Evidence map›Paper›PMID 32319525›Full record

ArticleInternational journal for quality in health care : journal of the International Society for Quality in Health Care2020

Understanding unwarranted variation in clinical practice: a focus on network effects, reflective medicine and learning health systems.

Femke Atsma, Glyn Elwyn, Gert Westert

Abstract read
In one paragraph

Article in International journal for quality in health care : journal of the International Society for Quality in Health Care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 3 pooled it
–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

48 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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

3 authors.

Femke AtsmaScientific Center for Quality of Healthcare, Radboud University Medical Center, Radboud Institute for Health Sciences, Geert Grooteplein Noord 21, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.
Glyn ElwynScientific Center for Quality of Healthcare, Radboud University Medical Center, Radboud Institute for Health Sciences, Geert Grooteplein Noord 21, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.
Gert WestertScientific Center for Quality of Healthcare, Radboud University Medical Center, Radboud Institute for Health Sciences, Geert Grooteplein Noord 21, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the past decades, extensive research has been performed on the phenomenon of unwarranted clinical variation in clinical practice. Many studies have been performed on signaling, describing and visualizing clinical variation. We argue that it is time for next steps in practice variation research. In addition to describing and signaling variation patterns, we argue that a better understanding of causes of variation should be gained. Moreover, target points for improving and decreasing clinical variation should be created. Key elements in this new focus should be research on the complex interaction of networks, reflective medicine, patient beliefs and objective criteria for treatment choices. By combining these different concepts, alternative research objectives and new targets for improving and reducing unwarranted variation may be defined. In this perspective, we reflect on these concepts and propose target points for future research.

Indexed as

Learning Health SystemHumansnetworksobjective clinical criteriapractice variationsquality improvementresearch agendashared decision-making

Identifiers

PMID32319525
PMCPMC7270826

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.