 54 with 10 boundaries unchanged. For details see: http://consultation.boundarycommissionforengland.independent.gov.uk/

4.

Office for National Statistics (ONS) geography and populations

National Postcode Lookup The Office for National Statistics (ONS) has produced a new postcode product the National Statistics Postcode Lookup (NSPL) in addition to its National Statistics Postcode Directory (NSPD) and the NHS Postcode Directory (NHSPD). Unlike the NSPD and NHSPD, the NSPL provides a postcode lookup which assigns a postcode to a census output area (COA) and builds higher geographical areas from whole COAs rather than assigning postcodes directly into higher areas. The NSPL method matches the way small area population estimates are prepared and provides a more accurate route to defining statistics such as age standardised rates. ONS Mid-year Population Estimates 2010 Mid-year population estimates for 2010 were published in two parts during 2011, national and Local Authority estimates at the end of May and Primary Care Trust and Super Output Areas at end of September. ONS have not published timetables for 2011 estimates because of the effect 2011 Census counts and boundary changes might have on the 2011 baseline. 2011 Census The 2011 Census took place on the 27thMarch 2011 with the aim to provide consistent, comparable population counts for the UK. ONS oversaw the delivery of 25.4 million census questionnaires to households in England and Wales. Active questionnaire tracking has been used for the first time and has made field operations more effective with 76% questionnaires returned within 10 days of census

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night. Stakeholder and community engagement together with a targeted marketing strategy has yielded dividends with early indications of a 94% response rate. Capture and coding of returns is on schedule and due to be complete by mid December. The first electronic data have been delivered from the processing centre to ONS for validation and quality checking. The first high level outputs for UK, England, Scotland, Wales and Northern Ireland and for local authorities for England & Wales are due to be reported in July 2012. Smaller area and cross tabulated data will follow throughout 2012 and 2013. There will be a common UK statistical disclosure control methodology for 2011 Census outputs. Census geographies will share a common boundary between England and Scotland and be available as „extent of the realm‟ and „mean high water mark‟ (coastline) files. Changes to output area boundaries will be minimal and limited to change in less than 5% of output and lower super output areas. Any changes to boundaries will be achieved by simple mergers and groupings rather than wholesale realignments. This strategy should allow more meaningful comparisons to be made between 2001 and 2011 results.

5.

Ordnance Survey OpenData and the Public Sector Mapping Agreement

Following the introduction of a public sector data portal in 2010 at www.data.gov.uk and the provision of Ordnance Survey (OS) OpenData a new „Public Sector Mapping Agreement‟ (PSMA) went live 1st April 2011.The PSMA provides OS datasets to any public sector organisation free at point of use. It is funded by central government and its management transferred from Department for Communities and Local Government to the Department for Business Innovation and Skills (BIS). The PSMA currently includes over 1700 organisations including many parish and town councils. This will be the first time all public sector organisations in England have access to the same OS products under one agreement which is licensed for 10 years. It will give much more opportunity to work together and share resources.

Diane Edwards GIS Specialist Cancer Information Author

West Midlands Cancer Intelligence Unit Public Health Building, University of Birmingham B15 2TT

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2 1.

The epidemiology of migration in the West Midlands

Introduction

Movement of people between countries is increasingly a feature of modern life and consequent changes in local populations can cause appreciable changes in the need for health and other services. Migrant groups will be characterised by cultural and religious beliefs and those providing them with services will need relevant cultural understanding and training. They may have a higher prevalence of particular disease conditions increasing the need for relevant services, thus information on migration is needed in order to establishing the level of local need and demand for a comprehensive migrant health service. The reality of migrant communities in the West Midlands is diverse, rich and complex. This chapter aims to describe the epidemiology of migrants in the West Midlands since understanding the characteristics of these migrant populations is key to informing priorities for commissioning and local Health and Wellbeing strategies.

2.

Definitions and terminology

This section defines the many terms used to describe aspects of migration Table 1. Migrant categories

Term

Meaning

International Migrant

A person who has changed their country of residence

Long Term International Migrant (LTIM)

A person who has changed their country of residence and intends to stay in the new country for more than 12 months. The term migrant is usually refers to LTIM.

Short Term Migrant

A person who has changed their country of residence and intends to stay for less than 12 months.

Refugee

A person who has left their previous country of residence in order to escape persecution or fear of persecution.

Asylum seeker

A refugee who has applied for asylum and permission to remain in a country. This will usually be granted if they are deemed to have a wellfounded fear of persecution in their country of origin

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Term

Meaning

Spousal migrant

A migrant who is coming to UK to join a spouse who is a UK citizen or a permanent resident. Dependent children of the marriage are also allowed to reside with the family in UK.

Irregular (illegal) immigrant

A person who is living in a country but has not been given leave to enter or remain or has stayed after their leave to remain has expired

Non UK national

A person who has a nationality of a country other than the UK and does not have dual UK nationality.

Ethnicity

Describes the ethnic group to which a person belongs and is no indication of nationality or immigrant status.

Country of birth

Simply describes the country in which a person was born and is not a reliable indication of nationality or migrant status. However, a high proportion of people born in some non UK countries are immigrants.

In this chapter the term „Migrant‟ used without qualification refers to Long Term International Migrants. The European Union consists of 27 countries. For many purposes migrants from EU countries are grouped into categories as shown in Table 2. Table 2. Various terms used to describe groups of countries

Group EU 15 Countries (joined before 2004)

Meaning Austria, Belgium, Finland, France, Denmark, Germany, Greece, Luxembourg, Ireland, Italy, Netherlands, Portugal, Spain, Sweden, UK Cyprus and Malta – joined in 2004 but are not included in A8.

A8 – Countries (joined in 2004) A2 – Countries (joined in 2007) Other European Economic Area countries

6

Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovak Republic, Slovenia. Bulgaria, Romania Iceland, Liechtenstein, Norway and Switzerland are not members of the EU but for most immigration purposes are treated as pre 2004 EU countries.

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A point to note is that although the term “region” is no longer recognised by the Government since much of the analysis cited in this chapter was done on the basis of former Government Office regions the term “region” has been retained when referring to that work.

3.

Data sources

Reliable local data for the migrant population are difficult to collect and interpret. However, using a variety of data sources much can be done to establish a feel for the number of migrants in an area and to some extent identify where there are gaps in services. The main data sources are GP registrations by local authority (Flag4), National Insurance number, Annual Population Survey, Data from Schools and Higher Education Institutions, Data on Asylum Seekers and the International Passenger and Long Term International Migrants surveys. Figure 1 illustrates the elements in the calculation of immigrant populations and flows. Figure 1. Immigrant populations and flows

Source: Migration Statistics 2008 Annual Report1

4.

The effect of migration on the West Midlands population

Figure 2 shows the components of population change in the West Midlands authorities for 2008-2009 expressed as a percentage of 2008 population. The net change varies from nearly 1% increase in Birmingham to a nearly 0.2% decrease in Stoke on Trent. Natural increase and decrease due to births and deaths accounts for much of the population change but in most local authorities net migration

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makes a contribution. At a UK level net population change is about 0.64% of which migration (international migration) accounts for 0.29% (45% of the change). Figure 2: Components of population change – West Midlands 2008-2009 – Birth, death and Migration (Internal and External) net change is shown as % of mid 2008 population.

Source: Office for National Statistics2‟3 Losses to the population –deaths, net outward international migration (moving from another country) and net outward internal migration (moving from one UK authority to another) are shown below line. Gains to the population –births, net inward international migration and net inward internal migration are shown above line. Net population change is shown as a bar.

5.

Long Term Migrant Survey

Table 3 shows estimated migration flow to each region. Due to methodological differences in data collection figures obtained from International Passenger Survey vary somewhat from Long Term International Migrants data.

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Table 3: Estimated number of long term migrants going to different regions in 2008 from LTIM and IPS Regions LTIM Numbers IPS Numbers North East 23000 20000 North West 45000 38000 Yorkshire & Humber 53000 44000 East Midlands 23000 22000 West Midlands 37000 33000 East 54000 51000 London 163000 145000 South East 84000 78000 South West 31000 29000 Source: Office for National Statistics4â€&#x;5

Figure 3 shows how the estimated numbers of immigrants to the West Midlands has risen over the years. It should be noted that prior to 2003, the data were recorded for calendar years and thereafter as financial years. Figure 3: Estimated number of immigrants and emigrants with West Midlands as destination 1991-2008

4

Source: Office for National Statistics ’6

Table 4 shows estimate of the numbers of migration inflow to and outflow from the West Midlands. In 2009 there was a net movement out to the pre 2004 EU countries and to the old commonwealth, and a net movement in from New Commonwealth countries and other countries.

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Table 4: Estimated number (in thousands) of immigrants from and emigrants to different countries for West Midlands 2009 European Union EU15 EU8 Immigrant Emigrant Balance

3 5 -2

3 1 +2

Commonwealth Old New 2 5 -3

10 2 +7

Other Foreign Countries 9 5 +4

Source: Office for National Statistics7

6.

Patient Register Data System (PRDS) – Flag 4 GP registrations

A person registering with a GP whose previous address is outside the UK is flagged (and a different flag is given to a returning migrant). Flag 4 data can, therefore, provide an indication of international migration to an area though it only counts those who registered with a GP. Figure 4: Number of Flag 4 registrations per 1000 residents in the West Midlands Local Authorities mid 2008-2009

Source: Office for National Statistics

Figure 4 shows the number of Flag 4 registrations per 1000 residents in the West Midland Local Authorities. The greatest numbers are in Birmingham and Coventry. There are very few in the Shire counties and Dudley

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Figure 5 shows the trends for Flag 4 registration in those local authorities with the largest numbers. Numbers of Flag 4 registration have risen in Coventry, Sandwell and Rugby but only risen slightly in Birmingham and Wolverhampton. Figure 5: Trends in Flag 4 per 1000 residents 2000/01 – 2008/09, selected local authorities

Source: Office for National Statistics8

7.

NINo registrations

Those intending to work coming from outside the UK must apply for a National Insurance Number (NINo). The number of new NINos granted to workers from outside UK is an indicator of migrant flow, however this will not identify their families nor those that do not register to work. The age of NINo registrants in the West Midlands is shown in table 5. It can be seen that the vast majority are young (18-34 years). Table 5: Percent of NINO registration in different age bands for the West Midlands 2009 Age Numbers (In 1000s)

<18

18-24

25-34

35-44

45-54

55+

1.8

40.6

37.2

12.6

5.8.

1.9

Source: Department for Work and Pensions (DWP)9 Figure 6 shows the number of NINo registrations for the West Midlands local authorities. Herefordshire has the most NINo registrations chiefly because it has high numbers of registrants under the Seasonal Agricultural Worker Scheme (SAWS). Wolverhampton, Birmingham, Sandwell and Coventry also have high numbers of NINo registrants.

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Figure 6. NINo registrations per 1000 residents 2009 by Local Authority

Source: Office for National Statistics10 Figure 7 shows trends in numbers of NINo registrants since 2004 for the local authorities with the highest numbers.

Figure 7. Trends in NINo registrations per 1000 residents for selected local authorities in the West Midlands

Source: Office for National Statistics10 .

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Figure 8: NINo Registrants by country of origin Key to country of origin

Americas

Australasia EU15

EU15 includes first15 member states & Cyprus, Malta, Switzerland, Norway & Iceland

Rest Asia & Middle East

Bangladesh

Other EU (A8) includes states which joined EU in 2004 except Poland

Poland Pakistan Pakistan

E Europe includes all other European states including Russia & Turkey Rest Asia and Middle East All Countries in Asia except India Pakistan & Bangladesh

Other EU (A8)

India

West Midlands aggregate figures shown opposite Africa

EU(A2)

E Europe

Birmingham

Coventry Americas

Australasia

Americas

Rest Asia & Middle East

Bangladesh

Australasia EU15

Pakistan

EU15

Poland

Poland

Rest Asia & Middle East

India

Bangladesh

Other EU (A8)

Other EU (A8) Pakistan Pakistan EU(A2)

Africa

Africa

EU(A2)

E Europe

E Europe

India

Herefordshire

Sandwell Americas Other EU15

Bangladesh Pakistan

Romania

Poland

Rest Asia & Middle East

Australasia EU15

Poland

India Other EU (A8)

Bulgaria Other EU (A8) E Europe

Africa EU(A2)

Source: Office for National Statistics

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8. Annual Population Survey and estimates by place of birth and nationality The Annual Population Survey asks people to describe their own nationality and their place of birth. Figure 9 shows the estimated percentage of resident population in the different local authorities who were born outside the UK. Figure 10 shows the estimated percentage who report being of some nationality other than British. Many of those born overseas have acquired UK nationality and so the numbers of nationals resident in an area are less than the numbers born in that country. The largest percentages in both categories are in Birmingham, Coventry, Sandwell and Wolverhampton.

Figure 9. Percentage of the West Midlands resident population born outside the UK 2009

Source: Office for National Statistics11

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Figure 10: Percentage of the West Midlands resident population of Non- British nationality 2009

Source: Office for National Statistics12

The trends in the percentage of resident population born outside the UK and reporting non-British nationality appear to be rising. 12 Tables 6 and 7 show the commonest five countries of birth and reported nationalities respectively for the West Midlands. Table 6: Estimated population resident in the West Midlands for five most common countries of birth January – December 2009 Country of Birth Estimate

95% CI

Pakistan

90,000

±13,000

India

86,000

±13,000

Poland

45,000

±9,000

Republic of Ireland

39,000

±9,000

Jamaica

22,000

±7,000

Source: Office for National Statistics13

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Table 7: Estimated population resident in the West Midlands for five most common nationalities January – December 2009

Nationality Estimate

95% CI

Poland

41,000

±9,000

India

39,000

±9,000

Pakistan

38,000

±9,000

Republic of Ireland

29,000

±7,000

Zimbabwe

13,000

±5,000

Source: Office for National Statistics13 There is clearly a difference between country of birth and individuals who have maintained their own nationality. This raises the question whether certain types of migration such as spousal migrants, family reunion etc. are likely to lead individuals to take on UK Nationality. In the case of the Polish community, for example, the gap between country of birth and nationality is lower possibly due to the fact that they have come to the UK much more recently than is true for other populations. Those with local knowledge believe that there is a large Somali population in the West Midlands and express surprise that this population group does not appear in the top five. It may be that the Annual Population Survey has under recorded this population.

9.

ONS population estimates by ethnic group

Accurate information on ethnic group is only available in census years but ONS has produced experimental estimates for later years based on census and other data. Figure 14 shows the ONS estimates for West Midland Authorities in 2007. Birmingham has the highest percentage of non-white ethnic groups as do other metropolitan areas. Asians make up the largest portion of the non-white groups and Pakistanis are the largest ethnic group among these.

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Figure 11. Estimated percentage of non-white ethnic groups in populations broken down by broad ethnic group West Midland Local authorities 2007

Source: Office for National Statistics14

10.

Place of birth of mothers of children born in the West Midlands

Table 8 shows the place of birth of mothers of babies born in the West Midlands in 2009. The figures on mothers‟ place of birth in 2009 have been extracted from ONS birth records held by the West Midlands Public Health Observatory (WMPHO). One fifth of babies are born to mothers whose place of birth was outside the UK. Table 8: Place of birth of mothers of children born in the West Midlands in 2009 Percent Mother’s place of birth Mother’s place of birth Percent Old European Union (Countries which joined before 2004 plus Norway & UK 77.8 Switzerland) 1.3 Pakistan 5.3 Middle East 1.1 Other African (Include North and sub Saharan Africa) 3.0 Other EU (A8 & A2) 1 Poland 2.3 Somali 0.8 Others India 2.3 0.8 Caribbean Other Asian 1.9 0.6 Rest of Europe Bangladesh 1.4 0.4 Source: ONS Births Registrations 2009, analysed by WMPHO

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Figure 12 shows the percentage of mothers born outside the UK giving birth in 2009 in the different West Midlandsâ&#x20AC;&#x; local authorities. Figure 12. Percentage of mothers born outside UK giving birth in West Midlands in 2009

Source: ONS Births Registrations 2009, analysed by WMPHO

The trends in the percentage of births in the West Midlands to mothers born outside the UK show a steady rise in all selected local authorities with Birmingham, Coventry, Sandwell and Wolverhampton having a higher percentage than that of the West Midlandsâ&#x20AC;&#x; region.13 Figure 13 shows the trends in the percentage of births in the West Midlands to mothers from different countries. It can be seen that the percentage of births to mothers born in Pakistan, India and Bangladesh has remained fairly steady but the percentage of births to mothers born in the A2 and A8 member countries of the EU and to mothers born in Somalia has risen over the past ten years.

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Figure 13. Percentage of births in the West Midlands to mothers from different countries

Source: ONS Births Registrations 2001 to 2009, analysed by WMPHO

11.

Ethnicity of school children

Figure 14 shows the percentage of children in primary and secondary schools whose first language is believed not to be English. A high proportion of these children will be migrants or have parents who are migrants. It can be seen that a high proportion (15-40% of primary school children and 10-35% of secondary school children) in the metropolitan local authorities fall into this category Figure 14: Percentage of pupils whose first language is known or believed to be other than English, 2009

Source: Department for Children, Schools and Families15 Table 9 shows the different ethnic groups in primary and secondary schools in the West Midlands. Pakistani and Indian ethnic groups account for nearly half of the quarter of children who are not

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classified as White British. It is likely though that most of the children who are not White British will have been born in this country and are not migrants. Table 9: Ethnic grouping of children in the West Midlandsâ&#x20AC;&#x2122; primary and secondary schools January 2009 Primary Secondary School School White British 71.65 75.69 Other White 2.41 2.39 Mixed White And Black 2.16 1.99 White And Asian 0.99 0.73 Mixed Any Other 1.26 0.97 Asian Indian 4.28 4.45 Pakistani 8.38 5.78 Bangladeshi 1.84 1.30 Asian Any Other 0.98 0.82 Black Black Caribbean 1.81 1.81 Black African 1.88 1.36 Black Any Other 0.46 0.37 Other Chinese & Other(including unclassified) 1.91 2.33 Source: Department for Children, Schools and Families15

12.

Asylum Seekers

Asylum seekers may be supported with subsistence only or with accommodation. Table 10 shows that West Midlands is the region which in 2009 supported the most asylum seekers with accommodation after the North West. The numbers supported with subsistence only are relatively low. Table 11 shows the distribution of supported asylum seekers within the West Midlands. Nearly half of those supported with accommodation are in Birmingham. Figure 15 shows the countries of origin of supported asylum seekers in the West Midlands December 2009. The largest numbers were from Zimbabwe, Pakistan, Afghanistan, China, Iraq and Iran. This distribution is similar to the total for the UK. Asylum seekers whose cases have been refused leave to remain, who are destitute, but temporarily unable to leave the UK have not been included in tables 10 and 11.

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Table 10. Supported Asylum Seekers by Region â&#x20AC;&#x201C; December 2009 Region Subsistence only Accommodation North East 35 2185 North West 265 6485 Yorks & Humber 175 3540 East Midlands 165 980 West Midlands 260 3590 East of England 200 270 London 3165 1265 South East 295 350 South West 40 685 Wales 20 1760 Scotland 50 2470 N. Ireland 15 265 UK 4670 23,840 Source: Home Office16

Table 11. Supported Asylum Seekers in West Midlands December 2009 Local Authority Subsistence only Accommodation Birmingham 105 1,345 Coventry 35 510 Dudley 335 Sandwell 25 245 Stoke-on-Trent 20 515 Walsall 15 95 Wolverhampton 25 545 Other 35 West Midlands 260 3,590 Source: Home Office

16

Figure 15. Supported Asylum Seekers (including dependents) in the West Midlands December 2009.

Other

Afghanistan China

Other Africa Pakistan

Sri Lanka Other Asia

Zimbabwe Iran Iraq

Nigeria

Eritrea

Other Middle East

Somalia

Source: Home Office17

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13.

Irregular immigrants

It has been estimated that in 2007 the number of irregular migrants in the UK was 618,000 (range 417-867,000), however local breakdowns are unavailable18.

14.

Conclusion

This chapter shows how there can be more „intelligent‟ use of existing data sources to track migrants‟ needs of health and social care. Over the past 5 to 10 years most indicators of migrant numbers have been rising. The local authorities with the most immigrants by most indicators are Birmingham, Coventry, Sandwell and Wolverhampton. Herefordshire has a large number of registrants under the Seasonal Agricultural Workers Scheme. The largest numbers of immigrants come from Poland, Pakistan and India but the picture varies considerably between the different local authorities. Every agency will see a different part of the picture and none will see the whole picture. It is therefore essential that the different agencies work together to share the information they have acquired on migrant communities

15.

Recommendations 

Partnerships are needed across central and local government, statutory service providers and voluntary, community and migrant organisations in local areas. They need to effectively coordinate and provide advice, support and services for migrants and ensure that migration issues are a key part of local planning and priorities.

The understanding of the health needs of migrants in the West Midlands is improving but more analysis and research is required to improve care and preventive support for this group.

The proposed new Public Health Service offers an opportunity to really get to grips with the migration agenda and address underlying health determinants and tackle inequality and disadvantage.

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16.

