Two Innovative Cancer Care Programs Have Potential to Reduce Utilization and Spending
Bibliographic record
Abstract
BACKGROUND: Cancer patients often present to the emergency department (ED) and hospital for symptom management, but many of these visits are avoidable and costly. OBJECTIVE: We assessed the impact of 2 Health Care Innovation Awards that used an oncology medical home model [Community Oncology Medical Home (COME HOME)] or patient navigation model [Patient Care Connect Program (PCCP)] on utilization and spending. METHODS: Participants in COME HOME and PCCP models were matched to similar comparators using propensity scores. We analyzed utilization and spending outcomes using Medicare fee-for-service claims with unadjusted and adjusted difference-in-differences models. RESULTS: In the adjusted models, both COME HOME and PCCP were associated with fewer ED visits than a comparison group (15 and 22 per 1000 patients/quarter, respectively; P<0.01). In addition, COME HOME had lower spending ($675 per patient/quarter; P<0.01), and PCCP had fewer hospitalizations (11 per 1000 patients/quarter; P<0.05), relative to the comparison group. Among patients undergoing chemotherapy, fewer COME HOME and PCCP patients had ED visits (18 and 28 per 1000 patients/quarter, respectively; P<0.01) and fewer PCCP patients had hospitalizations (13 per 1000 patients/quarter; P<0.05), than comparison patients. CONCLUSIONS: The oncology medical home and patient navigator programs both showed reductions in spending or utilization. Adoption of such programs holds promise for improving cancer care.
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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) | 0.000 | 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 | 0.000 |
| 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".