Relationship Between Quality of Comorbid Condition Care and Costs for Cancer Survivors
Bibliographic record
Abstract
PURPOSE: To estimate the association between cancer survivors' comorbid condition care quality and costs; to determine whether the association differs between cancer survivors and other patients. METHODS: Using the SEER-Medicare-linked database, we identified survivors of breast, prostate, and colorectal cancers who were diagnosed in 2004, enrolled in Medicare fee-for-service for at least 12 months before diagnosis, and survived ≥ 3 years. Quality of care was assessed using nine process indicators for chronic conditions, and a composite indicator representing seven avoidable outcomes. Total costs on the basis of Medicare amount paid were grouped as inpatient and outpatient. We examined the association between care quality and costs for cancer survivors, and compared this association among 2:1 frequency-matched noncancer controls, using comparisons of means and generalized linear regressions. RESULTS: Our sample included 8,661 cancer survivors and 17,332 matched noncancer controls. Receipt of recommended care was associated with higher outpatient costs for eight indicators, and higher inpatient and total costs for five indicators. For three measures (visit every 6 months for patients with chronic obstructive pulmonary disease or diabetes, and glycosylated hemoglobin or fructosamine every 6 months for patients with diabetes), costs for cancer survivors who received recommended care increased less than for noncancer controls. The absence of avoidable events was associated with lower costs of each type. An annual eye examination for patients with diabetes was associated with lower inpatient costs. CONCLUSION: Higher-quality processes of care may not reduce short-term costs, but the prevention of avoidable outcomes reduces costs. The association between quality and cost was similar for cancer survivors and noncancer controls.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".