References

1

Office for national Statistics, Migration Statistics 2008 Annual Report page 6 [Online] 2011 [cited 2011 Oct]. Available from URL: http://www.statistics.gov.uk/downloads/theme_population/Migration-Statistics-2008-AnnualReport.pdf 2

Office for National Statistics. Mid-year 2009 population estimates, Table 10 Local authority [Online] 2011 [cited 2011 Oct].Available from URL: http://www.statistics.gov.uk/statbase/Product.asp?vlnk=15106 3

Office for National Statistics. Local area migration indicators suite (Worksheet Migration data (PEU)) [Online] 2011 [cited 2011 Oct]. Available from URL: http://www.statistics.gov.uk/statbase/Product.asp?vlnk=15239 Office for national Statistics, Long Term International Migration (LTIM) â&#x20AC;&#x201C; Tables 1991-latest, LTIM calendar year, Table 2.06 Area of destination or origin within UK [Online] 2010 [cited 2010 Dec]. Available from URL:http://www.statistics.gov.uk/statbase/Product.asp?vlnk=15053 4

5

Office for national Statistics, Long-term international migration from International Passenger Survey (IPS) tables: 1991-latest, 3 series, IPS calendar years, Table 3.02 [Online] 2011 [cited 2011 Oct]. Available from URL:http://www.statistics.gov.uk/statbase/Product.asp?vlnk=15054 6

Office for national Statistics, Local area migration indicators suite (Worksheet Migration data (PEU)) [Online2011 [cited 2011 Oct].Available from URL: http://www.statistics.gov.uk/statbase/Product.asp?vlnk=15239 Office for national Statistics, Long Term International Migration(LTIM) â&#x20AC;&#x201C; Tables 1991-latest, LTIM calendar year, Table 3.02 Country of last or next residence by UK Area of destination [Online] 2011 [cited 2011 Oct]. Available from URL:http://www.statistics.gov.uk/statbase/Product.asp?vlnk=15053 7

8

Office for national Statistics, Local area migration indicators suite, Worksheet Migration Flag4 (ONS) [Online] 2011 [cited 2011 Oct]. Available from URL: http://www.statistics.gov.uk/statbase/Product.asp?vlnk=15239 9

Department for Work and Pensions, DWP Tabulation tool (adult overseas nationals entering UK by year of registration), [Online] 2011 [cited 2011 Oct].Available from URL: http://83.244.183.180/mgw/live/tabtool.html 10

Office for national Statistics, Local area migration indicators suite, Worksheet NINo data (DWP) [Online] 2011 [cited 2011 Oct].Available from URL: http://www.statistics.gov.uk/statbase/Product.asp?vlnk=15239 11

Office for national Statistics, Local area migration indicators suite (Worksheet Migration Non-UK (APS)) [Online] 2010 2011 [cited 2011 Oct].Available from URL: http://www.statistics.gov.uk/statbase/Product.asp?vlnk=15239 12

Office for national Statistics, Local area migration indicators suite (Worksheet Migration NonBritish (APS)) [Online] 2011 [cited 2011 Oct].Available from URL: http://www.statistics.gov.uk/statbase/Product.asp?vlnk=15239 13

Office for national Statistics, Population by country of birth and nationality April2009-Mar2010 Tables 1.4 and 2.4. [Online] 2011 [cited 2011 Oct]. Available from URL: http://www.statistics.gov.uk/statbase/Product.asp?vlnk=15147

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14

Office for national Statistics, ONS population estimated by ethnic group 2007 (experimental) Table EE1, [Online] 2011 [cited 2011 Oct].Available from URL: http://www.statistics.gov.uk/statbase/Product.asp?vlnk=14238 15

Department for Children, Schools and Families, Tables 13a/b Primary/secondary school number of pupils by first language by LA, [Online] 2011 [cited 2011 Oct].Available from URL: http://www.education.gov.uk/rsgateway/DB/SFR/s000843/index.shtml 16

Home Office, Immigration and Asylum Statistics, Control of Immigration: Statistics United Kingdom 2009 Excel data Tables 2.5 and 2.6. [Online] 2011 [cited 2011 Oct].Available from URL: http://rds.homeoffice.gov.uk/rds/immigration-asylum-stats.html 17

Home Office, Immigration and Asylum Statistics, Control of Immigration: Statistics United Kingdom 2009 Supplementary tables Table 2q. [Online] 2011 [cited 2011 Oct].Available from URL: http://rds.homeoffice.gov.uk/rds/immigration-asylum-stats.html 18

Gordon I., Scanlon K., Travers T.,Whitehead C. Economic impact on the London and UK economy of an earned regularisation of irregular migrants to the UK greater London Authority 2009 . [Online] 2011 [cited 2011 Oct].Available from URL: http://static.london.gov.uk/mayor/economic_unit/docs/irregular-migrants-report.pdf

George Fowajuh, Public Health Information Specialist, West Midlands Public Health Observatory(WMPHO) Authors

Acknowledgments

John Kemm,, Former Director, West Midlands Public Health Observatory, Lead Consultant, , JK Public Health Consulting

Dave Newall (West Midlands Strategic Partnership), Karen Saunders (Department of Health, West Midlands) and Kate Warren (NHS Walsall) helped with useful advice and comments.

Abridged by Yasmin Akram, from the full report, â&#x20AC;&#x17E;How many migrants are there in the West Midlands and who are they?â&#x20AC;&#x;. This was commissioned by the Department of Health, West Midlands, and is a publication from the West Midlands Public Health Observatory (www.wmpho.org) and available on their website.

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3

1.

Providing cancer statistics for commissioning

Introduction

The Health and Social Care Bill 2011 envisages a fundamental reform of health services in England. One of the most significant changes in the bill is the abolition of PCTs and the introduction of Clinical Commissioning Groups (formerly GP Consortia) to plan and commission health services for local populations. Based on groups of GPs and other health professionals the CCGs will require in-depth knowledge of the likely clinical need of their population now and into the future to ensure that health services are available in a timely manner when needed. Cancer Registries have long provided detailed information and robust statistics about patients diagnosed with cancer across their area. Because cancer registries record data at patient level data is easily aggregated in any number of different ways. However to aggregate data for health organisations we need to know either the organisation code or its geographical extent in order to provide information based on either registered or resident populations respectively. In addition we need to match that cancer data with similar whole population demographics to produce cancer statistics. In July 2011 West Midlands Cancer Information Unit embarked on an exercise to consider how we might provide routine statistics and information to support newly forming CCGs. 2.

Method

Four case study PCTs were identified in the region with very different patterns of CCG uptake. The PCTs were asked to provide lists of GP practices in each CCG. An extract of cancer registrations for 2007 was taken from the National Cancer Data Repository which had been enhanced with additional GP Practice information. The GP registered population denominators for 2007 were obtained from the National Cancer Information Network (NCIN) GP practice profiles toolkit. Resident population denominators are based on ONS mid-year estimates for LSOAs. Two scenarios for providing cancer statistics for CCGs were now possible: 1. By the GP registered population in a CCG - identify cancer patients registered with all the GPs in the CCG and incidence rates calculated on the total number of people registered with those practices in the NCIN GP practice profiles. The benefit of adopting a registered population statistic is it accurately reflects the workload of the GPs in the CCG. However it ignores people resident in the area but not registered at a GP and is very difficult to visualise geographically. 2. By the resident population of a geographic area â&#x20AC;&#x201C; this is the more commonly used method for statistics provision and relies on the identification of the area served by the CCG. Once the geographical extent is defined then both cancer cases and the population demographics can be assigned using standard postcode and small area geography lookup tables.

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This method allows cancer registries to readily update their data extraction routines to account for new postcodes and changes to organisation boundaries. It is the method we have used to provide cancer statistics through time and more recently to provide statistics to Health and Wellbeing boards. This method is consistent with ONS national statistics and fully supported by statistical geographies and annual population estimates. It is easily visualised to give a sense of place. However it takes no account of patient choice to register with more distant GP practices and will not include all those people seen by GPs in a CCG. If CCGs are defined by lists of GP practices then it may not be possible to define their geographical extent of a CCG.

3.

Results

At 7th July DH had confirmed 28 CCGs in the region who declared that they would be commissioning services for 4.6 of the 5.4 million residents in the region and include 793 of the 997 GP practices identified in the Connecting for Health Attribution Data Set (ADS). Individual CCGs have declared populations of between 26,000 and 315,000, which are generally smaller than the PCTs they replace which had populations of between 161,000 and 609,000. The CCGs range in size from 6 to 99 GP practices. There are 9 CCGs in the West Midlands that appear to align with the single PCT they replace although not all the GP practices on the ADS are included in the CCG. GP registered populations tend to be larger than resident population estimates. This â&#x20AC;&#x17E;list inflationâ&#x20AC;&#x; is a well-known problem and some CCGs still declare registered populations of up to 16% larger than their PCT resident population. Progress in setting up CCGs is not uniform across the West Midlands and at the time of writing one PCT has no CCG confirmed by DH.

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KHD 2011


PCT

No. GP Practices

Resident

54

306,320

South Birmingham

67

340,200

Coventry

63

66

Registered Population

Dudley GP Commissioning

54

315,000

Independent

9

30,000

Integrated

30

175,000

Godiva

39

176,238

InSpire

28

172,000

Black Country

18

91,788

HealthWorks (Sandwell part)

14

124,340

Health Alliance

30

113,200

Population

Dudley

Sandwell

No GP Practices

CCGs

310,490

288,750

Table 1: Summary of GP Practices in each Consortium and declared extent/populations in our case tudy areas.

PCT

CCG

REGISTERED Cases

Dudley

Dudley

South Birmingham

Independent

Population

RESIDENT Crude Rate

Cases

Population

Crude Rate

1611

313,000

515

1607

305,380

528

150

28,800

520

310

33,300

480

Godiva

740

177,000

410

---

---

---

InSpire

680

173,190

372

---

---

---

Black Country

460

103,000

451

548

58,900

478

HealthWorks

510

152,000

336

672

96,200

342

Health Alliance

400

112,000

359

428

50,800

430

Coventry

Sandwell

Table 2: Summary of no cases, population and incidence rates for CCGS in each consortia across 4 case study areas

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Case Study 1: Dudley

Figure 1. Map of Dudley general practices

In Dudley one PCT has one CCG approved with the same area. There is a difference of 4 cases between the registered and resident population methods which is due to patients registered with a GP resident outside the PCT boundary. GP list inflation in Dudley is 3% but more significantly this is not uniformly applied to all age groups but is most evident in 20-34 ages and in 45-55 age groups who get fewer cancers. The larger GP registered population does reduce the incidence rate but as the counts are based on similar numbers this is not statistically significant. Case study 2: South Birmingham In south Birmingham we were particularly interested in the smaller CCG, South Birmingham Independent Commissioning as it is the 2nd smallest to be confirmed in West Midlands. It has a registered population of 30,000, equivalent to a large Birmingham ward and was approved in early in the 2nd phase because its GPs have worked closely to address local health issues since 2006. The CCG includes a wide distribution of practices across South Birmingham with a diverse population including one of the main university GP practices and some of most and least affluent areas of city.

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Figure 2. Map of South Birmingham general practices

A doubling in the number of cases and denominator populations between the registered and resident populations raised some immediate concerns about our methodology for defining geographical extent. Looking at the distribution of registered cases we could see that 65 were registered with GPs in CCG and resident in the CCG area we had defined but that another 81 registered cases are resident more than 1 km away and 7 live outside the PCT. Conversely the area defined as the geographical extent includes 143 cases registered with one of 54 GP practices not included in the CCG with one practice having as many as 31 cases, another 17 and two others 15 cases each. Crude incidence rates for registered and resident populations differ by 10% suggesting that the small size of the CCG will make it difficult to provide reliable cancer statistics over time. Unless the geographical extent of the CCG is accurately defined at the outset even our most sophisticated model of geographical extent would struggle to define such small CCGs.

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Case Study 3 - Coventry The geographical distribution of GP practices between Godiva and InSpire CCGs showed no geographical separation across the city and in some cases GP practices within the same LSOA are members of different CCGs. We did not pursue a geographical solution to the provision of cancer statistics for these CCGs, instead we look at the differences in the registered populations of these 2 consortia.

Figure 3. Map of Coventry general practices

The population profiles of the two CCGs are very different, Godiva has a higher peak in 40-44 year olds and InSpire have more young people. List inflation runs at almost 15% which with two university communities in the city might explain the higher number of young people in InSpire CCG. Crude rates of cancer are much higher in Godiva than Inspire, reflecting their different age profiles. There is only one way to provide CCG specific cancer statistics to these CCGs that is by registered population but this will be of limited use with the known problems of GP list inflation and high student turnover.

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Case Study 4: Sandwell Three CCGs aim to commission services for patients in the PCT, one extends beyond the PCT into West Birmingham. Each CCG has a similar registered population and their practices appear to form clusters across the PCT. By assigning 1km zones around each GP practice we felt able to define a geographical area to each CCG based on small area statistical geographies (LSOAs). Where LSOAs are automatically assigned to more than one CCG they are manually allocated to the nearest GP and where an LSOA is not automatically assigned it is allocated to nearest GP to provide a continuous geographical extent for each CCG.

Figure 4. Map of Sandwell general practices Comparison of data for the „registered population‟ and the „resident population‟ of each CCG revealed very similar population profiles for each CCG and broadly similar incidence rates.

4.

Mortality Rates

Our original intention to repeat our methods for mortality rates quickly identified the current lack of data to address the needs of GP commissioning. National mortality statistics are produced by the ONS using death certificate notifications. The extracts of this data for non-cancer deaths do not include the patient identifiers nor GP code, only geographical area identifiers. If mortality rates are to be produced for CCGs we will need either a geographical identifier for the CCG or to source new mortality files from ONS with GP practice code or CCG to provide routine mortality data for the

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registered populations of CCGs. The latter would of course differ from official ONS mortality statistics.

5.

Conclusions

Providing cancer statistics by GP registered population is possible but poses significant challenges for the cancer registries in England. Attributing patients to GP practice is dependent on cancer registries receiving and recording GP practice code in their datasets. Although many cancer registries do record GP practice code this has not been a mandated/compulsory field and may be poorly populated in some data archives. Whilst it is possible to trace the registered GP of patients through time it is not possible to do this retrospectively for those who are now dead. GP practice population profiles by five-year age groups are not widely available across the NHS and cancer registries do not routinely have access to any of this data. To use this data were it available for statistical analysis would require that the problems of list inflation be addressed as a matter of urgency. One of the strengths of the cancer registry database is the historical time series that it can provide. Attempting this for registered populations rather than geographically defined areas will be problematic. It would become necessary to trace GP practice code for all patients in the database, whether alive or dead. GP practice list populations would need to be collated back through the lifecycle of the cancer registry database into the 1980s and methods agreed to allocate GP practices to CCGs where those practices have now closed. Using geography and resident populations has been our preferred method of calculating cancer statistics for many years. Our cancer registry database has used patient postcode as the key to calculating statistics and it has become a fully populated field back to 1980s. Using geography allows us to readily update our data extraction routines to account for new postcodes and changes to organisations and their boundaries as was seen in the recent introduction of Health and Wellbeing boards. This method is consistent with ONS National Statistics protocols and is fully supported by statistical geographies and annual population estimates. It is easily visualised to give a sense of place. To continue to provide cancer statistics for commissioning from the cancer registry database in a consistent and flexible manner a geographical extent for each CCG must be defined in statute using standard statistical geographies such as Lower Super Output Areas as their building blocks.

Author

Diane Edwards, GIS Specialist Cancer Information Sally Vernon, Deputy Director, John Broggio, Cancer Registration Information Officer West Midlands Cancer Intelligence Unit Public Health Building, University of Birmingham B15 2TT Ralph Smith, Deputy Head of Information & Intelligence, Sandwell PCT

Acknowledgments Angela Moss, Senior Public Health Intelligence Specialist, Dudley PCT Anne Hartley, Epidemiologist, NHS Coventry.

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4 1.

Measuring the quality of general practices

Introduction

West Midlands QI (WMQI), the regional quality observatory, are developing a series of Quality Profiles for Practices, Acute, Community and Mental Health Trusts in partnership with the other Quality Observatories. The aims of the profiles are: 

to enable commissioners (both NHS and the Health and Wellbeing Boards) to compare the relative quality of their providers;

 

to enable providers to benchmark their performance against the National average; to share with patients and the public information on the quality of the services being provided.

The profiles therefore fit into both the new Commissioning architecture of the NHS and support the Patient Information Revolution by putting more information freely and transparently into the public domain.

2.

Defining Quality

The concept behind the profile is to translate the Outcomes Framework into metrics that together describe how a provider, in this case a practice, is delivering these objectives. The five domains are: 1. 2. 3. 4. 5.

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 people have a positive experience of care Treating and caring for people in a safe environment and protecting them from avoidable harm

In selecting the metrics to be included in the profile we looked for metrics that fitted a functional model of health care delivery that reflects both the progression of a condition and a patient‟s journey: • • • • •

Prevention Screening Diagnosis Treatment/intervention Follow-up

For example for Coronary Heart Disease (CHD) we looked for metrics that were relevant to: prevention such as smoking cessation and obesity; to screening and diagnosis, in this case the ratio of patients on the register to the predicted prevalence; treatment/intervention and how many people were on beta blockers. The metrics were also tested against the Donabedian model of Structure, Process, Outcome as we wanted to ensure we were not solely using process measures and also to put process measures into a quality framework. In the case of CHD, the outcome we used was „how many patients were admitted as an emergency‟. Although not the best measure of outcome as it only focuses on the negative it is the best metric we have until better patient reported outcomes are

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available. To incorporate structure metrics we have added a sixth domain to the profile for “Organisational Context”.

3.

Generating the profile

The Practice Profile was generated from a dual process of reviewing current dashboards and tools used and by a consultative process. To ensure we were not duplicating a pre-existing resource in producing the practice profile we requested profiles in use in PCTs, accessed the Primary Care Commissioning Tool, searched the internet and asked local clinician leaders for tools they used. This search proved that although a there existed a wide range of tools used to report variation by practice, none of them delivered the objective we had set out to produce a Quality profile based on the Outcome Framework and very few were in the Public domain and that they used over 300 different metrics. The APHO practice profile is perhaps the closest to what we were looking to achieve, however this is primarily condition based rather than organised into the Outcomes Framework domains. One of the founding principles of WMQI is to put information in the hands of clinicians, „no measure about me, without me‟. Therefore WMQI brought together over 100 General Practitioners (GPs), Commissioners and others with a vested interest including the local RCGP and LMC to act as our peer review group. They were sent a standard template containing the 300 metrics to review and weight on whether: • • •

„This is a good measure of quality‟ (chose one: Strongly agree, Agree, Unsure, Disagree, Strongly disagree) „This will help drive quality improvement‟ (chose one: Strongly agree, Agree, Unsure, Disagree, Strongly disagree) „What application is this most useful for? Select one or more‟: o Benchmarking against peers o Tracking improvement over time o Demonstrating achievement of a minimum quality threshold. o Proxy for other un-measurable aspects of quality

They were also asked to comment on a series of presentation options including coloured tables, the Red Amber Green (RAG) rating compared to Gold Silver Bronze, and spine charts. Their comments enabled WMQI to produce a proposed list of 60 indicators, which were tested in a workshop with 20 GPs and commissioners. The challenges received focused primarily on the lack of long term condition metrics and around the use of hospital attendance based metrics as proxies for the behaviour of GPs. Both of these highlight the on-going issue about the lack of GP level metrics of quality apart from the Patient Survey and the Quality Outcomes Framework (QOF), both of which are limited and not without detractors. The final list of metrics is given in table 1, along with the data sources. Although some data items are not currently available, they have been included as part of the final dataset as it is important that these metrics are sourced in the future to complete the quality story.

