Evidence map›Paper›PMID 15695275›Full record

ArticleBMJ (Clinical research ed.)2005

Mapping choice in the NHS: cross sectional study of routinely collected data.

Mike Damiani, Carol Propper, Jennifer Dixon

Abstract read
In one paragraph

Article in BMJ (Clinical research ed.), 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Article
  2. Observational
  3. Influence of local provision of specialty health care service on patient access to care.Canadian journal of surgery. Journal canadien de chirurgie · 2007
    Article
  4. Poor access to care: rural health deprivation?The British journal of general practice : the journal of the Royal College of General Practitioners · 2006
    Article
  5. Choice.BMJ (Clinical research ed.) · 2005
    Article
  6. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Mike DamianiPolicy Directorate, King's Fund, London W1G 0AN.
Carol Propper
Jennifer Dixon

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo identify where in England there are likely to be most constraints on choice of hospital for patients waiting longer than six months for elective care.

designCross sectional study using routinely collected data.

settingPopulation of England and NHS trusts and private sector hospitals in England.

participantsAll residents in England.

main outcome measuresAvailability of beds (available and unoccupied hospital beds), demand (number of people waiting longer than six months), and access (travel time to facilities) to hospital care in England.

resultsMost people in England already have an extensive potential choice of hospital. The number of available and unoccupied beds within 60 minutes' travel time was lowest in the Scottish borders, North Yorkshire, and parts of East Anglia, Lincolnshire, Devon, and Cornwall. This pattern was not altered by adding in private facilities. Putting demand with this supply, the number of people in a geographical area waiting longer than six months per bed within 60 minutes' travel time was highest in the south east (except London), parts of the south west (Cornwall, Bristol), East Anglia, and the Welsh border.

conclusionPeople in the south east (outside London), East Anglia, and parts of the south west are likely to have to travel further to exercise meaningful choice of hospital for elective care.

Indexed as

Waiting ListsBed OccupancyCatchment Area, HealthChoice BehaviorCross-Sectional StudiesData CollectionElective Surgical ProceduresEnglandGeographyHealth Services AccessibilityHospitals, PrivateHospitals, PublicHumansMaps as TopicResidence CharacteristicsState Medicine

Identifiers

PMID15695275
PMCPMC548177

What OpenQuestion holds

Textmetadata
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.