Evidence map›Paper›PMID 28877694›Full record

ArticleBMC urology2017

Assembling and validating data from multiple sources to study care for Veterans with bladder cancer.

Florian R Schroeck, Brenda Sirovich, John D Seigne, Douglas J Robertson, Philip P Goodney

Open access · goldAbstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC urology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

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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

5 authors at 3 institutions in 1 country.

Florian R SchroeckWhite River Junction VA Medical Center, 215 N Main Street, White River Junction, VT, 05009, USA. florian.r.schroeck@dartmouth.edu.ORCID http://orcid.org/0000-0002-1860-2611
Brenda SirovichWhite River Junction VA Medical Center, 215 N Main Street, White River Junction, VT, 05009, USA.
John D SeigneSection of Urology, Dartmouth Hitchcock Medical Center, Lebanon, NH, USA.
Douglas J RobertsonWhite River Junction VA Medical Center, 215 N Main Street, White River Junction, VT, 05009, USA.
Philip P GoodneyWhite River Junction VA Medical Center, 215 N Main Street, White River Junction, VT, 05009, USA.
Dartmouth Institute for Health Policy and Clinical Practice · USDartmouth College · USDartmouth–Hitchcock Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the high prevalence of bladder cancer, research on optimal bladder cancer care is limited. One way to advance observational research on care is to use linked data from multiple sources. Such big data research can provide real-world details of care and outcomes across a large number of patients. We assembled and validated such data including (1) administrative data from the Department of Veterans Affairs (VA), (2) Medicare claims, (3) data abstracted by tumor registrars, (4) data abstracted via chart review from the national electronic health record, and (5) full text pathology reports.

methodsBased on these combined data, we used administrative data to identify patients with newly diagnosed bladder cancer who received care in the VA. To validate these data, we first compared the diagnosis date from the administrative data to that from the tumor registry. Second, we measured accuracy of identifying bladder cancer care in VA administrative data, using a random chart review (n = 100) as gold standard. Lastly, we compared the proportion of patients who received bladder cancer care among those who did versus did not have full text bladder pathology reports available, expecting that those with reports are significantly more likely to receive care in VA.

resultsOut of 26,675 patients, 11,323 (42%) had tumor registry data available. 90% of these patients had a difference of 90 days or less between the diagnosis dates from administrative and registry data. Among 100 patients selected for chart review, 59 received bladder cancer care in VA, 58 of which were correctly identified using administrative data (sensitivity 98%, specificity 90%). Receipt of bladder cancer care was substantially more common among those who did versus did not have bladder pathology available (96% vs. 43%, p < 0.001).

conclusionMerging administrative with electronic health record and pathology data offers new possibilities to validate the use of administrative data in bladder cancer research.

Indexed as

Data CollectionVeterans HealthAgedHumansRegistriesUnited StatesUrinary Bladder NeoplasmsBladder cancerCystoscopyElectronic health recordValidity

Identifiers

PMID28877694
PMCPMC5585934
OpenAlexW2753365655

What OpenQuestion holds

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LicenceCC BY
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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.