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Record W2605887500 · doi:10.23889/ijpds.v1i1.133

CanIMPACT: Understanding complexities, variation, and disparities in the breast cancer care continuum in Five Canadian provinces using administrative data

2017· article· en· W2605887500 on OpenAlexaffabout
Patti A. Groome, Marcy Winget, Li Jiang, Kathleen Decker, Cynthia Kendell, Monika K. Krzyzanowska, Dongdong Li, Aïsha Lofters, Mary L. McBride, Nicole Mittmann, Rahim Moineddin, Geoff Porter, Donna Turner, Robin Urquhart, Eva Grunfeld

Bibliographic record

VenueInternational Journal for Population Data Science · 2017
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsQueen's UniversityCancer Care OntarioUniversity Health NetworkDalhousie UniversityBC Cancer AgencyCancerCare Manitoba
Fundersnot available
KeywordsMedicineBreast cancerFamily medicineHealth careContext (archaeology)CensusCancerGeographyEnvironmental healthPopulationEconomic growth

Abstract

fetched live from OpenAlex

ABSTRACT
 ObjectiveCanIMPACT is a multi-province Canadian research team funded to understand the interplay between primary and oncology breast cancer care. A first step was to describe current practice and inter/intra-provincial care variation across the care continuum using provincial administrative health data. Here we describe the inter-provincial process and analysis plans.
 ApproachOur multi-disciplinary team includes five Canadian provinces: British Columbia, Alberta, Manitoba, Ontario and Nova Scotia. Cohorts consist of all breast cancers diagnosed from 2007 to at least 2011 in each of the five provinces. Common databases include cancer registries, census area-level income and rurality, outpatient physician claims, ambulatory care and inpatient hospitalizations. Other databases with laboratory, pharmacy, emergency services, and immigration data were available in some provinces. Common data elements across provincial datasets were identified, and a standardized methodology was developed.
 ResultsCommon data processing and analysis plans were finalized over 24 months; provinces refined details as per local context while maximizing methodological comparability. Basic descriptive analyses plus 18 phase-specific and 3 longitudinal analyses have been planned. Six plans for the diagnostic phase focus on identifying modifiable disparities in access and outcomes; 8 plans for the treatment phase focus on variation in chemotherapy treatment patterns, quality/safety, and utilization of primary care services; 4 plans for the survivorship phase focus on adherence to guidelines for follow-up breast cancer care, other chronic diseases and preventive care; 3 longitudinal analyses assess factors related to changes in utilization of chronic disease services over the cancer care continuum.
 ConclusionsWe have shown it is feasible to develop and standardize data processing and analyses across multiple provinces to address important cancer care questions across the continuum. This work will inform comparisons and improvements in Canadian cancer care. This effort has also helped increase research capacity in health services research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.522
GPT teacher head0.517
Teacher spread0.004 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes2
Has abstractyes

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