Evidence map›Paper›PMID 37315935›Full record

ArticleStatistics in medicine2023

Healthcare center clustering for Cox's proportional hazards model by fusion penalty.

Lili Liu, Kevin He, Di Wang, Shujie Ma, Annie Qu, Lu Lin, J Philip Miller, Lei Liu

Open access · greenAbstract read
In one paragraph

Article in Statistics in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.5field-weighted citation impact, top 17% of its field
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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Regression Trees With Fused Leaves.Statistics in medicine · 2024
    Article
  4. Health Care Provider Clustering Using Fusion Penalty in Quasi-Likelihood.Biometrical journal. Biometrische Zeitschrift · 2024
    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

8 authors at 4 institutions in 2 countries.

Lili LiuDivision of Biostatistics, Washington University in St. Louis, St. Louis, USA.
Kevin HeDepartment of Biostatistics, University of Michigan, Ann Arbor, USA.ORCID 0000-0002-8354-426X
Di WangDepartment of Biostatistics, University of Michigan, Ann Arbor, USA.
Shujie MaDepartment of Statistics, University of California, Riverside, California, USA.
Annie QuDepartment of Statistics, University of California, Irvine, California, USA.ORCID 0000-0002-8396-7828
Lu LinZhongtai Securities Institute for Financial Studies, Shandong University, Jinan, China.
J Philip MillerDivision of Biostatistics, Washington University in St. Louis, St. Louis, USA.
Lei LiuDivision of Biostatistics, Washington University in St. Louis, St. Louis, USA.ORCID 0000-0003-1844-338X
Shandong University · CNUniversity of California, Riverside · USUniversity of Michigan · USWashington University in St. Louis · US

Funding

WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8M
Improve Statistical Methods for Profiling of Healthcare ProvidersR01DK129539 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Zhi Kevin He · 2022 to 2026
$1.6M
High Dimensional Mediation Analysis for DNA Methylation Markers Mediating Cardiovascular Health Metrics and Cardiovascular DiseasesR21AG063370 · NIA · WASHINGTON UNIVERSITY · PI HOU, LIFANG, LIU, LEI · 2019 to 2020
$447k
Innovative Analytical Methods for Repeated Measures in the OHTS StudyR21EY031884 · NEI · WASHINGTON UNIVERSITY · PI GORDON, MAE O, LIU, LEI · 2020 to 2021
$439k
Resubmission: Latent Class Trajectory Analysis in the OHTS StudyR21EY033518 · NEI · WASHINGTON UNIVERSITY · PI GORDON, MAE O, LIU, LEI · 2022 to 2023
$430k
NCATS NIH HHS UL1 TR002345NEI NIH HHS R21 EY031884NEI NIH HHS R21 EY033518NIA NIH HHS R21 AG063370NIDDK NIH HHS R01 DK129539
6 · The paper itself

Abstract

There has been growing research interest in developing methodology to evaluate healthcare centers' performance with respect to patient outcomes. Conventional assessments can be conducted using fixed or random effects models, as seen in provider profiling. We propose a new method, using fusion penalty to cluster healthcare centers with respect to a survival outcome. Without any prior knowledge of the grouping information, the new method provides a desirable data-driven approach for automatically clustering healthcare centers into distinct groups based on their performance. An efficient alternating direction method of multipliers algorithm is developed to implement the proposed method. The validity of our approach is demonstrated through simulation studies, and its practical application is illustrated by analyzing data from the national kidney transplant registry.

Indexed as

AlgorithmsDelivery of Health CareCluster AnalysisComputer SimulationHumansProportional Hazards Modelsfixed effectsfusion penaltylatent classprovider profilingrandom effects

Identifiers

PMID37315935
PMCPMC10530598
OpenAlexW4380570841

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.