Measuring Integration of Cancer Services to Support Performance Improvement: The CSI Survey
Bibliographic record
Abstract
OBJECTIVE: To develop a measure of cancer services integration (CSI) that can inform clinical and administrative decision-makers in their efforts to monitor and improve cancer system performance. METHODS: We employed a systematic approach to measurement development, including review of existing cancer/health services integration measures, key-informant interviews and focus groups with cancer system leaders. The research team constructed a Web-based survey that was field- and pilot-tested, refined and then formally conducted on a sample of cancer care providers and administrators in Ontario, Canada. We then conducted exploratory factor analysis to identify key dimensions of CSI. RESULTS: A total of 1,769 physicians, other clinicians and administrators participated in the survey, responding to a 67-item questionnaire. The exploratory factor analysis identified 12 factors that were linked to three broader dimensions: clinical, functional and vertical system integration. CONCLUSIONS: The CSI Survey provides important insights on a range of typically unmeasured aspects of the coordination and integration of cancer services, representing a new tool to inform performance improvement efforts.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".