Evidence map›Paper›PMID 30945065›Full record

ArticleJournal of general internal medicine2019

Comparing Shared Patient Networks Across Payers.

Justin G Trogdon, W H Weir, S Shai, P J Mucha, T M Kuo, A M Meyer, K B Stitzenberg

Open access · bronzeAbstract read
In one paragraph

Article in Journal of general internal medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.4field-weighted citation impact, top 8% 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

18 citing papers in PubMed, 28 citations in OpenAlex.

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  17. Improving Network Science in Health Services Research.Journal of general internal medicine · 2019
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Justin G TrogdonDepartment of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. justintrogdon@unc.edu.
W H WeirCarolina Center for Interdisciplinary Applied Mathematics, Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
S ShaiDepartment of Mathematics and Computer Science, Wesleyan University, Marion, IN, USA.
P J MuchaCarolina Center for Interdisciplinary Applied Mathematics, Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
T M KuoLineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
A M MeyerIQVIA, Saint-Prex, Switzerland.
K B StitzenbergLineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
University of North Carolina at Chapel Hill · USIndiana Wesleyan University · US

Funding

Virology Research Program (Program 4)P30CA016086 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Deborah F. Tate · 1985 to 2026
$201.5M
NCI NIH HHS P30 CA016086
6 · The paper itself

Abstract

backgroundMeasuring care coordination in administrative data facilitates important research to improve care quality.

objectiveTo compare shared patient networks constructed from administrative claims data across multiple payers.

designSocial network analysis of pooled cross sections of physicians treating prevalent colorectal cancer patients between 2003 and 2013.

participantsSurgeons, medical oncologists, and radiation oncologists identified from North Carolina Central Cancer Registry data linked to Medicare claims (N = 1735) and private insurance claims (N = 1321). MAIN MEASURES: Provider-level measures included the number of patients treated, the number of providers with whom they share patients (by specialty), the extent of patient sharing with each specialty, and network centrality. Network-level measures included the number of providers and shared patients, the density of shared-patient relationships among providers, and the size and composition of clusters of providers with a high level of patient sharing.

resultsFor 24.5% of providers, total patient volume rank differed by at least one quintile group between payers. Medicare claims missed 14.6% of all shared patient relationships between providers, but captured a greater number of patient-sharing relationships per provider compared with the private insurance database, even after controlling for the total number of patients (27.242 vs 26.044, p < 0.001). Providers in the private network shared a higher fraction of patients with other providers (0.226 vs 0.127, p < 0.001) compared to the Medicare network. Clustering coefficients for providers, weighted betweenness, and eigenvector centrality varied greatly across payers. Network differences led to some clusters of providers that existed in the combined network not being detected in Medicare alone.

conclusionMany features of shared patient networks constructed from a single-payer database differed from similar networks constructed from other payers' data. Depending on a study's goals, shortcomings of single-payer networks should be considered when using claims data to draw conclusions about provider behavior.

Indexed as

Cohort StudiesColorectal NeoplasmsCommunity NetworksContinuity of Patient CareHumansInsurance Claim ReviewMedicareNorth CarolinaPractice Patterns, Physicians'RegistriesUnited Statescolorectal cancernetwork analysis

Identifiers

PMID30945065
PMCPMC6816773
OpenAlexW2933629300

What OpenQuestion holds

Textmetadata
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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.