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Record W2891497451 · doi:10.23889/ijpds.v3i4.967

Using data to explore vulnerable women's utilization of maternity health care

2018· article· en· W2891497451 on OpenAlexaffabout
Mahnoush Rostami, Paola Charland, Ameera Memon

Bibliographic record

VenueInternational Journal for Population Data Science · 2018
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsAlberta Health Services
Fundersnot available
KeywordsMedicineSocioeconomic statusPovertyDisadvantagedPrenatal careHealth careEnvironmental healthNursingFamily medicinePopulationEconomic growth

Abstract

fetched live from OpenAlex

IntroductionInequitable access to appropriate maternity health care is an issue for vulnerable women that negatively impacts health outcomes. As part of a feasibility study on midwifery services for vulnerable women, we used administrative data to further our understanding of socially disadvantaged women’s use of the primary care system during pregnancy. Objectives and ApproachTo better understand maternity health service utilization and social vulnerability of women in Calgary Alberta, a research partnership was formed between Alberta Health Services and a social service agency that serves clients experiencing, poverty, and food insecurity and were at risk for homelessness. This multi-phase study linked postal code data to data from provincial databases. Variables included socioeconomic characteristics, prenatal health care utilization and maternal and birth outcomes for the years 2013 to 2015. ResultsDatabases accessed included the Alberta Perinatal Health Program (APHP), Alberta Health Practitioner Claims Database, AHS Admission Discharge Transfer Database, Discharge Abstracts Database, National Ambulatory Care Reporting, and Provincial Registry Database. Data linkages yielded a total sample size of 7493 women, with 15.5% of women qualifying as ‘socially vulnerable’. Women receiving social assistance are relatively younger, experience more pregnancies, have higher antenatal risk scores and accessed maternal and emergency care more often and later in their pregnancy than those women who are not accessing social services. Our results suggest women living in vulnerable circumstances experience higher risk pregnancies that those not living in vulnerable circumstances. Therefore a maternity care model such as midwifery, which uses a holistic approach to care may be beneficial for vulnerable women. Conclusion/ImplicationsFindings from our study confirm that women experiencing poor social circumstances are at increased risk for complications during pregnancy and birth. Therefore, we need to further investigate utilizing maternity models of care that serve both the maternal health needs and the social needs of this population.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.450
Threshold uncertainty score0.894

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.011
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.767
GPT teacher head0.638
Teacher spread0.129 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2018
Admission routes2
Has abstractyes

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