Evidence map›Paper›PMID 25443905›Full record

ArticleUrology2014

Technology diffusion and prostate cancer quality of care.

Florian R Schroeck, Samuel R Kaufman, Bruce L Jacobs, Ted A Skolarus, Yun Zhang, Brent K Hollenbeck

Abstract read
In one paragraph

Article in Urology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 2 pooled it
4.6field-weighted citation impact, top 5% 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

3 citing papers in PubMed, 2 syntheses or guidelines pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Editorial comment.Urology · 2014
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Florian R SchroeckDivision of Health Services Research, Department of Urology, University of Michigan, Ann Arbor, MI; Division of Urologic Oncology, Department of Urology, University of Michigan, Ann Arbor, MI.
Samuel R KaufmanDivision of Health Services Research, Department of Urology, University of Michigan, Ann Arbor, MI.
Bruce L JacobsDepartment of Urology, University of Pittsburgh School of Medicine, Pittsburgh, PA.
Ted A SkolarusDivision of Health Services Research, Department of Urology, University of Michigan, Ann Arbor, MI; Division of Urologic Oncology, Department of Urology, University of Michigan, Ann Arbor, MI; Center for Clinical Management Research, Health Services Research and Development Service, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI.
Yun ZhangDivision of Health Services Research, Department of Urology, University of Michigan, Ann Arbor, MI.
Brent K HollenbeckDivision of Health Services Research, Department of Urology, University of Michigan, Ann Arbor, MI; Division of Urologic Oncology, Department of Urology, University of Michigan, Ann Arbor, MI. Electronic address: bhollen@med.umich.edu.
University of Michigan · USUniversity of Pittsburgh · US

Funding

University of Pittsburgh Clinical and Translational Science InstitutionKL2TR000146 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2012 to 2015
$8.7M
Uro Translational Research and Clinical Research Training (UroTRACT)T32DK007782 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI WEI, JOHN T · 2000 to 2019
$2.9M
HSRD VA IK2 HX001162NCATS NIH HHS KL2 TR000146NCATS NIH HHS KL2TR000146NIDDK NIH HHS T32 DK007782NIDDK NIH HHS T32DK07782
6 · The paper itself

Abstract

objectiveTo evaluate the association of technological capacity with prostate cancer quality of care. Technological capacity was conceptualized as a market's ability to provide prostate cancer treatment with new technology, including robotic prostatectomy and intensity-modulated radiotherapy (IMRT).

methodsIn this retrospective cohort study, we used data from the Surveillance, Epidemiology, and End Results-Medicare linked database from 2004 to 2009 to identify men with newly diagnosed prostate cancer (n = 46,274). We measured technological capacity as the number of providers performing robotic prostatectomy or IMRT per population in a health care market. We used multilevel logistic regression analysis to assess the association of technological capacity with receiving quality care according to a set of nationally endorsed quality measures, while adjusting for patient and market characteristics.

resultsOverall, our findings were mixed with only subtle differences in quality of care comparing high-tech with low-tech markets. High robotic prostatectomy capacity was associated with better adherence to some quality measures, such as avoiding unnecessary bone scans (79.8% vs 73.0%; P = .003) and having follow-up with urologists (67.7% vs 62.6%; P = .023). However, for most measures, neither high robotic prostatectomy nor high-IMRT capacity was associated with significant increases in adherence rates. In fact, for 1 measure (treatment by a high-volume provider), high-IMRT capacity was associated with lower performance (23.4% vs 28.5%; P <.001).

conclusionOur findings suggest that new technology is not clearly associated with higher quality of care. To improve quality, more specific efforts will be needed.

Indexed as

Diffusion of InnovationHumansLogistic ModelsMaleProstateProstatic NeoplasmsQuality of Health CareRadiotherapy, Intensity-ModulatedRetrospective StudiesRobotic Surgical ProceduresSEER ProgramTreatment OutcomeUnited States

Identifiers

PMID25443905
PMCPMC4254669
OpenAlexW2056535858

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.