Evidence map›Paper›PMID 25783775›Full record

ArticleHealth services research2015

On the Hospital Volume and Outcome Relationship: Does Specialization Matter More Than Volume?

Kris C L Lee, Kannan Sethuraman, Jongsay Yong

Abstract read
In one paragraph

Article in Health services research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  7. Measuring the Volume-Outcome Relation for Complex Hospital Surgery.Applied health economics and health policy · 2016
    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

3 authors.

Kris C L LeeGolden Dragon Centre, City University of Macau, Macau, China.
Kannan SethuramanMelbourne Business School, University of Melbourne, Carlton, VIC, Australia.
Jongsay YongFaculty of Business and Economics, University of Melbourne, Melbourne, VIC, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the relationship between hospital volume and outcome by focusing on alternative measures of volume that capture specialization and overall throughput of hospitals. DATA SOURCES/STUDY

settingHospital administrative data from the state of Victoria, Australia; data contain 1,798,474 admitted episodes reported by 135 public and private acute-care hospitals. STUDY

designThis study contrasts the volume-outcome relationship using regression models with different measures of volume; two-step and single-step risk-adjustment methods are used. DATA COLLECTION/EXTRACTION

methodsThe sample is restricted to ischemic heart disease (IHD) patients (ICD-10 codes: I20-I25) admitted during 2001/02 to 2004/05. PRINCIPAL

findingsOverall hospital throughput and degree of specialization display more substantive implications for the volume-outcome relationship than conventional caseload volume measure. Two-step estimation when corrected for heteroscedasticity produces comparable results to single-step methods.

conclusionsDifferent measures of volume could lead to vastly different conclusions about the volume-outcome relationship. Hospital specialization and throughput should both be included as measures of volume to capture the notion of size, focus, and possible congestion effects.

Indexed as

AgedAged, 80 and overAge FactorsComorbidityFemaleHospital MortalityHospitals, High-VolumeHospitals, SpecialHumansMaleMiddle AgedMyocardial IschemiaOutcome Assessment, Health CareOwnershipQuality of Health CareRisk Adjustmenthospital qualityHospital volume and outcomerisk adjustmentspecialization

Identifiers

PMID25783775
PMCPMC4693841

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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.