Integrated access to cancer screening: expanding access for cervical and colorectal cancer screening in rural and remote Northern Alberta, Canada using a mobile service to bring cancer screening closer to home
Bibliographic record
Abstract
BACKGROUND: The goal of the Integrated Access to Cancer Screening (IACS) initiative was to help reduce the disparity in cancer screening participation across Alberta by implementing an integrated mobile service delivery model for breast, cervical, and colorectal cancer screening in rural and remote communities in Northern Alberta, performed by Nurse Practitioners (NPs) that addressed barriers to access. The aim of this study was to evaluate the outcomes and impact the IACS initiative had on the communities and residents of Northern Alberta. This article describes the initiative design, implementation, outcomes, and impact of the initiative. METHODS: The IACS model was implemented in a total of 36 visited communities in Northern Alberta from December 2020 to December 2021. The impact of the IACS initiative was measured using a mixed methods approach. The participation rate, cancer screening overdue status, and connection to a PCP were assessed using quantitative data collected through the existing clinical information system. Patient and provider feedback were collected from opened-ended surveys, and all data was analyzed by the research team. This study evaluated the impact the IACS initiative had on patient cancer screening participation and cancer screening knowledge, addressing known barriers to service delivery in rural and remote Northern Alberta, and to understand how this service might be sustained for future operation. RESULTS: Six hundred fifty-three people participated in screening offered through the IACS initiative. 99% of Pap screenings offered to patients were accepted, and 98% of FIT kits were accepted from the NPs, with a completion rate of 84%. The clinical data and survey responses from patients and providers indicated support for sustaining the IACS initiative. The IACS model of screening was favoured by most female patients. It also increased screening uptake in the communities we visited in the North Zone of Alberta, where screening rates are low. CONCLUSION: These findings highlight that the IACS initiative was well-received and brought value to underserved communities in Northern Alberta. The IACS model effectively facilitated screening for those who were overdue or have never been screened before. The reach of the IACS model was broader than anticipated, with those who are attached to a PCP also finding the integrated mobile screening model beneficial, bringing the services closer to home.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".