Socioeconomic Disparity Trends in Cancer Screening Among Women After Introduction of National Quality Indicators
Bibliographic record
Abstract
PURPOSE: Primary care physicians have an important role in encouraging adequate cancer screening. Disparities in cancer screening by socioeconomic status (SES) may affect presentation stage and cancer survival. This study aimed to examine whether breast, colorectal, and cervical cancer screening rates in women differed by SES and age, and whether screening rates and SES disparities changed after introduction of a primary care-based national quality indicator program. METHODS: This repeated cross-sectional study spanning 2002-2017 included all female Israeli residents in age ranges appropriate for each cancer screening assessed. SES was measured both as an individual-level variable based on exemption from copayments and as an area-level variable using census data. RESULTS: In 2017, the most recent year in the study period, screening rates among 1,529,233 women were highest for breast cancer (70.5%), followed by colorectal cancer (64.3%) and cervical cancer (49.6%). Women in the highest area-level SES were more likely to undergo cervical cancer screening compared with those in the lowest (odds ratio = 3.56; 99.9% CI, 3.47-3.65). Temporal trends showed that after introduction of quality indicators for breast and colorectal cancer screening in 2004 and 2005, respectively, rates of screening for these cancers increased, with greater reductions in disparities for the former. The quality indicator for cervical cancer screening was introduced in 2015, and no substantial changes have occurred yet for this screening. CONCLUSIONS: We found increased uptake and reduced socioeconomic disparities after introduction of cancer screening indicators. Recent introduction of a cervical cancer screening indicator may increase participation and reduce disparities, as has occurred for breast and colorectal cancer screening. These findings related to Israel's quality indicators program highlight the importance of primary care clinicians in increasing cancer screening rates to improve outcomes and reduce disparities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".