Evidence map›Paper›PMID 28733459›Full record

ArticleJournal of epidemiology and community health2017

Advice given by NHS Direct in Wales: do deprived patients get more urgent decisions? Study of routine data.

Julie Peconi, Steven Macey, Sarah Rodgers, Ian Russell, Helen Snooks, Alan Watkins

Abstract read
In one paragraph

Article in Journal of epidemiology and community health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Julie PeconiSwansea University Medical School, Institute of Life Sciences 2 (ILS2), Swansea University, Swansea, UK.
Steven MaceyAction on Smoking and Health (ASH) Wales, Cardiff, UK.
Sarah RodgersSwansea University Medical School, Institute of Life Sciences 2 (ILS2), Swansea University, Swansea, UK.
Ian RussellSwansea University Medical School, Institute of Life Sciences 2 (ILS2), Swansea University, Swansea, UK.
Helen SnooksSwansea University Medical School, Institute of Life Sciences 2 (ILS2), Swansea University, Swansea, UK.
Alan WatkinsSwansea University Medical School, Institute of Life Sciences 2 (ILS2), Swansea University, Swansea, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the UK, National Health Service Direct Wales (NHSDW) uses computerised decision support software to advise patients on appropriate care. However, the effect of deprivation on the advice given is not known. We aimed to estimate the effect of deprivation on advice given by nurses in NHSDW adjusting for confounding variables.

methodsWe included 400 000 calls to NHSDW between January 2002 and June 2004. We used logistic regression to model the effect of deprivation on advice given by nurses in response to calls seeking advice or information. We analysed two outcomes: receiving advice to phone 999 emergency care rather than to seek other care and receiving advice to seek care face to face rather than self-care.

resultsAfter adjustment for covariates, an increase in deprivation from one-fifth of the distribution to the next fifth increased by 13% the probability that those calling for advice rather than information received advice to phone 999 (OR 1.127; 95% CI from 1.113 to 1.143). Deprivation increased the corresponding probability of being advised to seek care face to face rather than self-care by 5% (OR 1.049; 95% CI from 1.041 to 1.058) within advice calls and by 3% (OR 1.034; 95% CI from 1.022 to 1.047) within information calls.

conclusionsDeprivation increased the chance of receiving more urgent advice, particularly advice to call 999. While our dataset may underestimate the 'need' of deprived patients, it yields no evidence of major inequity in advice given to these patients.

Indexed as

health services needs and demandhotlinespoverty areassocioeconomic factorstelemedicinevulnerable populations

Identifiers

PMID28733459
PMCPMC5561357

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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.