Evidence map›Paper›PMID 25128055›Full record

ArticleValue in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research2014

Physician social networks and variation in rates of complications after radical prostatectomy.

Craig Evan Pollack, Hao Wang, Justin E Bekelman, Gary Weissman, Andrew J Epstein, Kaijun Liao, Eva H Dugoff, Katrina Armstrong

Abstract read
In one paragraph

Article in Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
–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

31 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Applications of network analysis to routinely collected health care data: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2018
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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

8 authors.

Craig Evan PollackJohns Hopkins University School of Medicine and Bloomberg School of Public Health, Baltimore, MD, USA; Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA; Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA. Electronic address: cpollac2@jhmi.edu.
Hao WangSidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA.
Justin E BekelmanUniversity of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Gary WeissmanHospital of the University of Pennsylvania, Philadelphia, PA.
Andrew J EpsteinUniversity of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Kaijun LiaoUniversity of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Eva H DugoffUniversity of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Katrina ArmstrongMassachussetts General Hospital, Boston, MA.

Funding

TRAINING IN HEALTH SERVICES RESEARCHT32HS000029 · AHRQ · JOHNS HOPKINS UNIVERSITY · PI DY, SYDNEY MORSS · 1987 to 2024
$8.3M
A Network Analytic Approach to Modeling Variation in Prostate Cancer CareK07CA151910 · NCI · JOHNS HOPKINS UNIVERSITY · PI POLLACK, CRAIG EVAN · 2011 to 2015
$780k
AHRQ HHS T32 HS000029NCI NIH HHS K07 CA151910
6 · The paper itself

Abstract

objectivesVariation in care within and across geographic areas remains poorly understood. The goal of this article was to examine whether physician social networks-as defined by shared patients-are associated with rates of complications after radical prostatectomy.

methodsIn five cities, we constructed networks of physicians on the basis of their shared patients in 2004-2005 Surveillance, Epidemiology and End Results-Medicare data. From these networks, we identified subgroups of urologists who most frequently shared patients with one another. Among men with localized prostate cancer who underwent radical prostatectomy, we used multilevel analysis with generalized linear mixed-effect models to examine whether physician network structure-along with specific characteristics of the network subgroups-was associated with rates of 30-day and late urinary complications, and long-term incontinence after accounting for patient-level sociodemographic, clinical factors, and urologist patient volume.

resultsNetworks included 2677 men in five cities who underwent radical prostatectomy. The unadjusted rate of 30-day surgical complications varied across network subgroups from an 18.8 percentage-point difference in the rate of complications across network subgroups in city 1 to a 26.9 percentage-point difference in city 5. Large differences in unadjusted rates of late urinary complications and long-term incontinence across subgroups were similarly found. Network subgroup characteristics-average urologist centrality and patient racial composition-were significantly associated with rates of surgical complications.

conclusionsAnalysis of physician networks using Surveillance, Epidemiology and End Results-Medicare data provides insight into observed variation in rates of complications for localized prostate cancer. If validated, such approaches may be used to target future quality improvement interventions.

Indexed as

Social NetworkingAgedCohort StudiesFollow-Up StudiesHumansLinear ModelsMaleMedicarePhysiciansPostoperative ComplicationsProstatectomyProstatic NeoplasmsRetrospective StudiesSEER ProgramTime FactorsUnited Statescancerclaims datahealth servicesoutcomes research

Identifiers

PMID25128055
PMCPMC4135395

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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.