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Record W3167113791 · doi:10.1093/ecco-jcc/jjab076.749

P629 Rural-urban inequities in Inflammatory Bowel Disease health care access: a population-based retrospective cohort study from a Western Canadian Province

2021· article· en· W3167113791 on OpenAlexaffabout
Juan Nicolás Peña-Sánchez, Jessica Amankwah Osei, Noelle Rohatinsky, Xuedan Lu, Tracie Risling, Ian Boyd, Karen Wicks, Carol-Lynne Quintin, Alison L. Dickson, Sharyle Fowler

Bibliographic record

VenueJournal of Crohn s and Colitis · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsSaskatchewan Health AuthoritySaskatchewan Health Quality CouncilCrohn's and Colitis CanadaUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineInflammatory bowel diseaseRetrospective cohort studyHealth careIncidence (geometry)PopulationHazard ratioResidenceCohortUlcerative colitisDiseasePediatricsEnvironmental healthConfidence intervalFamily medicineDemographyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Inflammatory bowel disease (IBD) is a chronic digestive condition with significant complications if left untreated. Rural dwellers face barriers to access specialised health care, which is located in larger urban centres. We aimed to contrast health care utilization (outpatient gastroenterology visits, colonoscopies, claims for IBD medications, IBD-specific and IBD-related hospitalizations, and surgeries for IBD) between rural and urban residents diagnosed with IBD in the Canadian province of Saskatchewan (SK). Methods We completed a population-based retrospective study using SK administrative health databases (hospital discharge abstracts, medication claims, and physician billings) between the 1999 to 2016 fiscal years. A validated IBD algorithm requiring multiple health care contacts was used for case ascertainment. IBD incidence cases were identified by requiring eight years of continuous health care coverage without IBD health care contacts before the date of diagnosis. Cases were assigned to a rural or urban location based on their residential postal codes at the date of IBD diagnosis. Study outcomes were measured from IBD diagnosis to the end of the study period or end of health care coverage. Cox proportional regression models were used to evaluate the associations between rural-urban residence and each study outcome. Models were adjusted by sex, age, neighbourhood income quintile at IBD diagnosis, and disease type (Crohn’s disease and ulcerative colitis). Adjusted hazard ratios (HR) and 95% confidence intervals (95%CI) were reported. Results We identified 5,173 IBD incident cases in SK between 1999 and 2016; 1,544 (29.8%) individuals were living in rural locations at the date of diagnosis. Compared to urban dwellers, rural residents had lower gastroenterology visits (HR=0.82, 95%CI 0.77–0.88) and higher 5-aminosalicylic acid (5-ASA) claims (HR=1.10, 95%CI 1.02–1.18). Furthermore, rural residents had a higher risk of IBD-specific (HR=1.23, 95%CI 1.13–1.34) and IBD-related (HR=1.20, 95%CI 1.11–1.31) hospitalizations than their urban counterparts. We did not observe significant rural-urban differences in the access to colonoscopies, biologic and immune modulator therapies, and surgeries for IBD. Conclusion We identified rural-urban disparities in IBD health care access, specifically, lower outpatient gastroenterology visits, higher 5-ASA claims, and a higher risk of hospitalizations for individuals living in rural locations at IBD diagnosis. Our findings reflect rural-urban inequities in the access to IBD care that require the attention of health care providers and decision-makers to promote health care innovation and equitable management of patients with IBD living in rural areas.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.017
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.007
Science and technology studies0.0040.001
Scholarly communication0.0020.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.250
Teacher spread0.244 · 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".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

Explore more

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