Evidence map›Paper›PMID 27624875›Full record

ArticleHealth services research2017

Socioeconomic Differences in Use of Low-Value Cancer Screenings and Distributional Effects in Medicare.

Wendy Yi Xu, Jeah Kyoungrae Jung

Abstract read
In one paragraph

Article in Health services research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 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

2 authors.

Wendy Yi XuDivision of Health Services Management and Policy, College of Public Health, The Ohio State University, Cunz Hall 208, 1841 Neil Avenue, Columbus, 43210, OH.
Jeah Kyoungrae JungDepartment of Health Policy and Administration, College of Health and Human Development, The Pennsylvania State University, University Park, PA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveConsuming low-value health care not only highlights inefficient resource use but also brings an important concern regarding the economics of disparities. We identify the relation of socioeconomic characteristics to the use of low-value cancer screenings in Medicare fee-for-service (FFS) settings, and quantify the amount subsidized from nonusers and taxpayers to users of these screenings. DATA SOURCES: 2007-2013 Medicare Current Beneficiary Survey, Medicare FFS claims, and the Area Health Resource Files. STUDY

designOur sample included enrollees in FFS Part B for the entire calendar year. We excluded beneficiaries with a claims-documented or self-reported history of targeted cancers, or those enrolled in Medicaid or Medicare Advantage plans. We identified use of low-value Pap smears, mammograms, and prostate-specific antigen tests based on established algorithms, and estimated a logistic model with year dummies separately for each test. DATA COLLECTION/EXTRACTION

methodsSecondary data analyses. PRINCIPAL

findingsWe found a statistically significant positive association between privileged socioeconomic characteristics and use of low-value screenings. Having higher income and supplemental private insurance strongly predicted more net subsidies from Medicare.

conclusionsFFS enrollees who are better off in terms of sociodemographic characteristics receive greater subsidies from taxpayers for using low-value cancer screenings.

Indexed as

AgedAged, 80 and overAge FactorsEarly Detection of CancerFee-for-Service PlansFemaleHumansIncomeMaleMammographyMedicarePapanicolaou TestProstate-Specific AntigenSocioeconomic FactorsUnited StatesProstate-Specific AntigenDistributional effectslow-value cancer screeningsMedicare

Identifiers

PMID27624875
PMCPMC5583315

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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.