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Mapping English GP prescribing data: a tool for monitoring health-service inequalities

Rowlingson, Barry and Diggle, Peter and Taylor, Benjamin and Lawson, Euan (2013) Mapping English GP prescribing data: a tool for monitoring health-service inequalities. BMJ Open, 3 (1). ISSN 2044-6055

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    Abstract

    Objective The aim of this paper was to show that easily interpretable maps of local and national prescribing data, available from open sources, can be used to demonstrate meaningful variations in prescribing performance. Design The prescription dispensing data from the National Health Service (NHS) Information Centre for the medications metformin hydrochloride and methylphenidate were compared with reported incidence data for the conditions, diabetes and attention deficit hyperactivity disorder, respectively. The incidence data were obtained from the open source general practitioner (GP) Quality and Outcomes Framework. These data were mapped using the Ordnance Survey CodePoint Open data and the data tables stored in a PostGIS spatial database. Continuous maps of spending per person in England were then computed by using a smoothing algorithm and areas whose local spending is substantially (at least fourfold) and significantly (p<0.05) higher than the national average are then highlighted on the maps. Setting NHS data with analysis of primary care prescribing. Population England, UK. Results The spatial mapping demonstrates that several areas in England have substantially and significantly higher spending per person on metformin and methyphenidate. North Kent and the Wirral have substantially and significantly higher spending per child on methyphenidate. Conclusions It is possible, using open source data, to use statistical methods to distinguish chance fluctuations in prescribing from genuine differences in prescribing rates. The results can be interactively mapped at a fine spatial resolution down to individual GP practices in England. This process could be automated and reported in real time. This can inform decision-making and could enable earlier detection of emergent phenomena.

    Item Type: Article
    Journal or Publication Title: BMJ Open
    Additional Information: This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.
    Subjects:
    Departments: Faculty of Science and Technology > Mathematics and Statistics
    Faculty of Health and Medicine > Medicine
    ID Code: 61535
    Deposited By: ep_importer_pure
    Deposited On: 07 Jan 2013 10:58
    Refereed?: Yes
    Published?: Published
    Last Modified: 21 Oct 2017 03:01
    Identification Number:
    URI: http://eprints.lancs.ac.uk/id/eprint/61535

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