4.11 GIS in the NHS; SAHSU; The UK Public Health Observatories

GIS in the NHS

The explosion in the use and interest of GIS and desktop mapping for health applications in the UK has resulted in the development of specialist health GIS and spatial analysis units such as the West Midlands Health GIS Service in Birmingham and SASHU in London, and more recently the Public Health Observatories of England (White, 2000).

The Small Area Health Statistics Unit (SAHSU)

SAHSU was established by the Government in response to considerable scientific and public interest in the distribution of diseases across small areas which arose following the identification of a 'cluster' of childhood leukaemia near the Sellafield nuclear plant in 1983. SAHSU is located in the Department of Epidemiology & Public Health, Imperial College School of Medicine, London.

SAHSU incorporates national cause-specific data on deaths (from 1981), cancers from the national cancer registry (from 1974), hospital admissions (from 1992) and congenital malformations (from 1983), using the postcode of residence to locate cases to within 100 m. (There are currently around 2 million postcodes in use in the UK.) The system also holds postcoded data on births (from 1981).

Terms of reference of SAHSU are as follows:

To examine quickly and advise on reports of unusual clusters of disease, particularly in the neighbourhood of industrial installations;
To carry out detailed epidemiological enquiry of routine health statistics, and, where available, relevant environmental data, particularly in the neighbourhood of industrial installations;
In collaboration with other scientific groups, to build up background information on the distribution of disease amongst small areas so that specific clusters can be placed in proper context;
To explore and develop methods for the study of available statistics in order to detect reliably any unusual incidence of disease; and
To develop the methodology for analysing and interpreting statistics relating to small areas.

Reporting On Disease Clusters

This SAHSU report relates the number of cases observed in a specified area to the number expected for a typical population of the same size, age structure and socio-economic profile as the neighbourhood in question.

Using an Oracle database and a Geographical Information System (ArcInfo), incident cancer cases, deaths, congenital malformations or hospital admissions occurring among residents living near sources of environmental pollution can be located and rates of disease calculated by linking these events to the underlying populations at risk. Population data are available for 1981 and 1991 census enumeration districts (around 440 people on average), and 1971 census wards (around 10,000 people). Small area deprivation measures (e.g., Carstairs index - see below), which are strongly predictive of mortality and cancer incidence, are also obtained from census statistics and used to adjust disease rates for possible confounding by socio-economic variables.

A choropleth map produced by SAHSU showing Carstairs deprivation scores by ward ranging from Affluent (light blue) to Deprived (dark blue)

N.B.: Area deprivation scores have been used for many purposes, particularly analysis for healthcare services. Standard deprivation scores include Townsend, Carstairs, Jarman, and DoE. The Carstairs Index for the 1981 Census of Scotland, developed by Vera Carstairs and Russell Morris in their book Deprivation and Health in Scotland, was considered a benchmark index.

Public Health Observatories of England

The Government White Paper - Saving Lives: Our Healthier Nation - set two major objectives: to improve the health of the population as a whole and to improve the health of the worst off in society.

In support of these objectives the White Paper announced the establishment of a Public Health Observatory in each of the NHS Regions. The eight observatories will be linked together to form a national network of knowledge, information and surveillance in public health. These new observatories will also be a resource for enquiry - searching for and compiling information and datasets on the nation's health and distilling from them the knowledge to guide its improvement. (www.pho.org.uk, 2000)

One of the principle functions of the observatories will be in health surveillance – a broad term that involves the ‘tracking’ and monitoring of health. This complex and far from straightforward task will involve the assimilation and analysis of many diverse data ranging from poverty, housing, pollution, crime, educational standards, to pay employment, and not to mention directly related health data. These are all data relating to a place, a common theme binding them together and one that explicitly places them in the domain of GIS. The combination of all these disparate data from a wide variety of sources is in direct line with the ‘joined up thinking’ ethos of the present government, a role GIS is uniquely qualified to fulfil. Public Health departments are increasingly aware of the value of GIS, but either tend not to be aware of its full value (creating output other than descriptive choropleth maps), or how to use it to its fullest potential (though that’s not to say some are accomplished users). (White, 2000)

