Evidence map›Paper›PMID 39145149›Full record

ArticleHealth services & outcomes research methodology2024

Limitations of the Inter-Unit Reliability: A Set of Practical Examples.

Nicholas Hartman, Vahakn B Shahinian, Valarie B Ashby, Katrina J Price, Kevin He

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Health services & outcomes research methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Nicholas HartmanDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, U.S.A.
Vahakn B ShahinianKidney Epidemiology and Cost Center, University of Michigan, Ann Arbor, MI, U.S.A.
Valarie B AshbyDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, U.S.A.
Katrina J PriceDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, U.S.A.
Kevin HeDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, U.S.A.

Funding

Improve Statistical Methods for Profiling of Healthcare ProvidersR01DK129539 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Zhi Kevin He · 2022 to 2026
$1.6M
NIDDK NIH HHS R01 DK129539
6 · The paper itself

Abstract

Healthcare quality measures are statistics that serve to evaluate healthcare providers and identify those that need to improve their care. Before using these measures in clinical practice, developers and reviewers assess measure reliability, which describes the degree to which differences in the measure values reflect actual variation in healthcare quality, as opposed to random noise. The Inter-Unit Reliability (IUR) is a popular statistic for assessing reliability, and it describes the proportion of total variation in a measure that is attributable to between-provider variation. However, Kalbfleisch, He, Xia, and Li (2018) [

Indexed as

Healthcare Quality MeasuresProvider ProfilingQuality of CareReliabilityRisk Adjustment

Identifiers

PMID39145149
PMCPMC11323040

What OpenQuestion holds

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LicenceTDM
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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.