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Table 1: Metrics selected for inclusion and their data sources Preventing people from dying prematurely Exception rate for QOF atrial fibrillation indicators Patients with hypertension: Last (9 months) blood pressure <=150/90 Patients with TIA/non-haem stroke: record that aspirin, APT or ACT is taken CHD prevalence ratio: observed/predicted CHD patients currently treated with beta blocker CHD Emergency Admission Rate Patients with chronic kidney disease and hypertension treated with an ACE inhibitor/ ARB Patients with diabetes: last (15 months) HbA1c is <=10 Diabetes hospital admission rate Patients with LVD who are currently treated with ACE inhibitor or ARB Heart failure hospital admission rate Alcohol related hospital admission rate % of patients with a long term condition to whom smoking cessation advice has been offered Smoking 4 week quit ratio Obesity related hospital admission rate 1 year survival rates of all cancers 5 year survival rates of all cancers 2-week referrals (cancer) Enhancing quality of life for people with Long-term conditions Dementia hospital admission rate Emergency psychiatric readmissions Patients on the mental health register with comprehensive care plan A&E attendances for patients with mental health problems COPD prevalence ratio: observed/predicted Patients with COPD: record of FeV1 in last 15 months COPD hospital admission rate Patients with asthma: had an asthma review in the last 15 months Patients age 18 and over on drug treatment for epilepsy who have a medication review

Data source QOF QOF QOF QOF QOF NHS comparators QOF QOF NHS comparators QOF SUS SUS QOF Data not available SUS National Cancer Information Toolkit (1)

SUS HES QOF SUS QOF QOF SUS QOF QOF

Helping people to recover from episodes of ill health or following injury Proportion of A&E attendances admitted to hospital SUS Accident and emergency attendances rate NHS comparators Emergency hospital admission rate NHS comparators Emergency hospital admission rate for the 19 Ambulatory Care NHS comparators Sensitive Conditions Zero day Length of stay emergency admissions without procedure and SUS discharged home Falls related hospital admission rate in older people SUS Emergency hospital readmission rate within 28 Days of discharge NHS comparators

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Repeated emergency hospital admissions GP referrals to outpatient (first attendance) rate Hospital admission rate with length of stay greater than 14 days Ratio of A&E attendances referred by walk-in centres/GPs Ensuring people have a positive experience of care GP patient survey: helpfulness of receptionists GP patient survey: satisfaction with doctor GP patient survey: satisfaction with nurse GP patient survey: able to see a GP fairly quickly GP patient survey: able to book ahead for an appointment GP patient survey: see their preferred doctor always, almost always or a lot of the time Inappropriate end of life care emergency hospital admissions

HES NHS comparators SUS Data not available Practice Survey Practice Survey Practice Survey Practice Survey Practice Survey Practice Survey Data not available

Treating and caring for people in a safe environment and protecting them from avoidable harm Emergency admission rate from residential & nursing homes SUS Childhood Immunizations - % of children receiving immunizations Data not available Influenza immunizations for at risk groups Data not available Cervical Screening Programme - % of eligible patients screened QOF National Cancer Information Bowel screening uptake Toolkit (1) National Cancer Information Breast screening coverage Toolkit (1) Chlamydia screening uptake Data not available Effective use of resources Number of GP appointments per 1,000 population Data not available Number of nurse appointments per 1,000 population Data not available Number of frequent attendees of A&E departments SUS Cost of prescribing YTD (Year to Date) NHS comparators Cost of procedures of limited clinical value Data not available ACE to ARB ratios etc Data not available Number of antibacterial drugs dispensed per STAR-PU NHS comparators % of prescribed low cost Statins NHS comparators Prescribing for which a generic equivalent is available Data not available 1- Data from National Cancer Information Toolkit is not currently available for the public

4.

The profile

The profile is currently being published as a pdf file, supported by downloadable CSV files containing the data used in its generation, along with full metadata. The presentation style agreed through the consultation was a RAG rated spine chart. These charts are constructed using statistical process control (SPC) principles and use control limits to indicate variation from the national mean. The display shows both two standard deviation (95%) control limits and three standard deviation (99.8%) control limits. Values within these limits (the light grey section) are said to display 'normal cause variation' in that variation from the mean can be considered to be random. Values outside these limits

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(in the light green or orange sections) are said to display 'special cause variation' at a two standard deviation level, and a cause other than random chance should be considered. Values outside these sections (in the dark green or red sections) also display 'special cause variation' but against a more stringent test. Variation at the two standard deviation level can be considered to raise an alert, and variation at the three standard deviation level to raise an alarm. This is illustrated in figure 1 as extracted from the front page of the profile.

Figure 1: Profile Spine chart

An illustration of a profile is shown in figure 2. Profiles are being created for every practice in England, with West Midlands being a priority. They are also available by PCT and Region, and will be available for the clinical commissioning groups as they come together. The profiles will be made publically available via our portal on the WMQI http://www.wmqi.westmidlands.nhs.uk/wmqiportal/practice-profiles and NHS Local www.nhslocal.nhs.uk websites, supported with a plain English guide on how to interpret data. We are constantly developing how we present data to make it available to all service users to assist them in choosing their care provider. To this end we are working with NHS Local to produce a reduced version of the profile in a star rating format.

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Figure 2. Components of a practice quality profile

38

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Figure3. Specimen example of a profile for a specific practice

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Links: APHO Practice Profiles: http://www.apho.org.uk/pracprof/ General Practice Survey: http://www.gp-patient.co.uk/info/ NHS Outcomes Framework : http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/PublicationsPolicyAndGuidance/DH_ 122944 Primary Care Commissioning Toolkit: http://www.pcc.nhs.uk/ Quality Outcomes Framework: http://www.ic.nhs.uk/statistics-and-data-collections/audits-andperformance/the-quality-and-outcomes-framework/the-quality-and-outcomes-framework-2010-11 All links lasted accessed: October 2011

Author

40

Richard Wilson, Head, West Midlands QI NHS West Midlands, St Chadâ&#x20AC;&#x;s Court, 213 Hagley Road Birmingham B16 9RG

KHD 2011


5 1.

Bowel Cancer Screening in the Black Country Cluster

Background

Bowel cancer is now the third commonest cancer in the UK and the second most frequent cause of cancer deaths, with over 16,000 deaths being attributed to it each year1. It is currently estimated that 1 in 20 people will develop bowel cancer during their lifetime1. Regular screening has been shown to reduce the risk of dying from bowel cancer by 16%2. Between 70% and 90% of bowel cancers develop from benign polyps lining the bowel wall 1. A polyp takes on average 10 years to develop into a cancerous tumour3.The incidence of bowel cancer increases with age; the median age for diagnosis is 704. This would suggest that screening for polyps at 60 would capture a large percentage of those at risk of developing bowel cancer in the early stages.

2.

The Bowel Cancer Screening Programme â&#x20AC;&#x201C; current provision

The NHS Bowel Cancer Screening Programme was established in April 2006 as a two year rolling programme offering screening to both men and women aged between 60 and 69. Screening was rolled out from July 2006, achieving nationwide coverage by 2010. It is now estimated that most areas will have sent out invitations to most eligible people by the end of 20125. Screening is offered for those in the eligible age bracket with no symptoms of bowel cancer, aiming to catch the cancer at an early stage when it is more responsive to treatment. It is also designed to detect polyps, which though harmless in themselves could develop into cancerous cells in the future. Polyps can be easily removed, reducing the risk of bowel cancer developing. Invitations to people to take part are sent out in batches according to the date of birth. The letter together with an information leaflet is sent to the individualâ&#x20AC;&#x;s home address. It can take up to two years for every eligible person in an area to be invited. Approximately one week after the invitation letter, a testing kit and step-by-step instructions is sent out to participants. Though the current screening programme is aimed at 60-69 year olds those aged over 70 can request a kit using a freephone number. However, from April 2010 the screening age range started extending to 74. General practices are not directly involved in the screening process, though they are notified when invitations are sent out and receive a copy of the results.

3.

How the Bowel Cancer Screening Process works

As polyps and bowel cancer sometimes bleed, faecal occult blood tests (FOBt) find tiny amounts of blood not normally visible to the naked eye in bowel movements. The FOBt does not detect cancer, but finding these blood traces indicates that further investigation is needed. Those within the eligible age-range are sent a FOBt to their home address. After returning the completed test, results should be received within 2 weeks.

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There are 4 possible outcomes of the tests: Normal (invited for screening again in 2 years) Abnormal (referred for further investigation) Unclear (test is repeated up to 2 times) Spoilt kit / technical fail (test is repeated)

FOBt kit delivered

Sample returned to lab

Test results received

Up to 2 weeks

Normal Result

Invited to re-test in 2 years if <70

Unclear result – repeat test Abnormal Result

Offered appointment for colonoscopy

Clear: FOB retest in 2 years if <70

Polyp: tests/treat

Cancer: refer/treat

Figure 1: Bowel Cancer Screening Process

Source: Bowel Cancer UK – “The Bowel Cancer Screening Programme – A Progress Report on the Roll-Out of Screening in England “ (Nov 2007).

About 2 in every 100 returned tests will have an abnormal result6. An appointment with a specialist nurse is offered and, if appropriate, a colonoscopy. A colonoscopy looks directly at the lining of the large bowel and is the most effective way to diagnose bowel cancer. There are 3 possible outcomes of the colonoscopy: Normal (returned to normal screening) Polyps are found Cancer is found Any polyps found will be removed and checked for abnormal cells which could be cancerous. Around 4 in 10 people who have a colonoscopy will be found to have one or more polyps7. Depending on the number and size of the polyps found patients will be either returned to normal screening, have 3 yearly colonoscopy screening until they have two negative examinations or a colonoscopy after 12 months followed by 3 yearly colonoscopy screening until they have two negative examinations.

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Any cancers discovered will be immediately referred. Around 1 in 10 people who have a colonoscopy will be found to have bowel cancer7.

4.

The Bowel Cancer Screening Programme – future provision

Following the Cancer Reform Strategy in 2007 the current age range for screening of 60-69 is being extended to include those aged 70-74. This age extension began in April 2010 and by February 2011, 31 of the 58 local screening centres had started inviting 70-74 year olds. In January 2012 the Department of Health is launching the „Be Clear on Cancer‟ advertising campaign to raise awareness of bowel cancer and its symptoms, aiming to get people displaying any of the early symptoms to talk to their GP. Another recent development in bowel cancer screening is for the introduction of flexible sigmoidoscopy (flexi-sig) for all men and women at the age of 55. This is a one-off test, looking for polyps and cancers before symptoms appear and is in addition to the Bowel Cancer Screening Programme. Details of the flexi-sig screening programme have yet to be announced.

5.

Programme implementation in the Black Country

For the four Primary Care Trusts comprising the Black Country Cluster (Wolverhampton, Dudley, Walsall and Sandwell) screening started between July 2006 and April 2008, with invitations being sent from the Wolverhampton screening centre. Table 1 shows the phased start dates PCT

Start date

Wolverhampton City

July 2006

Dudley

October 2006

Walsall

October 2006

Sandwell

April 2006

Table 1. The 4 PCTs in the Black Country Cluster and the implementation time table

6.

Methodology

Data from the start of the Bowel Cancer Screening Programme to date was requested by each of the 4 PCTs within the Black Country Cluster from the Midlands and Northwest Bowel Cancer Screening Programme Hub. This was provided at an aggregated level giving details of invitations to both screening and diagnostic tests by invitation date, gender, 5 year age band, Lower Super Output Area (LSOA), Mosaic Public Sector groups and types (where available) and GP Practice. Data were also provided at hub level for benchmarking purposes.

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These data have been analysed by completed 2 year screening cycle by PCT and at Cluster level. Uptake has been calculated as the percentage of 60-69 year olds invited to participate in the screening programme who returned an adequate sample. To calculate what percentage of the eligible population was invited to participate in the screening programme the coverage was calculated by dividing the number invited by the number within the eligible age group (60-69). As this is a transient population, with movement both in and out of the area within the two year period, it was decided to use the 2010 Attribution Dataset7 for the eligible population. The number invited was taken from data provided by the Midlands & Northwest Bowel Cancer Screening Programme Hub. This then provides an estimate of coverage for the Black Country Cluster of 90.2%

7.

Results

Numbers eligible, invited and coverage PCT

Most recent screening cycle dates (cycle no.)

Eligible population (aged 60-69)

Invited

Coverage (%)

Wolverhampton City

Jul 08 â&#x20AC;&#x201C; Jun 10 (3)

23,215

20,033

86.3

Dudley

Oct 08-Sep10 (3)

35,564

33,034

92.9

Walsall

Oct 08 - Sep 10(3)

26,659

26,179

98.2

Sandwell

Apr 09 â&#x20AC;&#x201C; Mar 11 (2)

29,793

24,696

82.9

115,231

103,942

90.2

Black Country Cluster

Table 2. Invitation coverage in the 4 Black Country PCTs for the most recent 2-year screening cycle for the age group 60-69.

Source: Attribution data set 2010, Dept of Health, Jun 2010, Midlands and Northwest Bowel Cancer Screening programme Hub As the estimated coverage is high, the invited population rather than the eligible population has been used in this analysis. Five screening centres started the age extension in November 2008 as early implementers, this includes the Wolverhampton centre, which covers the Black Country Cluster. PCT

44

Most recent screening cycle dates (cycle no.)

Eligible population (aged 70-74)

KHD 2011

Invited

Coverage (%)


Wolverhampton City

Jul 08 â&#x20AC;&#x201C; Jun 10 (3)

9,855

7,267

73.7

Dudley

Oct 08 - Sep10 (3)

13,859

11,979

86.4

Walsall

Oct 08 - Sep 10(3)

10,729

8,873

82.7

Sandwell

Apr 09 â&#x20AC;&#x201C; Mar 11 (2)

12,341

4,683

37.9

46,783

32,802

70.12

Black Country Cluster

Table 3. Invitation coverage in the 4 Black Country PCTs for the most recent 2-year screening cycle for the extended age group of 70-74.

Source: Attribution data set 2010, Dept of Health, Jun 2010, Midlands and Northwest Bowel Cancer Screening programme Hub Though this age extension is well underway in the Black Country the level of coverage of the eligible population is low and as such it was decided for this study to look at the 60-69 population only.The uptake across all 4 PCTs for each completed cycle demonstrates that uptake has risen with each successive 2 year rolling screening cycle. % Uptake

England Target

Midlands & Northwest Hub average

70

% adequate screens

60

50

40

30

20

10

0

1

2

3

Wolverhampton City PCT

1

2

3

NHS Dudley

1

2

3

NHS Walsall

1

2

Sandwell PCT

Trust and Screening Cycle

Figure 2: Proportion of those aged 60-69 years invited for screening who supplied an adequate sample (by Black Country Cluster PCTs and completed cycles)

The uptake for NHS Dudley has been consistently above the Midlands and Northwest Hub average of 53.9% and at 59.1% uptake for the most recent screening cycle is now close to the national screening

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target of 60%. NHS Walsall is also approaching the hub average as the uptake was 53.4% in the most recent screening cycle. Uptake by gender is significantly lower for men (and conversely significantly higher for women) than the cycle average for each PCT and in each screening cycle.

NHS Dudley

Wolverhampton City PCT

% Uptake

Cycle average

70

70

60

60

50

50

% adequate screens

% adequate screens

% Uptake

40

30

40

30

20

20

10

10

0

0 Male

Female

Male

Cycle 1

Female

Male

Cycle 2

Male

Female

Female

Male

Cycle 1

Cycle 3

Male

Female

Cycle 3

Screening Cycles and Gender

NHS Walsall % Uptake

Female

Cycle 2

Screening Cycles and Gender

Sandwell PCT

Cycle average

% Uptake

70

70

60

60

50

50

% adequate screens

% adequate screens

Cycle average

40

30

40

30

20

20

10

10

0

Cycle average

0 Male

Female

Cycle 1

Male

Female

Cycle 2

Male

Female

Cycle 3

Male

Female

Cycle 1

Screening Cycles and Gender

Male

Female

Cycle 2

Screening Cycles and Gender

Figure 3: Proportion of the responsible population aged 60 â&#x20AC;&#x201C; 69 years invited for screening who supplied an adequate sample (by PCT, gender and completed cycles)

The uptake is also increasing for both sexes for successive completed cycles, though the gap between men and women for uptake remains fairly constant. Deprivation and screening uptake

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To explore any potential link between deprivation and the uptake of bowel cancer screening uptake for the most recent screening cycle has been analysed by the Index of Multiple Deprivation 2007 national deciles.

Uptake

Cluster Average

80

70

% adequate samples

60

50

40

30

20

10

0 1 (Most Deprived)

2

3

4

5

6

7

IMD 2007 Decile

8

9

10 (Least Deprived)

Figure 4: Proportion of those aged 60-69 years invited for screening who provided an adequate sample by Index of Multiple Deprivation 2007 Decile (Most Recent Screening Cycle, Black Country Cluster PCTs)

This would suggest that there is a direct link between deprivation and uptake. We examine this putative link further through a „boston plot‟ (a quadrant scatter plot with the Black Country Cluster average splitting the data horizontally and the mid-point of the IMD quintile 1 range splitting the data vertically). The proportion of each general practice‟s population in the IMD 2007 national quintile 1(the most deprived) has been calculated along with the uptake for the most recent screening cycle for each practice.

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W-ton Uptake

Dudley Uptake

Walsall Uptake

Sandwell Uptake

% in IMD 1 mid-point

BCC Average

100 90 80

% adequate screens

70 60 50 40 30 20 10 0 0

10

20

30

40

50

60

70

80

90

% of registered population in IMD 2007 national quintile 1

Figure 5: Proportion of 60-69 year olds invited to participate in screening who returned an adequate sample by GP Practice (Black Country Cluster, most recent screening cycle) Numbering the quadrants clockwise starting at the top left, quadrant 2 gives practices with an unexpectedly high uptake, with one practice in Walsall achieving 100% uptake even though a high proportion of its registered population is resident in the most deprived national quintile. It should be noted however that this practice has a small population and very low numbers were invited for screening. Similarly practices in quadrant 4 have an unexpectedly low uptake as they have a much smaller proportion of their resident population living in the most deprived national quintile. In general however the negative correlation displayed would appear to confirm the link between deprivation and the number of adequate screening kits returned in the Bowel Cancer Screening Programme. Looking at the uptake for the most recent screening cycle from a geographical perspective the rates for each Middle Super Output Area (MSOA) can be mapped to give an overall picture of uptake across the Black Country Cluster. This would also appear to correlate low uptake with areas of known deprivation.

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Map 1: Uptake by Middle Super Output Area for the Black Country Cluster PCTs (significance measured against Black Country Cluster average uptake) 0

Uptake by MSOA for Black Country Cluster Most Recent Screening Cycle

5.322 kilometers

Significantly Higher Higher Low er Significantly Low er

Scale: 1:133,000

Walsall Walsall

Wolverhampton Wolverhampton

Sandwell Sandwell

Dudley Dudley

Topographic Data Š Crown copyright and database rights 2011 Ordnance Survey 100050565 Three of the PCTs within the Black Country Cluster (Wolverhampton, Dudley and Sandwell) use the Mosaic Public Sector population segmentation tool.

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The tool classifies UK postcodes into 15 distinct groups and then further sub-divides these groups into 67 types which describe socio-economic and socio-cultural behaviour in that area. However it is important to remember that this is a classification of the postcode area as a whole and it may well have people who do not fit into that type or group also living within that area. Table 4: Proportion of 60-69 year olds invited to participate in screening who returned an adequate sample in the Black Country Cluster by Mosaic Public Sector Group Mosaic Group

Invited

A Residents of isolated rural communities B Residents of small and mid-sized towns with strong local roots C Wealthy people living in the most sought after neighbourhoods D Successful professionals living in suburban or semi-rural homes E Middle income families living in moderate suburban semis F Couples with young children in comfortable modern housing G Young, well-educated city dwellers H Couples and young singles in small modern starter homes I Lower income workers in urban terraces in often diverse areas J Owner occupiers in older-style housing in ex-industrial areas K Residents with sufficient incomes in right-to-buy social houses L Active elderly people living in pleasant retirement locations M Elderly people reliant on state support N Young people renting flats in high density social housing O Families in low-rise social housing with high levels of benefit need U Unclassified Black Country Cluster* Totals

129 7,405 879 5,966 11,355 1,161 559 1,198 4,818 11,172 14,910 2,097 5,542 2,543 5,614 2,415 77,763

Adequate % Uptake Screens 71 55.0 4,841 65.4 600 68.3 4,053 67.9 6,684 58.9 715 61.6 264 47.2 579 48.3 1,806 37.5 6,595 59.0 7,319 49.1 1,371 65.4 2,545 45.9 895 35.2 2,195 39.1 1,147 47.5 41,679 53.6

Sig. Diff.‡               

* figures exclude Walsall PCT who don't use MOSAIC segmentation tool. ‡ * Figures excludeWalsall) NHS Walsall who don‟t use Mosaic Public Sector Significant difference to Black Country Cluster Total (excluing ‡

Significant difference to Black Country Cluster Total (excluding NHS Walsall)

Looking at the data for the cluster as a whole at the Mosaic group level shows significantly low uptake (when compared to the uptake for the BC) for all the low income Mosaic groups (H, I, K, M, N, O). The Mosaic types which have a significantly low uptake also demonstrate this link with social deprivation as well as a possible link with minority ethnic groups (Table 5). Types E20 – Upwardly mobile South Asian families living in inter-war suburbs and I40 – Multiethnic communities in newer suburbs away from the inner city are 2 of only 3 types with a significantly low uptake without a low income or social deprivation aspect. However ethnicity data are not currently available from the Bowel Cancer Screening Programme so this link cannot be investigated further.

