Evidence map›Paper›PMID 23293241›Full record

ArticleBMJ open2013

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

Barry Rowlingson, Euan Lawson, Benjamin Taylor, Peter J Diggle

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in BMJ open, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. bench4gis: Benchmarking Privacy-aware Geocoding with Open Big Data.Proceedings : ... IEEE International Conference on Big Data. IEEE International Conference on Big Data · 2019
    Article
  8. Article
  9. Organisation of services for managing ADHD.Epidemiology and psychiatric sciences · 2017
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Barry RowlingsonCHICAS, Lancaster University, Lancaster, Lancashire, UK.
Euan Lawson
Benjamin Taylor
Peter J Diggle
Lancaster University · GB

Funding

Medical Research Council G0902153Medical Research Council MC_PC_13042
6 · The paper itself

Abstract

objectiveThe 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.

designThe 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.

settingNHS data with analysis of primary care prescribing. POPULATION: England, UK.

resultsThe 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.

conclusionsIt 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.

Identifiers

PMID23293241
PMCPMC3549233
OpenAlexW2170129625

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.