Evidence map›Paper›PMID 31136047›Full record

ReviewJournal of evaluation in clinical practice2020

Unwarranted clinical variation in health care: Definitions and proposal of an analytic framework.

Kim Sutherland, Jean-Frederic Levesque

Abstract readReview
In one paragraph

Review in Journal of evaluation in clinical practice, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
88citing papers in PubMed, 2 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

88 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  17. Advancing Methods to Study Clinical Variation in Healthcare.Journal of evaluation in clinical practice · 2026
    Review
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28 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Kim SutherlandAgency for Clinical Innovation, Chatswood, New South Wales, Australia.ORCID 0000-0003-1327-090X
Jean-Frederic LevesqueAgency for Clinical Innovation, Chatswood, New South Wales, Australia.

Funding

HARC fellowshipNSW Health Unwarranted Clinical Variation TaskforceSax Institute, NSW
6 · The paper itself

Abstract

RATIONALE, AIMS, AND

objectivesUnwarranted clinical variation is a topic of heightened interest in health care systems around the world. While there are many publications and reports on clinical variation, few studies are conceptually grounded in a theoretical model. This study describes the empirical foundations of the field and proposes an analytic framework.

methodStructured construct mapping of published empirical studies which explicitly address unwarranted clinical variation.

resultsA total of 190 studies were classified in terms of three key dimensions: perspective (assessing variation across geographical areas or across providers); criteria for assessment (measuring absolute variation against a standard, or relative variation within a comparator group); and object of analysis (using process, structure/resource, or outcome metrics).

conclusionConsideration of the results of the mapping exercise-together with a review of adjustment, explanatory and stratification variables, and the factors associated with residual variation-informed the development of an analytic framework. This framework highlights the role that agency and motivation, evidence and judgement, and personal and organizational capacity play in clinical decision making and reveals key facets that distinguish warranted from unwarranted clinical variation. From a measurement perspective, it underlines the need for careful consideration of attribution, aggregation, models of care, and temporality in any assessment.

Indexed as

Clinical Decision-MakingDelivery of Health CareHumansframeworkperformance measurementquality improvementunwarranted clinical variation

Identifiers

PMID31136047
PMCPMC7317701

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.