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Table 5: Proportion of 60-69 year olds invited to participate in screening who returned an adequate sample in the Black Country Cluster by Mosaic Public Sector Type where uptake is significantly low (compared to the Black Country Cluster average) Mosaic Type

Invited

E20 Upwardly mobile South Asian families living in inter war suburbs G26 Well educated singles living in purpose built flats G32 Students and other transient singles in multi-let houses G33 Transient singles, poorly supported by family and neighbours G34 Students involved in college and university communities H36 Young singles and sharers renting small purpose built flats H37 Young owners and rented developments of mixed tenure I40 Multi-ethnic communities in newer suburbs away from the inner city I42 South Asian communities experiencing social deprivation I43 Older town centres terraces with transient, single populations I44 Low income families occupying poor quality older terraces K50 Older families in low value housing in traditional industrial areas K51 Often indebted families living in low rise estates M56 Older people living on social housing estates with limited budgets M57 Old people in flats subsisting on welfare payments M59 People living in social accommodation designed for older people N60 Tenants in social housing flats on estates at risk of serious social problems N61 Childless tenants in social housing flats with modest social needs N66 Childless, low income tenants in high rise flats O67 Older tenants on low rise social housing estates where jobs are scarce O68 Families with varied structures living on low rise social housing estates O69 Vulnerable young parents needing substantial state support Black Country Cluster* Totals

1,327 71 70 150 29 195 278 31 1,402 2,194 1,172 8,382 1,058 2,606 1,635 1,233 1,066 910 567 2,647 453 2,514 77,763

Adequate % Uptake Sig. Diff.‡ Screens 553 41.67  26 36.62  25 35.71  63 42.00  10 34.48  81 41.54  128 46.04  8 25.81  372 26.53  932 42.48  484 41.30  3,990 47.60  491 46.41  1,308 50.19  688 42.08  505 40.96  369 34.62  335 36.81  191 33.69  1,093 41.29  201 44.37  901 35.84  41,679 53.60

* Figures exclude NHS Walsall who don‟t use Mosaic Public Sector Significant difference to Black Country Cluster Total (excluding NHS Walsall)

% Abnormals

Midlands & Northwest Hub average

3.5

% abnormal results

3.0

2.5

2.0

1.5

1.0

0.5

0.0

1

2

3

Wolverhampton City PCT

1

2

3

NHS Dudley

1

2

3

NHS Walsall

1

2

Sandwell PCT

Trust and Screening Cycle Figure 6: Proportion of adequate screens with an abnormal result (by Black Country Cluster PCT and completed cycle)

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Abnormal Results The number of abnormal results returned for adequate screens has also been analysed by PCT and for the cluster as a whole for each screening cycle. In the first cycle of screening for each PCT the proportion of adequate screening kits returning an abnormal result is higher than in the following cycles, which is not unexpected as it is the first time the entire age range has been screened whereas with subsequent cycle it would only be the first time for a small number of participants and the other abnormal results would be as a result of changes from the last cycle for those who have already been screened at least once previously. Looking in more detail at the most recent cycle of screening gives some interesting results for differences in the proportion of abnormal results for gender Gender

No. invited

No adequate screen

No abnormal result

No. attended clinical tests*

% adeq samples

% abnormal results

% attended clinical tests*

Male

50,079

25,720

623

568

51.4

2.4

91.2

Female

51,358

28,592

433

388

55.7

1.5

89.6

Total

101,437

54,312

1,056

956

53.5

1.9

90.5

Table 6: Proportion of 60-69 year olds invited to participate in screening returning adequate samples, abnormal results received and subsequent clinical tests attended by gender for the Black Country Cluster * No data available for attendance of clinical tests for Wolverhampton City PCT

As discussed previously, the uptake in screening for males is significantly low across the Black Country Cluster and for all screening cycles, however the converse is true for the proportion of abnormal screens with males having a significantly high proportion of adequate screens returning an abnormal result. This difference in response and abnormal results rates by gender holds for the Midlands and Northwest hub as a whole as well being evident in the UK Colorectal Cancer Screening pilot8. Where a screening kit has returned an abnormal result all participants are offered an appointment with a specialist nurse and if clinically required further tests. Uptake for the clinical tests is similar across both sexes at around 90%. Examining the proportion of abnormal results by IMD 2007 national decile also points to a link with deprivation.

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% Abnormals

Cluster Average

3.5

3.0

% abnormal results

2.5

2.0

1.5

1.0

0.5

0.0 1 (Most Deprived)

2

3

4

5

6

7

IMD 2007 Decile

8

9

10 (Least Deprived)

Figure 7: Proportion of adequate screens with an abnormal result by Index of Multiple Deprivation 2007 Decile (persons aged 60-69 invited by the Bowel Cancer Screening Programme for the most recent cycle within the Black Country Cluster)

Male

Female

BCC Average (Males)

BBC Average (Females)

120

100

Mortality DSR

80

60

40

20

0

IMD 2007 national quintile

Figure 8: Directly Standardised Mortality Rates from Colorectal Cancer by IMD 2007 National Quintile (5-year rates, Black Country Cluster, Males & Females aged 60-69, 2005-2009)

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Currently no information is available at PCT level for the outcome of clinical tests following an abnormal screening result. However it is possible to look at the mortality rate for Bowel (Colorectal) cancer across the cluster for 2005 â&#x20AC;&#x201C; 2009 This further confirms the link with both deprivation and gender as males have a higher mortality rate than females across the Black Country Cluster and for both sexes the mortality rate is highest for those resident in the most deprived quintile, though not statistically significant.

8.

Key Findings

The analysis has shown that uptake for the Bowel Cancer Screening Programme for 60-69 year olds across the Black Country Cluster has increased with each successive 2 year rolling cycle of screening and for some PCTs is now approaching the national target of 60%. For the most recent cycle uptake at PCT level ranges from 47.5% (Sandwell PCT) to 59.1% (NHS Dudley) meaning that there is a large variation in uptake across the patch. There is significantly low uptake for males within the 60-69 year old age range but there are also a significantly high number of abnormal results returned. This combination indicates that further work needs to be done to target this demographic in particular. Links have also been shown to exist between low uptake and areas with high deprivation levels. There is also some evidence that these same areas experience a higher proportion of abnormal results. The number of abnormal results returned for adequate screening kits is initially high for the first cycle, but is then consistent within each of the 4 PCTs and subsequent screening cycles. There is a higher rate of abnormal results for Sandwell PCT and Wolverhampton City PCT, which have a higher proportion of their registered population resident in the most deprived IMD national quintile, which again points to a link with deprivation and abnormal results, so this is also an area to target in future campaigns. There is also some evidence of a link with ethnicity through using the Mosaic Public Sector population segmentation tool, highlighting the South Asian community as well as areas with high levels of social deprivation and low income as types with low uptake rates. Following the introduction in January 2012 of the national bowel cancer awareness campaign by the Department of Health it will be interesting to see if this has a positive impact on the uptake of screening offered. A large rise in uptake could also lead to an initial rise in abnormal results and cancers detected, as more people will be being screened for the first time, so this may also have an impact on services.

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References 1

Cancer Research UK, 2005. Cancerstats Cochrane Database of Systematic Reviews, 2006. Screening for colorectal cancer using the faecal occult blood test: an update. 3 Winawer SJ. Natural history of colorectal cancer. American Journal of Medicine, 1999, 106 (1A): 3Sâ&#x20AC;&#x201C;6S. 4 National Digestive Diseases Information Clearinghouse (NDDIC) (available at: http://digestive.niddk.nih.gov/index.htm; last assessed 5 May 2006). 5 NHS Bowel Cancer Screening Programme web-site (www.cancerscreening.nhs.uk/bowel) 6 Hewitson P, Woodrow C and Austoker J, Evidence Summary: Patient Information for the NHS Patient Bowel Screening Programme, 2008 (available at http://www.cancerscreening.nhs.uk/bowel/ publications/nhsbcsp04.pdf; last accessed 14 Oct 2011) 7 Department of Health, June 2010 8 Evaluation of the UK Colorectal Cancer Screening Pilot, 2003. (available at http://www.cancerscreening.nhs.uk/bowel/finalreport.pdf, last accessed 17 Oct 2011) 2

Authors

Acknowledgments

Suzanne Holt, Public Health Intelligence Analyst Angela Moss, Senior Public Health Intelligence Specialist Dudley Public Health, St Johns House, Union Street, Dudley DY2 8PP Emma Thomas, Senior Analyst, Public Health Intelligence Team,NHS Walsall Ralph Smith, Deputy Head of Information and Intelligence, Sandwell Primary Care Trust

Jason Gwinnett, Senior Public Health Information Analyst, Public Health, Wolverhampton City PCT Alison Tennant, Cancer Screening Programmes Lead, Dudley Public Health

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6 1.

The ten most common cancers in the West Midlands

Background

In the West Midlands there are over 28,000 invasive cancers (excluding non-melanoma skin cancer) diagnosed and recorded by the cancer registry annually, with approximately half diagnosed in males and half in females. This chapter displays the most common types of cancer diagnosed, and examines how this profile of cancers varies with age and socio-economic status. The profile of cancers in the West Midlands in 2008 is compared to the profile in England in 2008, and to the profile of cases in the West Midlands in 1988.

2. The ten most common cancers in the West Midlands compared to England West Midlands, males Incidence 26% 15% 14% 4% 4% 4% 4% 4% 3% 3%

20% 5,000

4,000

Cancer site o s t a t e Colorectal Tra ch ea, B ron ch u s & Lun g N o n - H o d g kin ' s l y m p h o m a B l a d d e r O e s o p h a g u s H e a d & N e c k S t o m a c h M el an o ma of th e ski n P a n c r e a s O t h e r s

P

3,000

2,000

1,000

Mortality 13% 11%

r

0 Number of cases (% of all cases)

24% 3% 4% 7% 3% 5% 1% 5%

25%

0

1,000

2,000

3,000

Fig 1. All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008.

England, males Incidence 24% 14% 14%

5% 4% 4% 4% 3% 3% 3% 21% 50,000

40,000

Cancer site r o s t a t e Trachea, Bronchus & Lung C o l o r e c t a l B l a d d e r N o n - H o d g kin ' s l y m p h o m a H e a d & N e c k M el an o ma of th e ski n O e s o p h a g u s K i d n e y S t o m a c h O t h e r s

Mortality 13% 24% 11%

P

30,000

20,000

10,000

0 Number of cases (% of all cases)

0

4% 3% 2% 1% 6% 3% 4% 29% 10,000

20,000

Fig 2: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008.

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30,000


Incidence 33%

11% 11%

21% 5,000

4,000

3,000

2,000

West Midlands, females Cancer site Mortality 16% B r e a s t 10% Colorectal 19% Trachea, Bronchus & Lung 6% 3% U t e r u s 5% 2% Non-Hodgkin's lymphoma 4% 6% O v a r y 3% M e la no ma o f the s kin 1% 3% 5% P a n c r e a s 2% C e r v i x 1% 2% K i d n e y 2% O t h e r s 1,000 0 0 Number of cases (% of all cases)

1,000

34%

2,000

3,000

Fig 3: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008

England, females Incidence 31% 11% 11%

4% 4% 4% 4% 3% 2% 2% 24% 50,000

40,000

Cancer site r e a s t Trachea, Bronchus & Lung C o l o r e c t a l U t e r u s O v a r y M el an o ma of th e ski n N o n - H o d g kin ' s l y m p h o m a P a n c r e a s L e u k a e m i a B l a d d e r O t h e r s

Mortality 16% 20%

B

30,000

20,000

10,000

0 Number of cases (% of all cases)

0

10%

2% 6% 1% 3% 5% 3% 2% 31% 10,000

20,000

30,000

Fig 4: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008.

For both males and females in the West Midlands, the top 3 cancer sites (prostate or breast, colorectal and lung) account for over half of new cancer diagnoses and almost half of all cancer deaths. A similar picture occurs in England as a whole, although the relative positions of lung and colorectal cancers are reversed. The eight most common cancers in the West Midlands are similar to those in England for both males and females. Kidney cancer incidence for males in the West Midlands is lower than that in England, and so it does not appear in the regionâ&#x20AC;&#x;s ten most common cancers. Incidence of cervical cancer is higher in the West Midlands than in England. This may be related to the higher than average levels of deprivation in the region and the relatively poor take-up of screening amongst more deprived women in the eligible population. Lung cancer is the most common cause of death due to cancer in both males and females, in the West Midlands and nationally.

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3.

Most common cancers 1988 to 2008 West Midlands, males Incidence

Cancer site o s t a t e Colorectal Tra ch ea, B ron ch u s & Lun g N o n - H o d g kin ' s l y m p h o m a B l a d d e r O e s o p h a g u s H e a d & N e c k S t o m a c h M el an o ma of th e ski n P a n c r e a s O t h e r s

26%

P 15% 14% 4% 4% 4% 4% 4% 3% 3%

20% 5,000

4,000

3,000

2,000

1,000

Mortality 13% 11%

r

0 Number of cases (% of all cases)

24% 3% 4% 7% 3% 5% 1% 5%

25%

0

1,000

2,000

3,000

Fig 5: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008. West Midlands, males Incidence 25%

Cancer site Tra ch ea, B ron ch u s & Lun g 15%

7% 7%

21%

4,000

P

r

B

l

S

t

2,000

1,000

o

t

e

a

s d

t d

a

e

r

o

m

a

c

h

3%

O e

s o p h

3%

L

u

3%

P

3% 2%

N o n - H o d g kin ' s l y m p h o m a K i d n e y O

3,000

33% 12%

Colorectal 12%

5,000

Mortality

e a

k n

t

a c

h

a g u

s

m

a

e r

e

e

i a

s

r

s

0 Number of cases (% of all cases)

0

10%

4% 9% 4% 3% 4% 2% 2% 18%

1,000

2,000

3,000

Fig 6: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 1988.

Incidence 33%

11% 11%

21% 5,000

4,000

3,000

2,000

West Midlands, females Cancer site Mortality 16% B r e a s t 10% Colorectal 19% Trachea, Bronchus & Lung 6% 3% U t e r u s 5% 2% Non-Hodgkin's lymphoma 4% 6% O v a r y 3% M e la no ma o f the s kin 1% 3% 5% P a n c r e a s 2% C e r v i x 1% 2% K i d n e y 2% O t h e r s 1,000 0 0 Number of cases (% of all cases)

1,000

34%

2,000

Fig 7: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008. In males, the proportion of lung cancer diagnoses has fallen from 25% to 14% between 1988 and 2008. The proportion of cancer deaths in males from lung cancer has fallen from 33% to 24%.

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3,000


The proportion of prostate cancer diagnoses has risen from 12% to 26%. In 2008, cancer of the head & neck and melanoma of the skin have replaced leukaemia and kidney cancer in the ten most common sites. West Midlands, females Incidence 26%

13% 10% 5% 5% 4% 3% 3% 2% 2%

26% 5,000

4,000

3,000

Cancer site e a s t Colorectal Tra ch ea, B ron ch u s & Lun g 6% O v a r y 2% U t e r u s 6% S t o m a c h 2% B l a d d e r 5% P a n c r e a s N o n - H o d g kin ' s l y m p h o m a 2% M e l a n o m a o f t h e s k i n 1% O t h e r s B

2,000

1,000

r

0 Number of cases (% of all cases)

0

Mortality 21% 13% 14%

28% 1,000

2,000

3,000

Fig 8: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 1988. In females in 2008, cervical cancer and kidney cancer have replaced stomach cancer and bladder cancer in the ten most common sites. The proportion of cancer deaths from lung cancer has risen in females from 14% to 19%, in contrast to the decline seen in males. The proportion of cancer deaths from breast cancer has fallen from 21% to 16%. There have been many significant changes to the health of the population of the West Midlands between 1988 and 2008 which explain the changes in the most common cancers. Smoking is less common, screening programmes have been introduced for breast, cervical, and bowel cancer, and diet has improved. The age profile of the population has also changed, with the population being on average more elderly in 2008.

4.

Most common cancers by age group - Males West Midlands, males aged 0-14 years Incidence

Cancer site Leukaemia Brain Non-Hodgkin's lymphoma Bone and connective tissue Eye Head & Neck Adrenal glands Liver & bile ducts Colorectal Kidney Others

36% 15% 12%

9% 7% 6% 3% 3% 3% 1% 3% 30

20

10

0 Number of cases (% of all cases)

Cancer site 13% 38% 0% 0% 0% 0% 13% 13% 0% 13% 13% 0

10

Fig 9: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008.

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West Midlands, males aged 15-49 years Incidence

17% 10% 9% 7% 7% 6% 5% 4% 4% 3% 29% 1,000

800

600

400

Cancer site Testicular Skin Colorectal Non-Hodgkin's lymphoma Head & Neck Leukaemia Brain Kidney Trachea, Bronchus & Lung Oesophagus Others

200 0 Number of cases (% of all cases)

Mortality 0% 5% 11% 4% 4% 7% 15% 4% 10% 7% 33% 0

200

Fig 10: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008.

West Midlands, males aged 50-69 years Incidence 28% 14% 14% 5% 5% 4% 3% 3% 3% 3% 17%

2,500

2,000

1,500

1,000

500

Cancer site Prostate Colorectal Trachea, Bronchus & Lung Head & Neck Oesophagus Non-Hodgkin's lymphoma Bladder Skin Pancreas Kidney Others

0 Number of cases (% of all cases)

Mortality 6% 11%

27% 4% 9% 3% 3% 2% 6% 2% 27%

0

500

1,000

Fig 11: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008.

West Midlands, males aged 70+ years Incidence

Cancer site Prostate Trachea, Bronchus & Lung Colorectal Bladder Stomach Non-Hodgkin's lymphoma Oesophagus Pancreas Kidney Head & Neck Others

27% 16% 15% 5% 5% 4% 4% 3% 2% 2% 17% 2,500

2,000

1,500

1,000

500

0 Number of cases (% of all cases)

Mortality 17% 23% 12% 5% 5% 3% 6% 4% 2% 2% 22% 0

500

1,000

Fig 12: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008.

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Cancer in male children is very different from cancer in adults, with only 3 of the ten most common childhood cancers appearing in the overall ten most common cancers. In male children aged under 15, leukaemia accounts for more than 1 in 3 diagnoses; blood disorders account for almost half the cancer diagnoses in this age group. In males aged 15-49, testicular cancer is the most common cancer and accounts for more than 1 in 6 cancers diagnosed. Cancer of the brain is the largest single cause of cancer mortality, accounting for 15% of deaths although it only accounts for less than 5% of diagnoses. In males aged 50 or over, the ten most common cancers were similar to those diagnosed in males of all ages, as the majority of cancers are diagnosed in patients aged over 50. Lung cancer is the biggest cause of cancer mortality, accounting for over 20% of deaths.

5.

Most common cancers by age group - females

West Midlands, females aged 0-14 years Incidence

Cancer site e u k a e m i a Non-Hodgkin's lymphoma Bon e an d connective tissue K i d n e y B r a i n E y e O v a r y S t o m a c h Tra ch ea, B ron ch u s & Lun g V a g i n a O t h e r s

34%

14% 12% 10% 8% 6% 2% 2% 2% 2% 8% 30

Mortality 50%

L

20

10

0% 0% 0% 25% 0% 0% 0% 0% 0% 25%

0 Number of cases (% of all cases)

0

10

Fig 13: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008.

West Midlands, females aged 15-49 years Incidence

45% 11% 8%

4% 4% 3% 3% 2% 2% 2% 15% 1,000

800

600

400

Cancer site Breast Cervix Skin Ovary Colorectal Uterus Thyroid Trachea, Bronchus & Lung Non-Hodgkin's lymphoma Head & Neck Others

200 0 Number of cases (% of all cases)

Mortality 29% 6% 3% 6% 8% 2% 0% 9% 2% 1% 34% 0

200

Fig14: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008.

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West Midlands, females aged 50-69 years Incidence 40% 10% 9% 8% 4% 4% 4% 2% 2% 2%

15% 2,500

2,000

1,500

1,000

500

Cancer site Breast Trachea, Bronchus & Lung Colorectal Uterus Ovary Non-Hodgkin's lymphoma Skin Kidney Head & Neck Pancreas Others

0 Number of cases (% of all cases)

Mortality 17% 22%

8% 3% 9% 2% 1% 2% 2% 5% 29% 0

500

1,000

Fig 15: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008. West Midlands, females aged 70+ years Incidence 23% 15% 13% 5% 4% 4% 4% 3% 3% 3% 24% 2,500

2,000

1,500

1,000

500

Mortality

Cancer site Breast Colorectal Trachea, Bronchus & Lung Uterus Non-Hodgkin's lymphoma Pancreas Ovary Stomach Oesophagus Bladder Others

0 Number of cases (% of all cases)

15% 11% 18% 2% 3%

6% 5% 4% 4% 3% 29% 0

500

1,000

Fig16: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008. Cancer in female children is very different from cancer in adults, with only 2 of the ten most common childhood cancers appearing in the overall ten most common cancers. In female children aged under 15, leukaemia accounts for more than 1 in 3 diagnoses; blood disorders account for almost half the diagnoses in this age group. In females aged 15-49, breast cancer is the most common cancer and accounts for almost half of all cancers diagnosed. Breast cancer is the largest single cause of cancer mortality, accounting for 29% of deaths. In females aged 50 or over, the ten most common cancers were similar to those diagnosed in females of all ages, as the majority of cancer is diagnosed in patients aged over 50. Lung cancer is the biggest cause of cancer mortality, accounting for nearly 20% of deaths.

6.

