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Health Informatics Journal
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Using administrative data for primary care research: the City and East London General Practice Database Project

J. Naish

The City and East London General Practice Database Project, The Department of General Practice and Primary Care, St Bartholomew’s and the Royal London School of Medicine and Dentistry, Queen Mary and Westfield College, London, E1 4NS, UK, j.naish{at}qmw.ac.uk

K. Moser

The City and East London General Practice Database Project, The Department of General Practice and Primary Care, St Bartholomew’s and the Royal London School of Medicine and Dentistry, Queen Mary and Westfield College, London, E1 4NS, UK

P. Sturdy

The City and East London General Practice Database Project, The Department of General Practice and Primary Care, St Bartholomew’s and the Royal London School of Medicine and Dentistry, Queen Mary and Westfield College, London, E1 4NS, UK

Y. H. Carter

The City and East London General Practice Database Project, The Department of General Practice and Primary Care, St Bartholomew’s and the Royal London School of Medicine and Dentistry, Queen Mary and Westfield College, London, E1 4NS, UK

The City and East London General Practice Database Project was launched in 1992 to provide a framework for describing and understanding the nature of general practice in east London using routinely available administrative data from all practices in the area. It has provided an opportunity to use information on practices for research, health planning and policy, and for educational purposes. The project differs from others because it allows description in detail, clarity and depth in three distinct ways. Firstly, by covering all practices, and not just a select group, it is possible to investigate intra-health authority variability. Secondly, it has taken into account social and demographic characteristics of the practice populations, so making it possible to examine practice outputs in relation to population deprivation. Thirdly, in time, analyses using a combination of patient outcomes, morbidity information and longitudinal data become possible, making it an even more powerful information base for commissioning.

Health Informatics Journal, Vol. 5, No. 1, 30-34 (1999)
DOI: 10.1177/146045829900500105
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