In presentation titled "Introduction to GIS and GI use in Health" and given at the Health SIG seminar on 25 May 1999 by Ralph Smith, GIS Manager of West Midlands Cancer Intelligence Unit, Smith points to the fact that true GIS potential has not been reached yet within the NHS, and that most of what is currently taking place in the NHS does not go beyond simple mapping.

HA = Health Authority

Smith concluded that GIS needs to be recognised in UK IT policy for national co-ordination, where GIS should also act as a framework for data sharing.

The Trent Public Health GIS

At the University of Sheffield in Trent (UK), a Public Health Geographical Information Sciences Unit was established in 1999. The Unit’s core activities are funded by a grant from the Public Health Development Fund. The unit has three main aims:

To conduct high quality grant funded and commissioned research;
To promote awareness and use of GIS in health;
To provide support for GIS and spatial analysis in health. (White, 2000)

The First European Conference on Geographic Information Sciences in Public Health will be held will be also held at the University of Sheffield in September 2001 and is sponsored by NHS Executive Trent.

GIS at the Diabetes, Endocrinology & General Medicine, Division of Medicine, St Thomas' Hospital, London (UK)

At the Diabetes, Endocrinology & General Medicine, Division of Medicine, St Thomas' Hospital, London, Weng and Sonksen (2000) used GIS to investigate differences in metabolic control, access to healthcare, clinical outcomes and mortality rates in people from different cultural and ethnic backgrounds living in different geographical areas within central London. Out of a cohort of 610 patients living within the Greater London boundary and having a first visit to St Thomas' hospital in 1982-1985, 332 patients (54%) were reviewed in 1995, 186 patients (30%) died between 1982 and 1995 and 92 patients (16%) were lost to follow-up. The patients' corresponding 'electoral wards' were ascertained in relation to postcodes of residence (Mapinfo). Each electoral ward has a Jarman 'Underprivileged Area Score' (UPA) so that patients can be clustered into prosperous, intermediate or deprived areas.

Patients living in deprived areas (n = 181) were older (61.3 years (95% confidence interval (CI) 59.5-63.1) vs. 58.6 years (95% CI 55.1-62.1), P = 0.01) and had a higher body mass index (29.2 kg/m2 (95% CI 28.4-30.0) vs. 25.7 kg/m2 (95% CI 24.1-27.2), P = 0.003) and worse glycaemic control (HbA1 (%), 10.5 (95% CI 10.1-10.9) vs. 9.1 (95% CI 8.2-10.0), P = 0.003) than patients in prosperous areas (n = 59). Patients in deprived areas were more likely to be Caucasian (P < 0.005), and were less likely to be insulin-treated (P = 0.004). Smoking was more prevalent in deprived areas (P = 0.02). The prevalence of microvascular complications was related to geographical location and the age-sex adjusted mortality rate was significantly higher in deprived than prosperous areas (2.6 vs. 1.91 per 100 person-years).

The researchers concluded that environmental factors affect diabetes outcomes; increased morbidity and mortality rates in diabetic patients are related to socio-economic and ethnic status.

References:

Elliott P, Westlake AJ, Kleinschmidt I, Hills M, Rodrigues L, McGales P, Marshall K and Rose G. The Small Area Health Statistics Unit: a national facility for investigating health around point sources of environmental pollution in the United Kingdom. J Epidemiol Community Health. 1992;46:345-349
Weng C, Coppini DV and Sonksen PH. Geographic and social factors are related to increased morbidity and mortality rates in diabetic patients. Diabet Med. 2000 Aug;17(8):612-7
White P. The Trent Public Health GIS Unit. University of Sheffield. 2000 (July)

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