Most common cancers by socio-economic status

The population of the West Midlands is more deprived than England as a whole, so a greater number of people fall in the most deprived quintile than in the least deprived quintile. Because of this, for both males and females in the West Midlands, more cancers are diagnosed in the most deprived group than in the least deprived group. Crude rates are not higher in the most deprived group, but when their younger age profile is adjusted for, the risk of cancer in the most deprived group is higher than in the

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1,500


least deprived. Similarly, there is higher mortality due to cancer in the most deprived group compared to the least deprived group for both males and females. West Midlands, males – most deprived Incidence 21% 18%

Cancer site r o s t a t e Trachea, Bronchus & Lung C o l o r e c t a l H e a d & N e c k S t o m a c h O e s o p h a g u s N o n -H o d g kin ' s l y mp h o ma B l a d d e r P a n c r e a s M el an o ma of th e ski n O t h e r s

15% 5% 5% 5% 4% 4% 3% 2% 20% 1,500

1,200

900

Mortality 12%

P

600

300

0 Number of cases (% of all cases)

29% 11% 4% 6% 6% 3% 4% 4% 0% 21% 0

300

600

Fig 17: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008.

West Midlands, males – least deprived Incidence 33%

Cancer site o s t a t e Colorectal Tra ch ea, B ron ch u s & Lun g N o n -H o d g kin ' s l y mp h o ma M el an o ma of th e ski n B l a d d e r O e s o p h a g u s H e a d & N e c k S t o m a c h P a n c r e a s O t h e r s P

14% 9% 5% 5% 4% 3% 3% 3% 2% 40%

1,500

1,200

900

600

300

Mortality 16% 11% 16% 4% 3% 4% 7% 2% 4% 5% 26%

r

0 Number of cases (% of all cases)

0

300

600

Fig 18: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008.

West Midlands, females – most deprived Incidence

Cancer site r e a s t Trachea, Bronchus & Lung C o l o r e c t a l U t e r u s C e r v i x N o n - H o d g kin ' s l y m p h o m a O v a r y P a n c r e a s K i d n e y M el an o ma of th e ski n O t h e r s

29% 14% 11% 6% 4% 4% 3% 3% 2% 2% 23%

1,500

1,200

Mortality 15%

B

900

600

300

0

24% 11% 3% 2% 2% 5% 6% 2% 0% 30%

0

300

600

Number of cases (% of all cases)

Fig 19: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008.

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West Midlands, females â&#x20AC;&#x201C; least deprived Incidence

Cancer site e a s t Colorectal Tra ch ea, B ron ch u s & Lun g U t e r u s M el an o ma of th e ski n O v a r y N o n -H o d g kin ' s l y mp h o ma P a n c r e a s K i d n e y C e r v i x O t h e r s

36%

B

8% 8% 6% 5% 4% 4% 3% 2% 1% 25% 1,500

1,200

900

600

300

Mortality 18% 15% 15%

r

0

3% 3% 7% 2% 7% 3% 1% 27% 0

300

600

Number of cases (% of all cases)

Fig 20: All invasive cancers, excluding non-melanoma skin cancer (ICD10 C00-C97 excl. C44): ten most common cancers in 2008.

7.

Conclusions

The pattern of cancer diagnosis in the West Midlands is broadly similar to that of England. The most common cancers are breast, colorectal, prostate and lung. Socio-economic status affects the most common cancers, with lung cancer more common in the most deprived population. Age also affects the most common cancers, with blood cancers, brain cancers and sarcomas being disproportionately common in the young. The most common cancers in the West Midlands have changed over time since 1988. Analysing the data by age and socio-economic status highlights differences in the cancer profile of different sub-sectors of the West Midlands population. Commissioners must be aware of the differing cancer profiles and associated needs of these patients groups, in order to provide appropriate services for their populations. Notes 1) Data was obtained from the UKCIS; CIS_4.3b@ November 2010 refresh (1985-2008 data) 2) The â&#x20AC;&#x153;Othersâ&#x20AC;? cancer site includes all malignant cancers not otherwise identified in the ten most common cancer sites. Tim Evans, Cancer Registration Information Manager, Sally Vernon, Deputy Director, John Broggio, Cancer registration Information Officer. Gill Lawrence, Director. Author West Midlands Cancer Intelligence Unit Birmingham B15 2TT

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7

1.

Prevalence of Coronary Heart Disease in Birmingham and Solihull Cluster Introduction

Crude prevalence data for various diseases at a GP practice level are available from the Quality Outcomes Framework (QOF)1. These crude prevalence figures are useful in demonstrating which practices have recorded an unusual number of patients with disease amongst the practice population. However, not all patients with disease will have been diagnosed and recorded on GP systems. Some practices are better than others in identifying and recording patients on disease registers. The prevalence of many diseases depends on age, gender, ethnicity and deprivation, amongst other factors. What QOF prevalence figures do not show is whether prevalence may be higher or lower than expected, given the demographic profile of the practice population. For example, a practice based in a student health centre would not be expected to have a high number of patients with coronary heart disease compared with a practice serving a large nursing home. Similarly, since diabetes affects a disproportionately high number of South Asians, a practice with a large South Asian population would be expected to have more people with diabetes than a practice with a mainly white population. Using coronary heart disease (CHD) as an example, this chapter demonstrates the importance of standardising prevalence data for the local demographic breakdown.

2.

Age and gender standardised prevalence ratios

Indirectly standardised prevalence ratios (SPRs) were calculated for each practice in Birmingham and Solihull. Age and gender specific prevalence rates from the 2006 Health Survey for England (HSE)2 were used to estimate the underlying prevalence of CHD. The HSE classifies patients as having CHD if they reported having a diagnosis of angina or heart attack confirmed by a doctor. The HSE prevalence rates by age and gender were multiplied by age-gender specific practice populations to give an expected prevalence for each gender and age group. These were summed to obtain a total expected number of cases of CHD in each practice. The actual number of patients with CHD in each practice in 2009/10 from QOF were divided by the expected number (and multiplied by 100) to produce Standardised Prevalence Ratios. These can be compared with 100 to identify whether the number of patients recorded with CHD in the practice is higher or lower than expected. An SPR of 120 indicates 20% more patients with CHD than would be expected given the age and gender distribution of the practice population whilst an SPR of 80 indicates 20% fewer than expected. The SPR can be multiplied by the overall prevalence of CHD, derived from the HSE data, in order to convert from a ratio to an absolute rate.

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Figure 1: Crude prevalence of CHD in Birmingham and Solihull

Figure 2: Age and gender standardised prevalence of CHD in Birmingham and Solihull

Boundary material in these maps is crown copyright sourced from Ordnance Survey Boundary â&#x20AC;&#x201C; Line products. Prepared under license by Heart of Birmingham TPCT 2011.

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The maps in Figure 1 and Figure 2 show the crude and age/gender standardised prevalence of CHD for Birmingham and Solihull Cluster. They have been produced by assuming that the prevalence rate for each practice applies in the area immediately surrounding each practice and there is a gradient in the rates between adjacent practices. The darker areas indicate a higher prevalence of CHD. Note that the legends on the two maps represent slightly different scales in order to differentiate between areas of high and low prevalence on each map. The first map (crude prevalence) shows very low rates of CHD across most of central Birmingham, however, once adjusted for age and gender, then it can be seen from the second map (age/gender standardised) that the prevalence in this area is increased compared to other areas of the Cluster. The third map (Figure 3) shows all-age mortality from CHD in Birmingham. Where areas of high mortality do not correspond with areas of high prevalence then it may suggest more work needs to be done in identifying patients with disease in those areas.

Figure 3: Standardised Mortality Ratios for CHD in Birmingham, 2007-2010 SMR 50% higher than expected 25% higher than expected National average Low er than expected

Boundary material is crown copyright sourced from Ordnance Survey Boundary Line products. Prepared under license by Heart of Birmingham TPCT 2011.

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3.

Heart of Birmingham local data

In Heart of Birmingham Teaching PCT (HoBtPCT), primary care data is extracted by the Graphnet system from practices on a weekly basis. It is thus possible to obtain very up-to-date information on practice populations and numbers of patients on disease registers. A cardiovascular screening and disease management project has been taking place within Heart of Birmingham since 2007 with the aim of screening 90% of the population aged 40-74 for hypertension, diabetes, chronic kidney disease, and atrial fibrillation by 2012. Numbers of patients who are added to vascular registers are monitored by the PCT. It would thus be expected that HoBTPCT practices are better than the national average in identifying patients with vascular disease and ensuring they are added to disease registers. As a comparison with the age and gender-specific prevalence rates from the Health Survey for England, HoBTPCT age and gender specific prevalence rates were also used to estimate the underlying prevalence for HoB practices. Self-reported ethnicity of registered patients is collected by Heart of Birmingham. Although ethnicity is not recorded for 100% of patients, ethnicity can be imputed by using Origins3 software to match a patientâ&#x20AC;&#x;s name with a likely country of origin. The methodology has been described in Key Health Data 2009/104. Using these methods ethnicity was assigned for 85% of Heart of Birmingham patients. SPRs standardised by age, gender and ethnicity were thus calculated, using practice populations broken down by age, gender and known ethnicity. The funnel plots below (Figures 4 to 7) show Standardised Prevalence Ratios for HoB practices plotted against expected number of cases of CHD using the template for indirectly standardised rates produced by the Association of Public Health Observatories (APHO).5 Practices below the lower control limit have fewer cases than expected and practices above the upper limit have more cases than expected. Figure 4 shows SPRs calculated using Health Survey for England rates as the underlying prevalence. 16 practices are below the lower control limit, showing significantly fewer cases of CHD than expected and only two practices are above the upper control limit. This contrasts with the funnel plot in Figure 5 in which HoB local rates are used for the underlying prevalence. In this chart, there are more practices with higher than expected prevalence than practices with lower than expected prevalence. Differences in ethnicity distribution may account for those practices with high prevalence in Figure 5. When prevalences are standardised by ethnicity in addition to age and gender, as in Figure 6, then only 3 practices have a higher than expected prevalence.

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Figure 4: Funnel plot showing CHD prevalence standardised by Health Survey for England rates by age and gender

Figure 5: Funnel plot showing CHD prevalence standardised by HoB rates by age and gender

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Figure 6: Funnel plot showing CHD prevalence standardised by Health Survey for England rates by age, gender and ethnicity

Figure 7: Funnel plot showing CHD prevalence standardised by HoB rates by age, gender and ethnicity

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4.

Comparison of Heart of Birmingham prevalence with national data

There were some differences in the age and gender specific prevalence rates for CHD between the Health Survey for England and Heart of Birmingham, as seen in Figure 8. The HSE prevalences were higher than HoB figures for men of all ages and women over 75. The reason for the discrepancy may be due to the different methods of collection. CHD from the HSE was self-reported heart attack or angina diagnosed by a doctor, whereas HoB figures were patients recorded by GPs on the CHD register. Both could be liable to misclassification.

Figure 8: Comparison of age and gender specific prevalence rates for CHD

5.

Adjustment for ethnicity

An attempt was made to adjust the Standardised Prevalence Ratios for all practices in Birmingham and Solihull Cluster to take account of the differences in prevalence due to ethnicity. This was done by adjusting the age and gender specific prevalence rates using relative risks from the 2004 Health Survey for England.6 The 2004 survey included a booster sample of people from minority ethnic groups. Relative risks for males and females for Indian, Pakistani, Bangladeshi, Black and other ethnic groups were applied to the age-gender specific prevalence rates from the 2006 survey to give age/gender/ethnicity specific prevalence rates, following methodology similar to that used by APHO in calculating diabetes prevalence.7 Practice population data split by age, gender and ethnicity were derived using Hospital Episode Statistics admissions data for 2007/8 to 2008/9 to estimate the proportion of patients in each ethnic group in each practice. Since CHD affects predominantly older people, only admitted patients aged 45 and over were used to estimate the proportion of each ethnic group in the practice population. The

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age-gender specific practice populations were multiplied by the proportion in each ethnic group to estimate the number of patients by age, gender and ethnicity. Expected numbers were obtained by applying the HSE age/gender/ethnicity prevalence rates to the practice populations and SPRs were calculated as before. However, there was thought to be a problem with this method, since the Standardised Prevalence Ratios were lower compared to the SPRs adjusted for only age and gender for virtually all practices, except for those with mostly white populations. Figure 9 shows a comparison of Standardised Prevalence Ratios for CHD produced by the two methods. Figure 7 shows a funnel plot of the HoB age/gender/ethnicity standardised prevalence ratios calculated using HSE underlying rates. Many of the practices are below the lower control limit. Contrast these with SPRs calculating using HoB underlying age/gender/ethnicity prevalence (Figure 6).

Figure 9: Effect on SPRs of standardising by ethnicity risk ratios from Health Survey for England

An analysis of the differences between age-standardised risk ratios by ethnicity from the Health Survey for England and from local Heart of Birmingham data revealed higher rates amongst the local White/British population and lower rates amongst the local Pakistani and Bangladeshi population than nationally. The reason for this could be due to the high levels of deprivation affecting Heart of Birmingham, including the White/British population, resulting in higher levels of CHD than seen in the general population surveyed by the HSE. Prevalence data by ethnicity for all practices across the Cluster is needed to determine appropriate local levels of risk to apply to each ethnic group.

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6.

Discussion

We have produced figures for age and gender standardised prevalence of coronary heart disease for general practice populations across the Birmingham and Solihull Cluster. Standardisation by ethnicity is possible, but requires wider local data on the prevalence of disease by ethnicity. Models for disease prevalence estimation have been produced by APHO.8 However, some of the assumptions used in these models do not hold in populations with large BME populations. For instance the proportion of smokers is assumed to be constant across ethnic groups. However, this is not the case as some Asian groups have lower rates of smoking than Whites, particularly for women. Thus the APHO estimates are likely to be inaccurate in populations with large numbers of ethnic minorities, such as in Birmingham. We have produced maps showing gradients in prevalence of CHD across the Cluster. There are several weakness associated with mapping data in this way. One is that the maps assume prevalence levels are geographically linked to practice postcodes. This fails to allow for the fact that many patients live at some distance from the practice they are registered with. The second is that equal weight is given to practices regardless of size. Thirdly we have taken the absolute values for the prevalence ratios and failed to take account of whether they are statistically significant. However, reference to the funnel plots can show practices with significantly high or low prevalences. Despite these caveats, maps can be an appealing way of demonstrating geographical variation in prevalence and by visually comparing with maps of mortality can be a useful tool in planning provision of services.

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References 1

NHS Information Centre. www.ic.nhs.uk/qof

2

Craig, R and Mindell, J (2008) Health Survey for England 2006. Cardiovascular disease and risk factors in adults. The Information Centre: London. 3

http://publicsector.experian.co.uk/Products/Mosaic%20Origins.aspx

4

Key Health Data 2009/10. Chapter 11: Prevalence of Vascular Disease and Related Conditions amongst various Cultural (Ethnic) Groups in Birmingham, UK. http://medweb4.bham.ac.uk/websites/key%5Fhealth%5Fdata/2009/index.htm 5

http://www.apho.org.uk/default.aspx?RID=39403

6

Sproston, K and Mindell, J (2006) Health Survey for England 2006. The health of minority ethnic groups. The Information Centre: London. 7

http://www.yhpho.org.uk/default.aspx?RID=81090

8

http://www.apho.org.uk/resource/view.aspx?RID=48308

Amanda Lambert, Head of Healthcare Information, Birmingham Public Health, Birmingham, B16 9PA Authors Felix Burden, Clinical Director, Heart of Birmingham Teaching Primary Care Trust, Birmingham, B16 9PA.

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8 1.

Abortion: trends in the last decade

Introduction

Medical termination of pregnancy became legal on 27th April 1968 when the Abortion Act of 1967 came into effect. The 1967 Act has since been amended by the Human Fertilisation and Embryology Act 1990, but in essence, a pregnancy can be terminated under certain circumstances provided certain prescribed legal requirements are fulfilled. Only a registered doctor can carry out a procedure to cause an abortion and he of she has, by law to notify the Chief Medical Officer and provide all the data required using a prescribed form (HSA4). Two registered doctors have to certify the justification for the abortion according to criteria laid down in law. The details on each woman having a legal abortion provide a wealth of information that can shed light on the reproductive and sexual health of the population. The data are held by the Department of Health and a large amount of aggregated statistical information is published and made available in the public domain (http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/PublicationsStatistics/DH_126769)

In this chapter we present a few summary statistics from this source.

2.

Trends in the number and rate of abortions

20.0

200

16.0 150

14.0 12.0 10.0

100

8.0 6.0 50

4.0 2.0

years 1969 to 2010

0 69

75

80

85

90

95

2000

0.0 5

10

44

18.0

rate per 1000 women aged 15-

Thousands

Omitting 1968, for which we have less than a full years data since the Act became operational in April of that year, the trend over the last 42 years is shown in Fig 1.

Figure 1. Trends in number of abortions in residents (red line, left hand axis), total abortions involving residents and visitors (blue line, left hand axis) and the age standardised rate (green line, right hand axis). These figures are for England and Wales. In 2010 in the West Midlands region there were 20,331 abortions carried out, with an age standardised rate of 19.3 per 1000. Source: Department of Health.

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Thousands

250

200

35 and over 30-34

150

25-29 100

20-24 50

0 2000

18-19 Under 18 01

02

03

04

05

06

07

08

09

2010

Figure 2. The age distribution of women having an abortion has remained largely unchanged over the last decade. 120

100

Percentage

13-19 weeks 80

10-12 weeks

60

3-9 weeks

40

20

0 2000

01

02

03

04

05

06

07

08

09

2010

Figure 3. Gestational age at which abortions were performed, trend over the last decade. The proportion of abortions being done at 10 weeks of gestation or greater is now almost half what it used to be a decade ago. In 2010 in the West Midlands region, 80% of all abortions were done at less than 10 weeks of gestation, 12% between 10 and 12 weeks, and 8% at 13 weeks and over. There is some variation across the 17 Primary care trusts (72% in Herefordshire - where unusually 75% of abortions are done in an NHS facility - to 85% in North Staffordshire PCT)

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3.

Trends in age distribution

Over the last decade there has been little change in the relative age profile of women having an abortion (Fig 2). Contrary to popular perception it is not teenagers who account for the largest number of cases.

4.

Gestation

Abortions are safest when carried out in early gestation. It is considered good practice to perform an abortion, when it is necessary to do one, at earlier than 10 weeks of gestation. More than 3 in 4 abortions now meet this standard (Fig 3).

5.

Methods used for abortions

There are two broad groups of methods used for carrying out the abortion. Surgical methods include vacuum aspiration (used in 52% of all abortions in 2010), surgical dilation and evacuation (used in 5% of all cases) and the seldom used method of feticide with surgical evacuation (used mainly in late gestation abortions) Medical means were used in 43% of all abortions in 2010. In almost all cases the method used was an antiprogesterone drug with or without a prostaglandin. Feticide with a medical evacuation is seldom used and then only in late gestation abortions. However there were considerable differences in the proportion of cases where a medical, as opposed to a surgical technique, was used according to the gestational age of the pregnancy. This is shown in Fig 4.

120

Medical methods

Surgical Methods

100 14

80

24

24

76

76

13 - 14

15 - 19

33

51

60 86

40 20

67

49

0

3-9

10 - 12

20 & over

Fig 4. Percentage of abortions in each gestational age category where medical or surgical method was used in 2010. Medical means were used in a just over half of cases in early gestation abortions. Overall, medical methods were used in 43% of cases.

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60

50

40

30

20

10 Parity 1+

Prev miscarriage

Prev abortion under Act

0 2000

01

02

03

04

05

06

07

08

09

2010

Fig 5. Trends in the proportions of repeat abortions. The blue line tracks the %age of abortions in parous women (i.e. who have had 1 or more previous pregnancies that went beyond 24 weeks); the middle green line tracks the %age of abortions in women who have had a previous pregnancy terminated under the Act; the bottom red line tracks the %age of women who had a previous pregnancy end in a spontaneous abortion or was an ectopic pregnancy (data not published for 2000 and 2001).

Birmingham East and North Solihull Coventry Teaching Dudley South Birmingham Wolverhampton City Sandwell Walsall Teaching Warwickshire South Staffordshire Telford and Wrekin Stoke on Trent Shropshire County Worcestershire North Staffordshire Herefordshire

0

5

10

15

20

25

30

35

Fig 6. Proportion (%) of abortions in women under 25 who have had a previous abortion under the Act. There is almost a 2 fold variation between the lowest and the highest rate PCT.

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Coventry Teaching Birmingham East and North Sandwell Dudley Telford and Wrekin Walsall Teaching Wolverhampton City Stoke on Trent South Birmingham South Staffordshire North Staffordshire Warwickshire Heart of Birmingham Teaching Herefordshire Shropshire County Worcestershire Solihull

0

5 10 15 20 25 Abortion rate per 1000 women under 18

30

Fig 7. Under 18 abortion rate. This is a crude rate that has not been standardised for age. There is a 2 fold variation between the lowest rate PCT and the highest. The West Midlands rate is 18 per 1000 and the England and Wales rate is 16.5 per 1000.

6.

Chlamydia screening

Abortion services present an obvious opportunity for sexual health promotion. Since 2002 data has been published on the proportion of women who have been offered Chlamydia screening. This figure has gone up from 65% on 2002 to 84% in 2010. Figures are not published by PCT

7.

Geographic variation within West Midlands PCTs.

