The Intelligent Board 2009: Commissioning to reduce inequalities

Health inequalities tool user guide

Follow these four easy steps to find out how well your local Primary Care Trust (PCT) serves your community health needs:

1. Choose an indicator from the list (diabetes, heart disease, ambulatory care sensitive conditions, stroke and alcohol)
2. Select the part of the country where you live on the interactive map
3. Choose your local PCT from the list
4. From your PCT page, enter your postcode and click the submit postcode button

For each health indicator you will be able to see if admissions for each PCT or GP practice have:

1. Higher rates of hospital admissions than expected nationally
2. Hospital admission rates as expected
3. Lower rates of hospital admissions than expected nationally

Choose an indicator:

ACS conditions Alcohol Diabetes Heart disease Stroke

This website is designed to support and extend the content of the report The Intelligent Board 2009: Commissioning to reduce inequalities, which was published in June 2009. View the full intelligent board report.

This report was produced by an independent reference group chaired by Alan Stephenson (chair of NHS Ashton, Leigh and Wigan and trustee of NHS Confederation) and supported by Dr Foster Intelligence. It aims to revisit the principles and approach first set out in The Intelligent Board and to apply them to the challenge of commissioning to tackle inequalities. The report challenges PCT boards to test their inequalities knowledge and the information they use against a 'best practice' checklist.

Preparing the report included the challenge of creating some analyses. Therefore we wanted to use data that is available now and as up to date as possible. We sought analyses that would be appropriate to the task of monitoring progress in tackling inequalities and that would enable comparisons and benchmarking. Above all, the analyses needed to be simply presented, particularly in prompting useful questioning and discussion.

For these reasons, we developed a number of indicators derived from patient administrative data (SUS). This national data-set allows for benchmarking and comparisons across NHS organisations. We are now making these indicators publicly available (along with some other similar ones), allowing people to see the results for any primary care trust (PCT) or GP practice.

We have selected conditions where the evidence suggests a strong correlation with inequalities, and where hospital admissions act as a marker for unmet need in access to effective prevention and primary care. We applied statistical techniques to create Standardised Admission Ratios (SARs), which take into account differences in the size, nature and demographics of the local population that are outside the PCT's control.

For each indicator used, you will be able to see if admissions for each PCT or GP practice have:

1. Higher rates of hospital admissions than expected nationally
2. Hospital admission rates as expected
3. Lower rates of hospital admissions than expected nationally

To calculate how many admissions were expected for a PCT, we looked at the national profile of admissions broken down by age, sex and deprivation. This breakdown was then applied to the PCT's population to show the number of expected admissions. More details and full methodology.

Like any single analysis, SARs are neither a perfect nor a comprehensive indicator of inequalities. They are not, in this context, an attempt to measure prevalence or morbidity, nor to measure the quality of services (though they could be used in conjunction with such analyses). They are useful because they reflect real events happening to real people: hospitalisations that are happening more often than expected in some places and for some population groups. Higher or lower than expected SARs prompt questions around the reasons behind these figures, and allow organisations to compare themselves with others and share ways of delivering care.

For this website's first release we have picked five common conditions:

1. Diabetes complications (non-elective admissions)
2. Heart disease (coronary atherosclerosis and other heart disease)
3. Ambulatory care sensitive (ACS) conditions
4. Stroke (acute cerebrovascular disease)
5. Alcohol (alcohol-related liver disease and alcohol-related mental breakdown

Please note that all of the above analyses are for hospital admissions, not A&E attendances. Most hospital activity where alcohol was implicated takes place in A&E. This analysis shows admissions for long-term alcohol-related conditions, where illness due to alcohol was the primary diagnosis. Admissions where alcohol was listed as a secondary diagnosis are not included. High levels of alcohol-related admissions may reflect the service provision in an area: if a hospital has a specific alcohol treatment service, this may lead to high levels of admissions. Conversely, if a PCT lacks a specific alcohol treatment service and as such has low levels of hospital admissions, this may reflect unmet need in the population. However, given the growing problem of alcohol across all PCTs, it would be worthwhile reviewing this indicator as a starting point.