Evidence map›Paper›PMID 19178585›Full record

ArticleHealth services research2009

Method to develop health care peer groups for quality and financial comparisons across hospitals.

Margaret M Byrne, Christina N Daw, Harlan A Nelson, Tracy H Urech, Kenneth Pietz, Laura A Petersen

Abstract readComparative Study
In one paragraph

Article in Health services research, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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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

6 authors.

Margaret M ByrneDepartment of Epidemiology and Public Health, University of Miami, Miami, FL, USA.
Christina N Daw
Harlan A Nelson
Tracy H Urech
Kenneth Pietz
Laura A Petersen

Funding

Resource and QOL Consequences of Lung Cancer ScreeningK07CA101812 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BYRNE, MARGARET M. · 2003 to 2007
$649k
NCI NIH HHS K07 CA101812
6 · The paper itself

Abstract

objectiveTo develop and explore the characteristics of a novel "nearest neighbor" methodology for creating peer groups for health care facilities. DATA SOURCES: Data were obtained from the Department of Veterans Affairs (VA) databases. STATISTICAL METHODS AND

findingsPeer groups are developed by first calculating the multidimensional Euclidean distance between each of 133 VA medical centers based on 16 facility characteristics. Each medical center then serves as the center for its own peer group, and the nearest neighbor facilities in terms of Euclidean distance comprise the peer facilities. We explore the attributes and characteristics of the nearest neighbor peer groupings. In addition, we construct standard cluster analysis-derived peer groups and compare the characteristics of groupings from the two methodologies.

conclusionsThe novel peer group methodology presented here results in groups where each medical center is at the center of its own peer group. Possible advantages over other peer group methodologies are that facilities are never on the "edge" of a group and group size-and thus group dispersion-is determined by the researcher. Peer groups with these characteristics may be more appealing to some researchers and administrators than standard cluster analysis and may thus strengthen organizational buy-in for financial and quality comparisons.

Indexed as

Delivery of Health CareEconomics, HospitalQuality of Health CareResearch DesignCluster AnalysisDatabases as TopicHospitalsUnited StatesUnited States Department of Veterans Affairs

Identifiers

PMID19178585
PMCPMC2677055

What OpenQuestion holds

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Registered trials

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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.