The Dept of health also publishes limited statistics on abortions by Primary Care Trust. These figures show considerable variation among PCTs in the region both for the proportion of abortions that are carried out in women under 25 where there has been a previous abortion under the Act (Fig 6) and for the abortion rate per 1000 women under 18 (Fig 7)

8.

Trends in abortions in women with previous pregnancy experience

There has been little change in the trend over the last 10 years in the proportion of abortions in women with previous obstetric experience (Fig 5). The data set records whether a woman undergoing an abortion has had 1 or more previous pregnancies that a) went beyond 24 weeks and resulted in a live birth or stillbirth; b) ended in a spontaneous abortion; and c) was aborted under the Act. Since each case can have 1 or more previous pregnancies the categories are not mutually exclusive. All three rates show a slight increase over the decade 2000 to 2010.

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No.

% of total abortions

Multiparity

94320

49.7

1 or more previous spontaneous abortion or ectopic pregnancy

29772

15.7

I or more previous abortions under the Act

64303

33.9

Previous obstetric experience

Table 1. Previous obstetric experience of women having abortions under the Act in 2010. Note: the categories are not mutually exclusive, and cannot be added up.

9.

Commentary

Since the late 60s when liberal social policy led to the legalisation of abortion, there has been a steady rise in the number of women choosing abortion to control fertility. The debate around abortions policy (pro choice vs. pro life) has continued throughout this period and across many countries. When the policy was changed in 1967 the argument in favour of legalisation was won not on the basis that abortion was desirable but on the basis that the alternative â&#x20AC;&#x201C; back street abortion â&#x20AC;&#x201C; was both dangerously unsafe and not amenable to eradication by prohibitory legislation. Medical termination of pregnancy cannot be an easy decision for any woman; there is a large body of evidence of variable quality suggestive of adverse consequences of abortion on womenâ&#x20AC;&#x;s psychological well-being. Nevertheless there can be no question that a liberal society must offer women a range of options, including abortion, to control fertility. The last few decades has also been a time of increasingly liberal attitudes towards contraception coupled with wide availability of contraceptive services. From a public health perspective the question that arises is why abortions have not declined over time. Why do so many women fail to choose the safer, cheaper and more widely available upstream preventative option of contraception as a means of avoiding unplanned pregnancy rather than resorting to abortion as a means of avoiding unplanned childbirth? Are women making an irrational choice? On the face of it one could argue the case that contraception is the only rational choice. Given that it is widely and freely available, it is also the easy choice. However women also face a trade-off between continuous use of a contraceptive method to avoid the relatively small risk of pregnancy on the one hand, and the option of relying on a safe and effective means of dealing specifically with an unwanted pregnancy after that risk has crystallised. It is likely that, for some women at least, the widespread availability of early gestation abortion using medical means has proved a disincentive to practicing contraception.

Jammi N Rao, Consultant in Public Health Medicine, Sadia Janjua, Research Reviewer and Analyst Authors West Midlands Commissioning Support Unit, University of Birmingham, B15 2TT

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9 1.

HIV infection and AIDS in the West Midlands

Introduction

Acquired Immunodeficiency Syndrome (AIDS) was first described as a distinct disease in 19811 and subsequently in 1984, the scientific and medical community identified AIDS as an outcome of advanced infection with the Human Immunodeficiency Virus (HIV)2. Over the past 30 years, considerable progress has been made in our understanding of the natural history of HIV/AIDS and in the development of diagnostic tests and effective agents for postexposure prophylaxis and treatment. As a result, what was once a fatal condition has now become a manageable chronic infection for those diagnosed and treated in the early stages of HIV infection. Despite these improvements in the detection and treatment of HIV, many people living with HIV in the United Kingdom remain undiagnosed and a large proportion of individuals are diagnosed at a late stage of infection, resulting in poorer outcomes. This chapter describes the epidemiology of HIV/AIDS in the West Midlands from 1982 to 2009 including trends in HIV-related outcomes with some emphasis on key risk groups and settings. It is hoped that this report will stimulate some debate, encourage active collaboration and the implementation of effective control measures. Data for this report was obtained from a variety of sources. Data on new HIV diagnoses in the West Midlands are from the West Midlands Regional HIV Surveillance Project, which utilises data provided by diagnosing hospitals and the NHS laboratories in the West Midlands. Prevalence data and information on patients accessing HIV care is provided by the Survey of Prevalent HIV Infections Diagnosed (SOPHID), a cross-sectional survey of all persons who attend for HIV-related care at an NHS site in England, Wales and Northern Ireland within a calendar year. Data on HIV testing are sourced from the Health Protection Agencyâ&#x20AC;&#x;s Unlinked Anonymous Prevalence Monitoring Programme (UAPMP) which monitors the prevalence of HIV infection amongst GUM clinic attendees, pregnant women and injecting drug users.

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2.

Global context

Fig 1: Number of people newly infected with HIV in the world, 1990-2009; Source: UNAIDS/WHO

HIV infection and AIDS are important global health problems. Worldwide, more than 60 million people have been infected with HIV since the pandemic began and it was estimated that there are about 33.3 million people living with HIV in the world in 2009, with approximately 2.5 million people diagnosed every year3,4. However, the annual number of new HIV infections has steadily declined since 2000 and the number of people living with HIV in the world has now stabilised (see figure 1), probably due to the impact of HIV prevention efforts and the natural course of HIV epidemics3,4. The HIV pandemic has mainly affected the sub-Saharan region of the Africa continent, this region accounts for 70% of all new infections and 67% of all those living with HIV4 (this is shown on figure 2 alongside other regions of the world that are most affected by the HIV pandemic). As a result, AIDS is the leading cause of death in sub-Saharan Africa, and the fourth leading cause of death globally3. Globally, the number of people who have died from AIDS is estimated to be around 30 million since the start of the pandemic3. An estimated 1.8 million AIDS-related deaths were reported in 2009, lower than the 2.1 million reported in 20043,4. This may be due to the significant increase in people receiving treatment i.e. antiretroviral therapy. The global initiative to address the HIV/AIDS pandemic is led by the World Health Organisation through collaboration with various governmental and non-governmental agencies. These initiatives are driven by the Millennium Development Goal (MDG)6 that aims to halt the spread of HIV/AIDS by 2015, one of the eight international development goals that 189 countries (including the United Kingdom) agreed to achieve.

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Fig 2: Global prevalence of HIV infection, 2009; Source: UNAIDS / WHO

3.

National context5,7

The United Kingdom (UK) accounts for about 0.26% (n=86,500) of the total number of people living with HIV in the world in 2009. This is estimated to be equivalent to a crude rate of 140 people per 100,000 of the UK population. The annual crude rate of newly diagnosed HIV in the UK increased steadily from the late 1990s peaking in 2005 at 14 per 100,000 (n = 7,982). Since 2006, the rate has decreased year on year to its current rate of 11 per 100,000 (n= 6,630) observed in 2009 (see figure 3). The observed decrease is largely as a result of fewer diagnoses amongst those who heterosexually acquired the infection abroad (mainly in sub Sahara Africa). Although the rate of new HIV infection in 2009 indicates a recent decrease, the rate is double that observed in the late 1990s. The annual crude rate of AIDS and deaths related to HIV infection in the UK has declined from its peak in 1995 and has remained stable since 2000 (from 3 per 100,000 in the 1995 to about 1 per 100,000 in 2009 (see figure 3). This is largely due to increased access to HIV treatment and care. In 2009, 547 people were diagnosed with AIDS and 516 people infected with HIV died. The majority (73%) of those who died had presented late for HIV treatment and care.

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Fig 3: New HIV and AIDS diagnosis and death rates in the UK by year of diagnosis or death, 19952009; Source: HPA, New HIV Diagnoses National Tables

4.

Regional context

Fig 4: New HIV and AIDS diagnosis and death rates in the West Midlands by year of diagnosis or death, 1984-2009; Source: HPA, West Midlands Regional HIV Surveillance Project

A cumulative total of 5382 new diagnoses of HIV were reported in the West Midlands during the period from 1982 to 2009. These represent 4.9% of all new HIV diagnoses reported in the UK and 5.3% of all diagnoses reported in England over this time period. Of the 5382 new diagnoses in the West Midlands, 17% (n= 916) went on to be diagnosed with AIDS and 14% (n=734) were known to have died (other case that have died may have been lost to follow up).

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The annual rate of newly diagnosed HIV in the West Midlands is consistent (but with lower rates) with the trend observed in the UK, with observed rates of about 8 per 100,000 (n= 424) newly diagnosed HIV in 2009, following a peak of about 10 per 100,000 (n=531) in 2006 (see figure 4). Again, the observed decrease is largely as a result of fewer diagnoses amongst those who heterosexually acquired the infection abroad. Note that the spike observed in 1985 was as a result of the development of a HIV test in 1984 and the increased diagnosis amongst men who have sex with men and those who acquired infection through blood products (see figure 4 and 18). The annual rate of AIDS diagnosis and HIV-related deaths in the West Midlands has fluctuated around 1 per 100,000 of the population over the period 1984 to 2009 (see figure 4).

5.

Age

Fig 5: New HIV diagnosis rates in the West Midlands by year of diagnosis and age at diagnosis, 1984-2009; Source: HPA, West Midlands Regional HIV Surveillance Project

The majority of newly diagnosed cases of HIV infection reported in the United Kingdom are in those aged fifteen (15) years or above, with individuals between twenty-five to thirty-four (25-34) most affected. In the West Midlands the highest diagnosis rates have been also been observed in the 25-34 year old age group. Rates in this group have increased steadily from 1999, peaking in 2006 at 35 diagnoses per 100,000 (n=131) but have since fallen to 22 per 100,000 (n=233) in 2009. Diagnosis rates are also high in 35-49 year olds and have seen a four-fold increase from 1999 to 2009. Although the lowest new diagnosis rates in adults are observed in those aged 50 and over, rates in this group have trebled over the same period (see figure 5).

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6.

Gender

Fig 6: New HIV diagnosis rates in the West Midlands by year of diagnosis and gender, 1984-2009; Source: HPA, West Midlands Regional HIV Surveillance Project

Males account for the majority (63%) of all newly diagnosed HIV infections in the West Midlands, similar to that observed in the UK (male accounted for 69% of all newly diagnosed HIV infection in the UK). HIV diagnoses have always been higher amongst the male population since 1984, except for the period 2001-2004 when there was no significant difference between males and females (see figure 6). The higher rate in males may be driven by increased transmission amongst men who have sex with men (MSM).

7.

Ethnicity

The ethnic distribution of newly diagnosed HIV infections in the West Midlands between the periods 1982 to 2009 showed that the highest proportion were in the White ethnic group (43%) followed by the Black African ethnic group (41%). However, the cumulative and annual rates of newly diagnosed HIV infection are higher amongst the Black Africans, more than a 100 times the rate amongst the White ethnic group, as shown in Figure 8 and 9.

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Fig 7: New HIV diagnoses in the West Midlands by year of diagnosis and ethnic group, 1984-2009 (Black African and White ethnic groups); Source: HPA, West Midlands Regional HIV Surveillance Project

Fig 8: New HIV diagnosis rates in the West Midlands by year of diagnosis and ethnic group, 20022009 (Black ethnic groups); Source: HPA, West Midlands Regional HIV Surveillance Project

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Fig 9: New HIV diagnosis rates in the West Midlands by year of diagnosis and ethnic group, 20022009 (Black Caribbean, Other/Mixed and the White ethnic group); Source: HPA, West Midlands Regional HIV Surveillance Project

However, the annual rate of newly diagnosed HIV infection in the West Midlands amongst the Black African ethnic group has decreased considerably, from about 1400 per 100,000 in 2002 to about 400 per 100,000 in 2009 (as shown in figure 8), largely as a result of a fall in diagnoses amongst those who heterosexually acquired the infection in Africa. The annual rate of newly diagnosed HIV infection amongst the white ethnic group has remained largely stable (with some random variation) at below 5 per 100,000 from 2002 to 2009 (see figure 9). However, actual numbers of diagnoses in the white population have seen an overall increase over the same time period (Figure 7).

8.

Incidence by West Midlands Primary Care Trust (PCT)

All the PCTs in the West Midlands have reported cases of newly diagnosed HIV over the period 1982 to 2009, some disproportionately more than others. Heart of Birmingham Teaching PCT had the highest new HIV diagnosis rates in 2009 (23 per 100,000) followed by Coventry Teaching and Wolverhampton City PCTs (18 and 17 diagnoses per 100,000 respectively) (see Figure 10). Figures 12 to 16 show how diagnosis rates across the 17 PCTs in the region have changed from 2001 to 2009.

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Š Crown copyright and database right 2010. All rights reserved. Ordnance Survey Licence number 100016969/100022432 #Mid-2008 population estimates for PCT used as denominator (Source: ONS, Population Estimates Unit)

Fig 10: New HIV diagnoses rates in the West Midlands by Primary Care Trust of residence (cases diagnosed in 2009); Source: HPA, West Midlands Regional HIV Surveillance Project

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Fig 11: New HIV Diagnoses Rates in the West Midlands by PCTs in the Arden PCT Cluster, 20012009; Source: HPA, West Midlands Regional HIV Surveillance Project

Fig 12: New HIV Diagnoses Rates in the West Midlands by PCTs in the Birmingham and Solihull PCT Cluster, 2001-2009; Source: HPA, West Midlands Regional HIV Surveillance Project

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Fig 13: New HIV Diagnoses Rates in the West Midlands by PCTs in the Black Country PCT Cluster, 2001-2009; Source: HPA, West Midlands Regional HIV Surveillance Project

Fig 14: New HIV Diagnoses Rates in the West Midlands by PCTs in the Staffordshire PCT Cluster, 2001-2009; Source: HPA, West Midlands Regional HIV Surveillance Project

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Fig 15: New HIV Diagnoses in the West Midlands by PCTs of West Mercia PCT Cluster, 2001-2009; Source: HPA, West Midlands Regional HIV Surveillance Project

9.

Probable exposure category

The majority of newly diagnosed HIV infections in the West Midlands reported between 1982 and 2009 were probably acquired through sexual contact and 55% (n=2978) were acquired through heterosexual contact. The annual rate of infections acquired through heterosexual contact rose steadily from less than 1 per 100,000 population in 1996 to a peak level of 8 per 100,000 in 2004 and is now on a downward trend (about 4 per 100,000 in 2009), as shown in figure 16. This fall is largely due to a decrease in the number of infections acquired in Africa, which may be a consequence of progress made in Africa in reducing HIV infection. While infection acquired abroad has been decreasing, the number of new diagnoses of HIV infection acquired in the UK has been steadily increasing since 1998 possibly as a result of increasing high-risk sexual behaviour in the UK (see figure 17). Cases acquired through sex between men also represent a large proportion of new diagnoses in the West Midlands, 35% (n=1857) of all cases reported from 1982 to 2009. The rate of HIV diagnosed amongst men who have sex with men (MSM) has increased since 2001; we now know that almost every four in five newly diagnosed HIV infections in MSM are acquired within the UK7. Disappointingly, current rates are triple those observed in the early 1980s when HIV infection was mainly associated with MSM5 (see figure 16). Although rates now appear to be on a downward trend it should be noted that there has been an increase in the number of cases for which route of transmission is unknown. Nationally, when data are corrected for this, the estimated number of new diagnoses in MSM is increasing and a similar situation may exist in the West Midlands.

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Fig 16: New HIV diagnosis rates in the West Midlands by year of diagnosis and probable exposure category, 1984-2009; Source: HPA, West Midlands Regional HIV Surveillance Project

Fig 17: New HIV diagnoses in the West Midlands acquired through heterosexual contact by world region of infection, 1984-2009; Source: HPA, West Midlands Regional HIV Surveillance Project

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10.

Other routes

Despite advances in prevention and treatment of HIV infection, especially amongst pregnant women, we still observe a small number of cases of mother to child transmission in the West Midlands. There were 108 cases of mother to child transmission reported in the West Midlands between 1988 and 2009; these represent 2% of all cases reported in that period. Thirteen (13) cases of mother to child transmission of HIV were reported in 2009, the highest since 2006 (n=11). There is a need to ensure there are confidential investigations to ascertain and address the cause of these failures. New diagnoses amongst injecting drug users are relatively low representing 2% (n=108) of all cases reported to the West Midlands between 1982 and 2009. There were four (4) cases reported in 2009, a slight drop compared to 2008 (n = 6). Prevention through needle exchange programmes remains an important measure in preventing transmission amongst injecting drug users. Transmission through blood or blood products is now very rare, with only one (1) case reported between the period 2007 and 2009. There were a hundred and fifty one (151) cases of new HIV diagnoses probably acquired through blood or blood products reported to the West Midlands between 1982 and 2009; these represent 2.8% of all new HIV diagnoses reported. The majority (64%) of these were diagnosed in 1985, just after the HIV test was developed.

11.

HIV testing and undiagnosed infection

There is a national recommendation of universal testing for all attendees of GUM or sexual health clinics, antenatal services, termination of pregnancy services, drug dependency programmes, healthcare services for those diagnosed with tuberculosis, hepatitis B, hepatitis C and lymphoma6..Hence the majority of HIV testing takes place in the Genitourinary Medicine (GUM) clinics, during antenatal screening and amongst injecting drug user services. The Unlinked Anonymous Prevalence Monitoring Programme (UAPMP) provides information on testing uptake in these settings in addition to data on HIV prevalence in these selected adult populations (pregnant women, injecting drug users and genitourinary medicine clinic attendees). Two GUM clinics in the West Midlands participate in the UAPMP survey of GUM clinic attendees. Data from these clinics suggest that there has been an increase in uptake of HIV testing over the period 1999 to 2008. Of the 98,700 people in the West Midlands that attended the participating GUM clinics in the West Midlands between 1999 and 2008 while unaware of their HIV status, only 70% received a HIV test. Of the 563 anonymous samples (of those who did not receive HIV test between 1999 and 2008) that were tested, 34% were positive for HIV infection (see table 1). We now know that in 2009, approximately a quarter of HIV-infected people in the UK were unaware of their infection and it appears there has been no decline in the prevalence of undiagnosed infection over the period 2001 to 20087.

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Table 1: Survey of Genitourinary Medicine Clinic Attendees receiving an HIV test and previously undiagnosed HIV positive attendees remaining undiagnosed, West Midlands (1999-2008) Source: HPA,UAPMP Survey of GUM Clinic Attendees

Data from antenatal screening indicates that over the same period i.e. 1999-2008, of the 548,931 women screened as part of the UAPMP survey, 0.1% (n=546) tested positive and 0.05% (n=255) of those tested were diagnosed during pregnancy. The percentage of women accepting HIV testing as part of the antenatal screening in the UK has remained high and was about 95% in 20097. The uptake of HIV testing in specialist Injecting Drug User services appears to be improving. The percentage uptake in 2009 was 74%, much higher than 53% observed in 1998 and the prevalence rate of HIV positivesâ&#x20AC;&#x; remains relatively stable (annual percentage prevalence is below 2% between 1990 and 2009). See Table 2.

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Year

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 1.0% 0.3% 0% 0% 0% 1.4% 0% 0.4% 0.4% 0% 2 1 0 0 0 2 Number of samples anti-HIV positive 0 1 1 0 209 387 213 179 113 145 Total number of samples collected 119 235 231 315 1 59% 44% 48% 53% 57% 55% 50% 64% 66% 68% HIV VCT Uptake 119 168 98 90 63 78 Number reporting a VCT for HIV 56 145 147 211 201 379 206 170 111 141 Total number of answering question 111 225 224 309 Anti-HIV Prevalence

2

Level of direct sharing Number of reporting direct sharing

20%

34%

35%

30%

32%

32%

21%

18%

13%

19

101

47

23

41

26

24

31

21

32

Total number of answering question

95

296

135

77

128

82

114

168

157

194

Level of sharing (direct & indirect)3 Number of reporting sharing

69%

69%

57%

61%

51%

47%

41%

31%

32%

202

94

44

78

42

54

71

49

63

Total number of answering question

294

137

77

128

82

115

173

157

194

15% 7

19% 25

13% 9

28% 12

15% 8

14% 5

15% 7

22% 17

17% 11

24% 21

47

129

70

43

53

36

48

76

64

89

Proportion always using a condom Number always using a condom

4

Total number of answering question

16%

Table 2: Survey of Injecting Drug users. Source: HPA,UAPMP Survey of Injecting Drug Users in contact with specialist services 1. VCT = Voluntary Confidential Test 2. Sharing of needles and syringes among those who had last injected during the four weeks preceding participation in the survey. Sharing of needles and syringes, mixing containers, filters or the water used to prepare drugs among those who had last injected during the four weeks preceding participation in the survey. Condom use among those reporting with more than one sexual partner in the preceding 12 months

In the West Midlands, two PCTs, Heart of Birmingham and Coventry, had a prevalence of diagnosed HIV greater than 2 per 1000 of their 15-59 year old population in 2009 (see figure 12). This is the recommended threshold at which expanded HIV testing should be implemented and ideally these PCTs should have programs in place to test for HIV in all adults registering in general practices and in all general medical admissions6.

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Fig 18: Prevalence of diagnosed HIV infection in the West Midlands by Primary Care Trust of Residence (2009); Source: HPA, Survey of Prevalent HIV Infections Diagnosed (SOPHID)

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12.

