Predictors of timely follow‐up after abnormal cancer screening among women seeking care at urban community health centers
Bibliographic record
Abstract
BACKGROUND: We sought to measure time and identify predictors of timely follow-up among a cohort of racially/ethnically diverse inner city women with breast and cervical cancer screening abnormalities. METHODS: Eligible women had an abnormality detected on a mammogram or Papanicolaou (Pap) test between January 2004 and December 2005 in 1 of 6 community health centers in Boston, Massachusetts. Retrospective chart review allowed us to measure time to diagnostic resolution. We used Cox proportional hazards models to develop predictive models for timely resolution (defined as definitive diagnostic services completed within 180 days from index abnormality). RESULTS: Among 523 women with mammography abnormalities and 474 women with Pap test abnormalities, >90% achieved diagnostic resolution within 12 months. Median time to resolution was longer for Pap test than for mammography abnormalities (85 vs 27 days). Site of care, rather than any sociodemographic characteristic of individuals, including race/ethnicity, was the only significant predictor of timely follow-up for both mammogram and Pap test abnormalities. CONCLUSIONS: Site-specific community-based interventions may be the most effective interventions to reduce cancer health disparities when addressing the needs of underserved populations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".