Evidence map›Paper›PMID 30318592›Full record

ArticleHealth services research2019

What drives variation in spending for breast cancer patients within geographic regions?

Anna D Sinaiko, Alyna T Chien, Michael J Hassett, Pragya Kakani, Danielle Rodin, David J Meyers, Belen Fraile, Meredith B Rosenthal, Mary Beth Landrum

Abstract read
In one paragraph

Article in Health services research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

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

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

  1. Pooled it
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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

9 authors.

Anna D SinaikoDepartment of Health Policy and Management, Harvard T. H. Chan School of Public Health, Boston, Massachusetts.ORCID 0000-0003-4230-1947
Alyna T ChienHarvard Medical School, Boston, Massachusetts.
Michael J HassettDepartment of Medicine, Harvard Medical School, Boston, Massachusetts.
Pragya KakaniHarvard University, Cambridge, Massachusetts.
Danielle RodinDepartment of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada.
David J MeyersDepartment of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island.ORCID 0000-0002-4081-1751
Belen FraileDepartment of Finance, Value and Population Health Management, Dana Farber Cancer Institute, Boston, Massachusetts.
Meredith B RosenthalDepartment of Health Policy and Management, Harvard T. H. Chan School of Public Health, Boston, Massachusetts.
Mary Beth LandrumDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts.

Funding

Laura and John Arnold Foundation
6 · The paper itself

Abstract

objectiveTo estimate and describe factors driving variation in spending for breast cancer patients within geographic region. DATA SOURCE: Surveillance, Epidemiology, and End Results (SEER)-Medicare database from 2009-2013. STUDY

designThe proportion of variation in monthly medical spending within geographic region attributed to patient and physician factors was estimated using multilevel regression models with individual patient and physician random effects. Using sequential models, we estimated the contribution of differences in patient and disease characteristics or use of cancer treatment modalities to patient-level and physician-level variance in spending. Services associated with high spending physicians were estimated using linear regression. DATA EXTRACTION

methodA total of 20 818 women with a breast cancer diagnosis in 2010-2011. PRINCIPAL

findingsWe observed substantial between-patient and between-provider variation in spending following diagnosis and at the end-of-life. Immediately following diagnosis, 48% of between-patient and 31% of between-physician variation were driven by differences in delivery of cancer treatment modalities to similar patients. At the end-of-life, patients of high spending physicians had twice as many inpatient days, double the chemotherapy spending, and slightly more hospice days.

conclusionsSimilar patients receive very different treatments, which yield significant differences in spending. Efforts to reduce unwanted variation may need to target treatment choices within patient-doctor discussions.

Indexed as

Breast NeoplasmsFemaleHealth Care CostsHealth ExpendituresHumansMedical OncologyQuality of Health CareRegional Health PlanningUnited Statesbreast cancerspendingvariation

Identifiers

PMID30318592
PMCPMC6338302

What OpenQuestion holds

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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.