Late Diagnosis

Timely diagnosis and prompt institution of effective treatment have been shown to improve outcomes in HIV infected individuals7. People diagnosed with HIV at a late stage (i.e. those with immunity cells (CD4) count less than 350 cells/mm3) tend to have poorer outcomes with treatment5,6.. Those who are not infected with HIV will normally have these immunity cells (i.e. CD4) count of between 500 and 1200 cells/mm3. In the West Midlands, over the period 1982 to 2009, only 31% (n=1671) of the 5382 cases of HIV reported had a record of an early CD4 count (i.e. CD4 count within 3 months of diagnosis). Of these, 55% (916/1671) were diagnosed at a late stage (see table 3). In 2009, only 61% (n=257) of the 424 cases of HIV reported had a record of an early CD4 count. Of these 257, 56% (n=143) were diagnosed at a late stage (see table 3). Most of the late diagnoses were amongst residents of Heart of Birmingham, Wolverhampton and Coventry PCTs (see table 3).

Table 3: New HIV Diagnoses in the West Midlands, Primary Care Trust of Residence by Earliest Reported CD4 Cell Count (Cumulative Cases 1982-2009); Source: HPA, West Midlands Regional HIV Surveillance Project

13.

Access to HIV care

In 2009, 4141 West Kingdom, an increase of Midlands residents diagnosed with HIV infection were seen for HIV treatment or care at NHS sites in the United 11% compared to 2008 and 63% compared to 2005, see Table 4. Heart of Birmingham Teaching PCT had the most residents accessing care in 2009 (614 residents), followed by Coventry PCT (554 residents), see Table 4.

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Between 2000 and 2009, there has been a year on year increase in access to HIV-related care in all age groups, with the majority (53% in 2009) of those accessing HIV-related care aged 35-49 years old. Overall there has been a five-fold increase in patients accessing care between 2000 to 2009, with the largest increases seen in the under 15 (ten-fold) and 24-34 (seven-fold) age groups. There was a six-fold increase in those aged 50 or over.

Table 4: Access to HIV Care by Primary Care Trust of Residence by Year of Survey, 2005-2009; Source: HPA, Survey of Prevalent HIV Infections Diagnosed (SOPHID)

14.

Conclusion

HIV infection and AIDS are global health problems which mainly affects the sub-Sahara African region. In 2009, the United Kingdom accounted for 0.25% of the global burden of prevalent HIV infection. The majority (92.5%) of all new diagnoses of HIV infection in the United Kingdom between 1982 and 2009 were in England. Of these, 5.3% were in the West Midlands. The demographic distribution of newly diagnosed HIV infection in the West Midlands is broadly similar to that observed in England and the United Kingdom. The majority of cases of HIV infection in the West Midlands are in those aged 25-49 years and the Black African ethnic group. Although new diagnosis of HIV infection is decreasing amongst those aged 25-34, it is increasing amongst 35-49 year olds in the West Midlands. This may indicate increasing high-risk sexual behaviour in this age group. Most of those diagnosed with HIV infection in the West Midlands acquired the infection through unprotected heterosexual contact abroad (mainly in sub-Sahara Africa) but HIV infection through this route (i.e. acquisition abroad) has been declining steadily for some years. However, there is an increasing rate of HIV infections that are acquired within the United Kingdom; a high proportion of these are amongst men who have sex with men. This increasing trend may be as a result of increasing high risk sexual behaviour in the West Midlands and thus there is a need to re-double sexual health promotion in the region, especially amongst high risk groups.

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The most affected areas of the West Midlands are Birmingham, Coventry and the Black Country. Heart of Birmingham, Coventry, South Birmingham, Birmingham East and North, Wolverhampton and Sandwell PCTs have the highest number of newly diagnosed HIV infection, with annual rates of newly diagnosed HIV infection above the average for the West Midlands between the periods 2001 to 2009. There is the need to re-double HIV prevention efforts in these PCTs. In 2009 two PCTs in the region, Heart of Birmingham and Coventry, had a prevalence of diagnosed HIV greater than 2 per 1000 population aged 15-59. This is the threshold at which expanded HIV testing (in medical admissions and primary care registrations) in adults is recommended. Data from the Health Protection Agencyâ&#x20AC;&#x;s Unlinked Anonymous Prevalence Monitoring Programme suggest that there has been an increase in the percentage of those offered and tested for HIV infection in the West Midlands, especially in the GUM and Intravenous Drug User (IDU) service. However, the uptake rate is not as high as those observed in the antenatal screening programme. Most of those who were diagnosed with AIDS and most of those who died as a result of HIV-related infection in the United Kingdom had presented late for diagnosis, treatment and care. Although the number of those diagnosed with HIV infection in the West Midlands that are accessing treatment and care is improving, there is the need for stakeholders to encourage those who may be at risk of HIV infection to seek testing as early diagnosis benefits both the individual (who can expect to live a normal life span following early presentation for treatment) and the community (as transmission within the community can be minimized).

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References 1 Hawker J., Begg N., Blair I., Reintjes R. and, Weinberg J. (2005) Communicable Disease Control Handbook. 2nd ed., Oxford: Blackwell Publishing. 2

Gallo R.C. and Montagnier L. (2003) The discovery of HIV as the cause of AIDS. N Engl J Med. 349(24):pp.2283–2285 3

USAID (2010) HIV/AIDS: Frequently Asked Questions [online]. USAID [cited 11th July 2011] Available on <http://www.usaid.gov/our_work/global_health/aids/News/aidsfaq.html> 4

WHO (2011) HIV/AIDS: Global Observatory Report available [online]. WHO [cited 11th July 2011] Available on <http://www.who.int/gho/hiv/en/index.html> 5

HPA (2011) Infectious Diseases-HIV. 30 years on: people living with HIV in the UK about to reach 100,000. HPA. [cited 11th July 2011]. Available at <http://www.hpa.org.uk/Topics/InfectiousDiseases/InfectionsAZ/HIV/> 6

HPA (2011) Time to test for HIV: Expanded healthcare and community HIV testing in England. HPA. [cited 11th July 2011]. Available at <http://www.hpa.org.uk/web/HPAwebFile/HPAweb_C/1287145497243> 7

HPA (2011) HIV in the United Kingdom: 2010 Report. HPA. [cited 11th July 2011]. Available at <http://www.hpa.org.uk/web/HPAwebFile/HPAweb_C/1287145367237>

Authors

Victor Aiyedun, Specialist Registrar in Public Health Medicine; Helen Bagnall, Epidemiological Scientist; Obaghe Edeghere, Locum Consultant Regional Epidemiologist; Kate Martin, Information Scientist (HIV and STI Surveillance); Yasmin Rehman, Epidemiological Scientist. Health Protection Agency – West Midlands, 5 St Philips Place, Birmingham B3 2PW

Acknowledgement

All those who contribute data to the West Midlands Regional HIV Surveillance Project and SOPHID survey (from GUM clinics, HIV treatment centres and NHS laboratories across the region). HPA Centre for Infections (New HIV Diagnoses National Tables, SOPHID, Unlinked Anonymous Prevalence Monitoring Programme).

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Spatial planning decisions and obesity 1.

Introduction

Obesity is major public health problem; there is no question but that the prevalence is rising. The role of the environment in which people live, the access they have or do not have to high quality food and the opportunity and incentives to be active is captures in the phrase „obesogenic environment‟. There has been recent political interest in planning policy around hot food takeaways and various policies options have been proposed, and some have been implemented in parts of the country. This chapter takes a look at Birmingham‟s approach to date in terms of further integration with local spatial planning to move towards the delivery of a health promoting environment. We also consider how this can be taken forward in the future. We have used this as an illustration of potential options for the city but it is important to recognise that a multi-faceted approach is likely to be most effective.

2.

Background

Obesity (or severely unhealthy excess body weight) is caused by an imbalance in „energy in‟ and „energy out‟, the difference between what we consume through eating and what is used by the body. While this is governed by an individual‟s biology and behaviour, external factors such as social and environmental factors also have an influence. While the determinants of obesity are very complex and inter-related, the causes can be grouped into four main areas: human biology, culture, behaviour, and the food/physical environment. Medical evidence demonstrates that excess fat in the body makes a significant contribution to the likelihood of contracting preventable illnesses such as heart disease, cancer, Type II diabetes, liver disease and hypertension (high blood pressure). These illnesses can be life threatening, and affect the quality of life and ability to make a full contribution to society. Increasing amounts of International and UK research literature clearly demonstrates a role for local environmental determinants, including access to amenities. Since the production of the Governments Foresight report on Obesity1, the Marmot Review on Health Inequalities2, and the Public Health White Paper3, it is recognised that individual changes are insufficient to change trends in the UK that are having a detrimental impact upon the lives of our population. A significant body of evidence and practice on planning strategy, policy and practice as a tool for better health has emerged within this area. There is clear evidence that a multi-faceted approach to public health and planning, including education, individual measures and appropriate policy steps, can bring changes to health inequalities and its associated healthcare costs. Birmingham has significant assets, both in green space and development and also risks, including the increasing number of hot food takeaways (class A5). Other local authorities have already made

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successful changes to local legislation that impact upon the obesogenic environment, including High Court rulings in favour of local authorities and enforcement of Supplementary Planning Documents to tackle the spread of hot food takeaways.

3.

Policy Review

A considerable amount of emerging good practice has been gathered through a variety of agencies, including the Department of Health‟s Childhood Obesity National Support Team and Obesity Policy Team, Local Government Improvement and Development, and the Planning Advisory Service. Previous work has identified a variety of approaches including: Healthy Towns Programme, Healthy Urban Development Unit and healthy urban planner posts4,5,6 Incentives for food operators to consider healthy options, recipes and ingredients7 Policies to limit hours of operation near schools and licensing agreements in proximity to parks and schools, including implementation of supplementary planning documents7,8,9,10,11,12,13 Improvement of walking and cycling facilities7 These cases have highlighted the potential for spatial planning to benefit health and particularly in reference to the obesogenic environment.

4.

Prevalence of obesity and associated risk factors in Birmingham

Several media sources have recently termed Birmingham as the „fattest‟ city in Europe, this statement is an extrapolation of results from the i2sare14 project published in April 2011 but nevertheless has caused significant political and public reaction. Recent reports from the NHS Information Centre15 and the Association of Public Health Observatories16 have also indicated that the obesity prevalence in both adults and children in the city is significantly higher than the England average. Age Group

Birmingham

England

Data Source

Reception % (4-5 year olds) 2009/10

11.2 (10.7-11.7)

9.8 (9.7-9.9)

Year 6 % (10-11 year olds) 2009/10

23.1 (22.4-23.8)

18.7 (18.6-18.8)

National Child Measurement Programme (NHS Information Centre)

Adults % (16+) 200608

26.2 (25.6-26.9)

24.2 (23.6-24.7)

APHO JSNA Dataset

Table 1 – Comparative obesity prevalence (with 95% Confidence intervals) in Birmingham compared with data for England

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In 2010 diseases relating to overweight and obesity were estimated to cost the NHS in Birmingham around £330m each year17. In 2007 the Foresight Report1 used a ratio of 7:1 for comparing the indirect costs of overweight and obesity to the direct costs applicable to the NHS. Applying this estimate to Birmingham would indicate that costs such as lost earnings due to premature mortality or sickness, as a result of obesity cost the city in the region of £2.6 billion in 2010. When looking at risk factors for obesity the city also has significantly lower rates of healthy eating and physical activity than England on average, whilst having a significantly higher prevalence of both Type 2 diabetes and coronary heart disease. Risk factor or associated disease

Birmingham

England

Data Source

Adult (16+) Colorectal Cancer 2004-06 Incidence (rate per 100,000)

46.50 (44.11-48.89)

45.55 (45.25-45.86)

NHS Information Centre for Health and Social Care, NCHOD, Compendium of Clinical and Health Indicators

Adult (16+) CHD Prevalence 2009 (%)

7.16 (7.11-7.22)

5.64 (5.63-5.64)

Eastern Regional Public Health Observatory

Adult (16+) Type 2 Diabetes Prevalence 2006 (%)

4.80 (4.76-4.85)

4.14 (4.14-4.15)

Yorkshire & Humber Public Health Observatory

Adult (16+) Hypertension Prevalence 2006 (%)

29.48 (29.38-29.58)

30.38 (30.37-30.39)

Eastern Regional Public Health Observatory

Adult (16+) Physical Activity 2005/06 (% 3x30mins including transport)

51.96 (50.41-53.50)

58.27 (58.11-58.43)

Active People Survey, re-analysis by National Obesity Observatory

Adult (16+) Healthy Eating 2006-08, five or more portions of fruit or vegetables a day

24.6 (23.3-25.9)

28.7 (28.0-29.3)

APHO JSNA Dataset

Table 2 – Prevalence of risk factors and associated diseases for obesity in Birmingham and England

Our analysis has shown that the prevalence of obesity is significantly higher in more deprived areas and significantly lower in more affluent areas of the city; however this is likely due to a range of factors and along with the above cannot be indicated as a sole risk factor.

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5.

Location and distribution of hot food takeaways across the city

Before looking in detail at different policy options relating to hot food takeaways it is important to build a picture of how this affects different areas within Birmingham. To do this we used the Local Retail and Community Facilities database provided by Birmingham City Council, this allowed us to look at the distribution of the following locations across the city: 

Hot Food Takeaways (Class A5)

 

Youth Facilities Leisure Centres

Educational facilities

 

Pre-Primary Primary Schools

Secondary Schools

 

Special Schools Higher Further Education

Unspecified Education

The information specified in Table 3 was also collected to support this work. Data

Source

Level of geography

Adult Obesity (2003-05)

APHO JSNA Dataset

MSOA

Childhood Obesity for Reception and Year 6 (2006-10)

National Child Measurement Programme, Local Data return from NHS Information Centre

Ward

Public Open Space

GIS Team, Birmingham City Council

Custom Layers

Local Centres (draft at time of collation)

GIS Team, Birmingham City Council

Custom Layers

Index of Multiple Deprivation

Department of Communities and Local Government

LSOA

Proportion of BME community

Census 2001

LSOA

Table 3 – Data included in analysis outside Local Retail and Community Facilities database

The definition of a Class A5 hot food takeaway is an establishment whose primary business is the sale of hot food for consumption off the premises.18 Examples of hot food takeaways include pizza takeaways, kebab shops, fried chicken shops, fish & chip shops, Chinese takeaways and Balti/curry

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takeaways. It is important to note that many large brands of what would be considered fast food, such as McDonalds, Burger King, KFC and Subway are licensed as Class A3 restaurants and do not sit under hot food takeaways. Local centres will be the preferred locations for retail, office and entertainment developments and for community facilities (e.g. health centres, education and social services and religious buildings).19 Open space is taken to mean all open space of public value, including not just land, but also inland bodies of water such as rivers, canals, lakes and reservoirs which offer important opportunities for sport and outdoor recreation and can also act as a visual amenity.20

In April 2011, there were 928 hot food takeaways registered on the Local Retail and Community Facilities database. This means that there were nine hot food takeaways per 10,000 population, which is a similar proportion to that of both Waltham Forest and Barking and Dagenham, prior to their supplementary planning documents. The distribution of hot food takeaways varies substantially across the city; in general large concentrations of takeaways tend to be distributed along particular roads, for instance the Stratford Road and the Coventry Road. There is substantial variation within electoral wards, where Ladywood has 57, whilst Edgbaston has just three.21 The concentration of takeaways is distributed largely within the city centre and within the more deprived areas of the city. In the most deprived 10% of areas in the city there are 3.65 times as many hot food takeaways, as there are in the most affluent 10% of areas. This demonstrates a correlation with the higher prevalence of obesity in more deprived areas but further investigation would be required to address confounding factors in this association. To visualise the potential impact of implementing similar policy options to those that have been passed elsewhere7,8, several scenarios were undertaken. These included looking at a 400m perimeter around key facilities, such as schools and leisure centres and also the concentration of hot food takeaways within local centres. This analysis utilised Geographical Information Systems (GIS) software and an interactive map was produced.22 Some key results from this analysis were: ď&#x201A;ˇ ď&#x201A;ˇ

71% of all primary and secondary schools in the city have a hot food takeaway within 400m, some have as many as 19 within this distance Over 48% are within local centres

ď&#x201A;ˇ

Under 22% are not within local centres or within 400m of a school

There is additional potential to expand this piece of work to further investigate the effects of potential policies. Here we have presented a largely exploratory analysis and further work could be done to investigate the connection between clustering of hot food takeaways and dietary habits within the city. It would be important in this work to acknowledge additional confounding factors where possible. Cluster analysis and tests for association may be based on work by Austin et al.23 and Fraser et al.24 along with other relevant studies.

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Figure 1 â&#x20AC;&#x201C; Locations of Hot Food Takeaways (Class A5) in Birmingham

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6.

Next Steps

At the beginning of July 2011 councillors, planners, public health and other key representatives across the city met to agree a plan of action for how planning policies, development management, regeneration and implementation can contribute more effectively to tackling obesity in Birmingham. The starting point for discussion were options for controlling unhealthy fast food, responding to considerable local debate about the impact of unhealthy fast food on the health of Birmingham residents. The analysis mentioned in this report and other materials were used to support discussion. Following this workshop, there has been a clear indication and steer from members (political support) and a partnership commitment from Birmingham City Council and Public Health for support to tackle health inequalities through policy change and policy implementation relating to Planning and Public Health. Priorities for 2011/2012 are: 

The Health Policy Statement of the Core Strategy is aligned to Public Health priorities, specifically with reference to the 6 Marmot Policy Objectives

The emerging Places for the Future (Sustainability) Supplementary Planning Document has clear Public Health leadership and input

The local centres Supplementary Planning Document includes public health commitments, with specific reference to Class A5 and A3 restrictions and levies

The proposed Supplementary Planning Document for Hot Food Takeaways is written and published for consultation prior to March 2012

 

CIL/Section 106 is adopted as a joint Public Health/Planning Priority The 2008 City Council adopted Statement of Community Involvement is revisited and considered with reference to how Public Health and Planning should be engaging with the public; and how this can assist the JSNA Support the Public Health Impact Assessment that is being conducted on the Health Policy Statement of the Core Strategy

References 1. http://www.bis.gov.uk/assets/bispartners/foresight/docs/obesity/03.pdf (Foresight Report) 2. http://www.marmotreview.org/AssetLibrary/pdfs/Reports/FairSocietyHealthyLives.pdf (Last accessed 03/11/11) 3. http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/PublicationsPolicyAndGuida nce/DH_121941 (Last accessed 03/11/11) 4. Sheffield City Council 5. Sandwell MBC 6. Dudley MBC 7. London Borough Barking & Dagenham - Saturation Point – Addressing the health impacts of hot food takeaways Supplementary Planning Document (March 2010)

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8. London Borough Waltham Forest - Hot Food Takeaway Supplementary Planning Document (March 2009) 9. London Borough Barking & Dagenham - Planning Appeal against Refusal of Takeaway on basis of Saturation Point SPD (Dominoâ&#x20AC;&#x;s Pizza UK Ltd.) (Feb.2011) 10. London Borough Tower Hamlets - Regina (Copeland) v London Borough of Tower Hamlets 11. Leicester City Council 12. Liverpool City Council 13. Salford City Council 14. http://www.i2sare.eu/ (Last accessed 03/11/11) 15. http://www.ic.nhs.uk/ncmp (Last accessed 31/10/11) 16. http://www.apho.org.uk/resource/item.aspx?RID=97319 (Last accessed (31/10/11) 17. (Healthy Weight, Healthy Lives) http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/PublicationsPolicyAndGuida nce/DH_082378 (Last Accessed 03/11/11) 18. Use Class A5 under the Town and Country Planning (Use Classes) Order 1987 as amended 19. SP17 â&#x20AC;&#x201C; Birmingham Core Strategy 2026 20. Planning and Local Government Group 21. http://birminghamhealthandwellbeing.info/wp-content/uploads/2011/08/Statistics-on-thelocation-of-hot-food-takeaways-and-childhood-obesity-in-Birmingham.xls (Last Accessed 03/11/11) 22. http://birminghamhealthandwellbeing.info/wp-content/uploads/2011/08/Mapping-theobesogenic-environment-in-Birmingham.pdf (Last Accessed 03/11/11) 23. Clustering of Fast-Food Restaurants Around Schools: A Novel Application of Spatial Statistics to the Study of Food Environments (Austin et al., American Journal of Public Health, September 2005, Vol 95, No. 9) 24. The association between the geography of fast food outlets and childhood obesity rates in Leeds, UK (Fraser et al. Health & Place 16 (2010) 1124-1128)

Andy Baker, Public Health Scientist Kyle Stott, Health Improvement Specialist Authors

Birmingham Public Health CIBA Suite 203 146 Hagley Road Edgbaston Birmingham B16 9NX

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11 1.

