Evidence map›Paper›PMID 31891115›Full record

ArticleBMC rheumatology2019

Factors that influence rheumatologists' anti-tumor necrosis factor alpha prescribing decisions: a qualitative study.

Sean P Gavan, Gavin Daker-White, Katherine Payne, Anne Barton

Abstract read
In one paragraph

Article in BMC rheumatology, 2019. 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. Article
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

4 authors.

Sean P Gavan1Manchester Centre for Health Economics, Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Oxford Road, Manchester, M13 9PL UK.ORCID 0000-0003-3659-056X
Gavin Daker-White3NIHR Greater Manchester Patient Safety Translational Research Centre, Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Oxford Road, Manchester, M13 9PL UK.
Katherine Payne1Manchester Centre for Health Economics, Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Oxford Road, Manchester, M13 9PL UK.
Anne Barton2NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.

Funding

Medical Research Council MR/K015346/1
6 · The paper itself

Abstract

backgroundTreatment decisions for any disease are usually informed by reference to published clinical guidelines or recommendations. These recommendations can be developed to improve the relative cost-effectiveness of health care and to reduce regional variation in clinical practice. Anti-tumor necrosis factor alpha (anti-TNF) treatments are prescribed for people with rheumatoid arthritis according to specific recommendations by the National Institute for Health and Care Excellence in England. Evidence of regional variation in clinical practice for rheumatoid arthritis may indicate that different factors have an influence on routine prescribing decisions. The aim of this study was to understand the factors that influence rheumatologists' decisions when prescribing anti-TNF treatments for people with rheumatoid arthritis in England.

methodsSemi-structured one-to-one telephone interviews were performed with senior rheumatologists in different regions across England. The interview schedule addressed recommendations by the National Institute for Health and Care Excellence, prescribing behavior, and perceptions of anti-TNF treatments. Interviews were recorded digitally, transcribed verbatim, and anonymized. Data were analyzed by thematic framework analysis that comprised six stages (familiarization; coding; developing the framework; applying the framework; generating the matrix; interpretation).

resultsEleven rheumatologists (regional distribution - north 36%; midlands: 36%; south: 27%) participated (response rate: 24% of the sampling frame). The mean duration of the interviews was thirty minutes (range: 16 to 56 min). Thirteen factors that influenced anti-TNF prescribing decisions were categorized by three nested primary themes; specific influences were defined as subthemes: (i) External Environment Influences (National Institute for Health and Care Excellence Recommendations; Clinical Commissioning Groups; Cost Pressures; Published Clinical Evidence; Colleagues in Different Hospitals; Pharmaceutical Industry); (ii) Internal Hospital Influences (Systems to Promote Compliance with Clinical Recommendations; Internal Treatment Pathways; Hospital Culture); (iii) Individual-level Influences (Patient Influence; Clinical Autonomy; Consultant Experience; Perception of Disease Activity Score-28 (DAS28) Outcome).

conclusionsFactors that influenced anti-TNF prescribing decisions were multifaceted, seemed to vary by region, and may facilitate divergence from published clinical recommendations. Strategic behavior appeared to illustrate a conflict between uniform treatment recommendations and clinical autonomy. These influences may contribute to understanding sources of regional variation in clinical practice for rheumatoid arthritis.

Indexed as

Clinical recommendationsDAS28Health economicsNICEPrescribing behaviourQualitative studyRegional variationResource use, Rheumatoid arthritis

Identifiers

PMID31891115
PMCPMC6921483

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.