Antipsychotic prescribing 2007 to 2011

Introduction

Antipsychotic drugs are used for the management of mental health problems presenting with psychotic and behavioural symptoms, schizophrenia and bipolar disorder. These drugs can also be used for the treatment of some physical symptoms such as insomnia and severe nausea and vomiting. First-generation or “conventional” antipsychotics, such as chlorpromazine, haloperidol and thioridazine, have been the mainstay of pharmacological treatment for many years but recently the use of “atypical” antipsychotics, such as risperidone, olanzapine, quetiapine, and aripiprazol (in order of introduction), have gained popularity as treatments for psychosis and behavioural problems due to the reported lower risk of side effects.1 They are recommended as first-line treatment choices alongside conventional antipsychotics in the management of schizophrenia.2,3 All antipsychotics can cause side effects although these will be different for each patient and each drug. Atypical antipsychotics have been associated with range of side effects that include weight gain, postural hypotension, extrapyramidal symptoms and an increased risk of mortality, particularly in older people.4 Concerns regarding the serious adverse effects and over-prescription of antipsychotics prescribed for the behavioural and psychological symptoms of dementia (BPSD) dementia have highlighted the need for investigation and action.5 Recent evidence has documented the association between antipsychotics and a number of negative impacts which compromise the quality of life in people with dementia. The most severe effects include increased risk of stroke and mortality.6 Recent reports have highlighted the need for a reduction and more appropriate prescribing of antipsychotics as well as the use of alternative supportive strategies to treat people with Alzheimer‟s disease and dementia experiencing behavioural disturbances.7 At present, risperidone is the only antipsychotic indicated for treatment in the elderly, and only for short-term intervals (6 weeks) with regular review.8 As antipsychotics are used for a variety of mental and physical symptoms and are often prescribed chronically, a large proportion of people receiving antipsychotic therapy will receive them in primary care (general practices [GPs]). Indeed, it is this group of healthcare professionals who are predominantly responsible for on-going support and follow-up of patients on antipsychotics. It is important, therefore, to monitor trends in antipsychotic prescribing especially in primary care.

2.

Methods

We reviewed the prescribing of antipsychotic drugs in the West Midlands using the NHS Business Service Authority‟s Electronic Prescribing Analysis and Cost (ePACT) system from April 2007 to March 2011.

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Electronic Prescribing Analysis and Cost (ePACT) system ePACT is an electronic system which enables retrospective analysis of primary care prescribing data held on the NHS Prescription Services database. Data is collected monthly (5 weeks after the dispensing month) and can be reported in a number of different formats. Antipsychotic drugs We reviewed the prescribing of drugs listed as antipsychotic agents in the British National Formulary (BNF September 2011) within the West Midlands Strategic Health Authority (SHA) area. We analysed prescribing of antipsychotic depot injections separately. Further, we examined prescribing trends for specific antipsychotic drugs, previously identified as being the most commonly prescribed in primary care in the West Midlands. These were chlorpromazine, haloperidol, olanzapine, quetiapine and risperidone. Population demographics The population of the West Midlands SHA area is approximately 5.4 million. The region is served by 17 PCTs with the highest population density being within Birmingham. The region is ethnically diverse and the population is dynamic and changing in age profile, with the majority of growth evident in older age groups. Number of prescriptions To report trends in prescribing practices, the number of prescription items for antipsychotics was analysed by PCT over a four-year period. Further analysis of specific antipsychotics was also completed.

3.

Results

Annual antipsychotic drug use Figure 1 shows the total number of prescription items for all antipsychotic drugs in the West Midlands increased from 1925.65 items per thousand patients in 2007/2008 to 2187.05 items per thousand in 2010/2011, an overall increase of 261.4 items per thousand (14%). The total actual cost of antipsychotic prescription items increased from £24,066,594 to £26,597, 339, an overall increase of £2,530,745 (11%) over the same period. The number of prescription items of antipsychotic depot injections in the West Midlands increased from 40.23 items per thousand patients in 2007/2008 to 42.09 items per thousand in 2010/2011, an overall increase of 1.86 items per thousand (5%) as shown in figure 2. The annual cost of antipsychotic depot injections increased from £491 656.27 to £528 797.28, an overall increase of £37 141.01 (8%). Although the increase in antipsychotic prescriptions of oral drugs appears more evident it must be kept in mind that oral preparations are conventionally used for acute management and depot injections for chronic management of psychosis and behavioural problems.


2250

2000

Items per 1000 patients Antipsychotic drugs

1750

1500 2007/2008

2008/2009

2009/2010

2010/2011

Figure 1. Antipsychotics per 1000 patients in the West Midlands for the financial periods 20072011.Source: ePACT, NHS Business Services Authority

50

45

40

Items per 1000 patients

35

30 2007/2008

2008/2009

2009/2010

2010/2011

Figure 2. Antipsychotic depot injections per 1000 patients in the West Midlands for the financial periods 2007-2011. Source: ePACT, NHS Business Services Authority

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200

175

150 Antipsychotic depot injections

125

100

75

50 2007/2008

2008/2009

2009/2010

2010/2011

HOB

COV

DUD

B E/N

HER

NS

SAN

SHR

SOL

S BHAM

S STA

SOT

T&W

WAL

WARK

WOLV

WORC

Figure 3. Antipsychotic prescribing per item per 1000 patients in the West Midlands from the financial periods 2007-2011 for each PCT. Source: ePACT, NHS Business Services Authority

Antipsychotic prescribing by individual PCT The majority of PCTs display upward trends in antipsychotic prescribing (per 1000 patients) from 2007 to 2011 (figure 3). The largest increase in antipsychotic prescribing rate was seen in Coventry PCT. The lowest number of antipsychotic prescription items in 2010/2011 was in Warwickshire and the only decrease in antipsychotic prescribing rates from 2007 to 2011 was recorded in Birmingham East and North. The number of antipsychotic prescription items in Coventry increased from 145.12 items per thousand patients in 2007/2008 to 186.95 items per thousand in 2010/2011, an overall increase of 41.83 items per thousand (29%). The second highest overall increase of 26.2 items per 1000 patients (27%) was seen in Worcestershire, with an increase from 97.62 to 123.82 over the same period. Increases were recorded in Walsall, with an overall increase of 31.29 items (25%) from 126.22 to 157.57 and North Staffordshire, with an overall increase of 24 items (25%) from 97.65 to 121.65 over the same period.


200 175

175 Chlorpromazine hydrochloride

Haloperidol

150 150 Items per 1000 patients

125

Items per 1000 patients

125 100

100

500

600 Quetiapine

Olanzapine

550

450 500 400

450 Items per 1000 patients

400

Items per 1000 patients

350 350 300

300

400 Risperidone

350 Items per 1000 patients

Figure 4. Prescribing trends for specific antipsychotic prescriptions

300

Source: ePACT, NHS Business Services Authority

Figures indicating increases in items per 1000 patients for all PCTs from 2007/2008 to 2010/2011, including actual cost data for the period 2010/2011 are presented in Table 1.

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The number of antipsychotic prescription items in Birmingham East and North decreased from 114.94 in 2007/2008 to 113.31 items per 1000 patients in 2010/2011, an overall decrease of 1.63 items (1%). The total actual cost of antipsychotic prescription items in this PCT was £ 2 110 770 in 2010/2011.

PCT

Items prescribed per 1000 patients 2007/2008

Items prescribed per 1000 patients 2010/2011

Overall item increase (%) 2007 to 2011

Total actual cost 2010/2011 (£)

Coventry

145.12

186.95

41.83 (29%)

2 499 767

Worcestershire

97.62

123.82

26.2 (27%)

2 331 381

Walsall

126.22

157.57

31.29 (25%)

1 665 627

North Staffordshire

97.65

121.65

24 (25%)

981 511

Dudley

115.35

143.05

27.7 (24%)

1 314 927

Solihull

85.86

105.47

19.61 (23%)

749 921

Telford and Wrekin

105.28

123.15

17.87 (17%)

821 045

Heart of Birmingham

113.23

129.99

16.76 (15%)

1 644 739

Herefordshire

103.2

115.12

11.92 (12%)

773 465

South Staffordshire

97.32

107.35

10.03 (10%)

2 193 648

Wolverhampton City

139.25

152.35

13.1(9%)

1 330 224

Shropshire County

103.75

112.31

8.56 (8%)

1 244 702

Sandwell

114.14

119.95

5.81 (5%)

1 676 302

South Birmingham

136.43

141.48

5.05 (4%)

1 874 344

Warwickshire

99.29

100.74

1.45 (2%)

1 878 661

Stoke on Trent

130.7

133.79

3.09 (2%)

1 506 703

Table 1. Increases in antipsychotic prescribing per item per 1000 patients per PCT in the West Midlands from the financial periods 2007-2011. Source: ePACT, NHS Business Services Authority

Prescribing of specific antipsychotic drugs Quetiapine is currently the most commonly prescribed antipsychotic agent in the West Midlands (figure 4). The use of conventional antipsychotics (chlorpromazine, haloperidol) has decreased while the use of “atypical” antipsychotics (olanzapine, quetiapine, risperidone) has increased. For the years 2007 to 2011, the use of chlorpromazine decreased from 181.92 items to 49.01 items per 1000 patients, an overall decrease of 32.91 (18%). Within the same period, the use of haloperidol decreased from 157.42 items to 132.22 items per 1000 patients and an overall decrease of 25.2 (16%). In


contrast from 2007 to 2011, the use of olanzapine increased from 426.84 items per 1000 patients to 468.0 items equating to an overall increase of 41.16 items (10%). During the same period, the use of quetiapine increased from 375.8 items to 571.01 items per 1000 patients; an overall increase of 195.21 items (52%) from 2007 to 2011. The use of risperidone also increased from 349.96 items in 2007 to 397.31 items per 1000 patients in 2011, equating to an overall increase of 47.35 items (14%).

4.

Discussion

The prescription item is defined as the number of times a product appears on a prescription form. It is a relatively crude measure of prescribing volume. For areas of prescribing where there is likely to be a high level of repeat prescribing, such as antipsychotics, the number of items can be misleading because different practices use a different duration of supply, i.e. some will issue a prescription monthly, others for two months or three months and so will have different numbers of items for the same amount of medication. Even within a single practice there can be differences in the duration of prescriptions. However, at PCT level the shortcomings of the prescription item tend to be reduced and it can be used as a reasonable proxy measure for the volume of prescribing at this level. Antipsychotic drugs are used for a range of different indications and therefore, it is not possible to link changes in prescribing to changes in the incidence and prevalence of specific mental health disorders. Trends in prescribing in primary care can also be influenced by other factors such as changes to the configuration of local services, the introduction of local drug formularies or initiatives to optimise prescribing behaviour. The numbers of prescription items for antipsychotic drugs and antipsychotic depot injections in primary care have both increased in the West Midlands from 2007 to 2011. These observations are based on items per 1000 patients and thus only average prescribing trends in the region can be described. However, the data is consistent with observed increases in the prevalence and incidence of mental health problems at both national and regional levels. The number of people accessing specialist NHS mental health services has been steadily rising over the past five years. This increase had previously been accompanied by a decrease in the number of people who received inpatient care for mental health related problems. However, since 2009 the number of people spending time in an NHS mental hospital has been increasing (includes people being compulsorily detained in hospital under the Mental Health Act).9 Antipsychotic prescribing rates in Coventry remained consistently higher than the other 16 PCTâ&#x20AC;&#x;s from 2007 to 2011. A number of variables could affect prescribing rates and it would be inappropriate to offer any conclusions or explanations regarding the higher prescribing rate. Specific needs indices, the population profile of Coventry and the risk factors associated with mental health disorders indicate that the population may be at an increased risk of mental health disorders. However, on further analysis of Quality and Outcomes Framework (QOF) and individual GP practice prescribing data, great variation between practices is evident.10 Quetiapine was the most commonly prescribed antipsychotic drug. This may be explained by concerns regarding the safety profiles and side-effects of other atypical antipsychotics.11 Extensive

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use of quetiapine has been reported elsewhere and a need for further research on the safety and efficacy of this drug emphasized.12 The use of newer atypical antipsychotic drugs is increasing and preferred to first-generation drugs, of which use has decreased proportionally with the introduction of atypical antipsychotics. Limitations of data derived from the ePACT system include the inability to standardise prescriptions according to age and sex thus cannot reflect prescribing trends associated with population demographics. Data is also not linked to diagnosis or to individual patients and conclusions regarding prescribing practices for specific conditions or length of therapy cannot be made. Evaluation of the incidence of psychiatric disorders was beyond the scope of this work but will be useful in further analyzing prescribing practices. Further, the changes observed from this data may not reflect antipsychotic prescribing in other settings (inpatient wards or care homes). The use of atypical antipsychotics among psychiatrists has been documented as higher than in primary care.13 As GPs initiate antipsychotic therapy and are often responsible for follow-up of patients initiated in other settings, it is clear that the monitoring of prescribing trends in primary care will provide a clearer picture of antipsychotic trends overall. The trends observed from this data have also been found in other studies, particularly with regard to increases in general antipsychotic use and atypical antipsychotic use.14 Continuous monitoring of antipsychotic trends is necessary in order to achieve and identify safe and effective prescribing goals while ensuring good patient care. Further linking of antipsychotic data to incidence of psychiatric illness and population demographical would prove invaluable. The integration of mental health services and linking of data is essential to putting recommendations into practice and improving antipsychotic prescribing practices.

References 1. Leucht S, Corves C, Arbter D et al (2009). Second-generation versus first-generation antipsychotic drugs for schizophrenia: a meta-analysis. Lancet 373: 31â&#x20AC;&#x201C;41. 2. Naber D, Lambert M (2009). The CATIE and CUtLASS studies in schizophrenia: results and implications for clinicians. CNS Drugs 23(8): 649-659. 3. National Institute for Healthcare and Clinical Excellence NICE clinical guideline 82. Schizophrenia. Core interventions in the treatment and management of schizophrenia in adults in primary and secondary care (2011). Available from http://www.nice.org.uk/cg82 4. Risk of Death with Atypical Antipsychotic Drug Treatment for Dementia Meta-analysis of Randomized Placebo-Controlled Trials (2005). JAMA 294:1934-1943. 5. All-Party Parliamentary Group on Dementia (2008).Always a Last Resort: Inquiry into the prescription of antipsychotic drugs to people with dementia living in care homes. 6. Schneider LS, Dagerman K, Insel PS (2006). Efficacy and Adverse Effects of Atypical Antipsychotics for Dementia: Meta-analysis of Randomized, Placebo-Controlled Trials. American Journal of Geriatric Psychiatry 14(3): 191-210.


7. Banerjee S (2009). The use of antipsychotic medication for people with dementia: Time for action. Report for the Minister of State for Care Services, Department of Health Publication. 8. Ballard C, Hanney ML, Theodoulou M et al (2009). The dementia antipsychotic withdrawal trial (DART-AD):long-term follow-up of a randomised placebo-controlled trial. Lancet Neurology 8: 151-157. 9. The Health and Social Care Information Centre (2011). Mental Health Bulletin Fourth report from Mental Health Minimum Dataset (MHMDS) annual returns, 2010. 10. Forde J (2008). Coventry Mental Health Needs Assessment. 11. Maher AR, Maglione M, Bagley S (2011). Efficacy and Comparative Effectiveness of Atypical Antipsychotic Medications for Off-Label Uses in Adults: A Systematic Review and Meta-analysis. Journal of the American Medical Association 306(12): 1359-1369. 12. Philip NS, Mello K, Carpenter LL et al (2008). Patterns of quetiapine use in psychiatric inpatients: an examination of off-label use. Annals of Clinical Psychiatry 20(1): 15-20. 13. Frangou S, Lewis M (2000). Atypical antipsychotics in ordinary clinical practice: a pharmacoepidemiologic survey in a south London service. European Psychiatry 15: 220-226. 14. Kaye JA, Bradbury BD, Jick H (2003). Changes in antipsychotic drug prescribing by general practitioners in the United Kingdom from 1991 to 2000: a population/based observational study. British Journal of Clinical Pharmacology 56: 569 â&#x20AC;&#x201C; 575.

Angelique Mavrodaris Mental health and Wellbeing Division, Warwick Medical School Authors

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Richard Seal, Programme Consultant in Medicines Management. NHS West Midlands St Chads Court, 213 Hagley Road Birmingham B16 9RG

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12 1.

Smoking Cessation the West Midlands

Introduction

Smoking tobacco is one of the government‟s major public health challenges, which causes an estimated 80,000 premature fatalities in England each year1. The White Paper, Healthy lives and healthy people: Our strategy for public health in England sets out the Government‟s pledge to enhance the public health in populations across England. The Government published its Tobacco Control Plan, Healthy lives, Healthy people: A Tobacco Control Plan for England on 9th March 2011. The Tobacco control Plan gave a framework of how, over the next five years, tobacco control will be carried out in the milieu of the new public health system. The plan envisaged three national aspirations to decrease smoking rates in England by the end of 2015: 1) From 21.2 per cent to 18.5 per cent or less among adults; 2) From 15 per cent to 12 per cent or less among 15 year olds; and 3) From 14 per cent to 11 per cent or less among pregnant mothers (measured at the time they give birth).

2.

NHS Stop Smoking Services

The NHS Stop Smoking Services help and assist people to stop smoking. This may consist of behavioural support therapy (in a group or one-to-one setting) and advise on the use of clinically effective stop smoking pharmacotherapies to aid the quit attempt. Such pharmacotherapies include, Nicotine Replacement Therapy (NRT), Bupropion and the more recently introduced Varenicline. Stop smoking support is intended to be easily accessible for local communities and is delivered by qualified staff, such as specialist smoking cessation advisors, trained nurses and pharmacists. The total expenditure on NHS Stop Smoking Services nationally was £84.3 million and £10.5 million in the West Midlands in 2010/111

3.

Current Services within West Midlands

A lifestyle tariff pilot was first introduced within the West Midlands in April 2010. The scheme introduced local tariffs, for stop smoking services and aimed to improve health outcomes by increasing the supply and quality of stop smoking provision. Payments are made to providers based on the number of smokers who quit for 4 and 12 weeks. A higher tariff is also paid for smokers from vulnerable groups who are at greater risk for smoking and smoking related illness.

1

Statistics on NHS Stop Smoking Services: England, April 2010 – March 2011 – NHS Information Centre


The following Primary Care Trusts (PCTs) within the West Midlands opted to join the pilot:        

Telford and Wrekin Coventry Stoke on Trent Shropshire County Walsall South Staffordshire Worcestershire Sandwell

PCTs that opted out of the pilot also commission a range of community providers to deliver stop smoking support. For example, Birmingham has adopted a „hub and spoke‟ model for service delivery, whereby a „core service‟ provides community groups and clinics targeting high smoking prevalence areas, but also support and monitor „subcontracted‟ providers of stop smoking services such as local GP‟s and community pharmacies. Referrals into the stop smoking services are made via a single point of contact telephone number and managed by a call centre.

Smoking Cessation Statistics

Quitters per 100,000 aged 16+

4.

England

950

West Midlands

900 850 800 750 700

2006/07 2007/08 2008/09 2009/10 2010/11

Figure 1. The number of successful 4-week quitters per 100,000 popn in England and West Midlands, 2006/7 to 2010/11. There was a marked increase during 2007/08 following the implementation of the smokefree legislation. Despite reductions in the following year during 2008/09, the rate continues to show an overall upward trend both in England and in the West Midlands. Source: Source: Statistics on NHS Stop Smoking Services: England, April 2010 – March 2011 – NHS Information Centre

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Figure 2. Quit rate (per 100,000 population) in West Midlands PCTs. 2010-11. Statistics on NHS Stop Smoking Services: England, April 2010 – March 2011 – NHS Information Centre.

450

Cost per Quitter

400

PCT

England

350 300 250 200 150 100 50 0

Figure 3. Cost per quitter in West Midlands PCTs. Source: Statistics on NHS stop smoking services: England, April 2010-March 2011 – NHS Information centre. Correlation coefficient between Quit Rate and Cost per Quitter – R= -0.088, P=0.738 - not significant


5.

Variation within West Midlands PCTs

Considerable variation can be seen between individual PCTs (Fig 2). Seven PCTs achieved quit levels in excess of the West Midlands and England, while eight did less well. A number of factors may explain this variation, such as sociodemographic profile of each PCT and the level of funding allocated to stop smoking provision and marketing. Source: Stop smoking services have also developed differently in the PCTs in the region. It is no surprise therefore that there is such variation not only in how the service is delivered and in the success rates but also in cost efficiency (Fig 3). There appears to be little correlation between success and cost per quitter. More than half of the schemes cost more than West Midlands as a whole, and only four schemes cost less than England

6.

Summary / Recommendations   

There needs to be closer monitoring of the effectiveness of stop smoking services that are commissioned to ensure the delivery of the 2015 target. Commissioners should evaluate the reasons for variations in success rates of individual services, identify the markers that predict high performance, and share good practice. Delivery of the Quality Innovation Productivity & Prevention (QIPP) programme will depend on mass roll out of stop smoking brief opportunistic training across sectors, including patientfacing staff within acute and mental health trusts.

Catherine Tomaney, Health Improvement Specialist Hashum Mahmood, Public Health Epidemiologist

Authors

Health Improvement Directorate, Waterlinks House, 2nd Floor Richard St, Aston, Birmingham B7 4AA

Antony Stewart, Professor of Public Health Staffordshire University, Stoke-on-Trent, ST4 2DF

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Key Health data 2010-11