Prevalence-adjusted trends in U.S. healthcare spending on colorectal cancer, 1996-2016.
Bibliographic record
Abstract
e18819 Background: Colorectal cancer is rising in prevalence and associated with high healthcare costs. We estimated trends in the US healthcare spending in patients with colorectal cancer between 1996 and 2016. Methods: We used data on national healthcare spending developed by the Institute for Health Metrics and Evaluations for the Disease Expenditure Project. Corresponding US age-specific prevalence of colon cancer was estimated from the Global Burden of Diseases Study. Prevalence-adjusted, temporal trends in the US healthcare spending in patients with colorectal cancer, stratified by age groups ( < 20, 20-44, 45-64, >65) and by type of care (ambulatory, inpatient, emergency department, pharmaceutical prescriptions, nursing care and government administration) were estimated using joinpoint regression, expressed as annual percent change (APC) with 95% confidence intervals. Results: Overall, annual US healthcare spending on colorectal cancer increased from $8.85 billion (95% CI $8.17 billion, $9.53 billion) in 1996 to $10.5 billion (95% CI $9.35 billion, $11.7 billion) in 2016, with total costs increasing by 0.9%/year (95% CI 0.1%, 1.6%). After adjusting for colorectal cancer prevalence, the absolute per capita spending decreased from $8848 to $8427 and there has been no significant change over time (APC 0.3%, 95% CI, -0.2%, 0.8%). However, spending in patients > 65 decreased significantly by 1.3%/year (95% CI -2.2%, -0.5%). Inpatient care was the largest contributor to total colorectal cancer-related expenditures: in 2016, 65.9% (95% CI 59.5%, 71.0%) and 19.7% (95% CI 14.8%, 25.8%) of the total cost were spent on inpatient care and ambulatory care, respectively. Between 1996-2016, increases in the price and intensity of care (defined by the cost per encounter) was the largest positive driver of changing healthcare spending, accounting for $5.02 billion ($2.60, $7.33 billion). Conclusions: After adjusting for rising prevalence, US healthcare spending on colorectal cancer has not changed significantly since 1996, while the per capita cost continues to decrease, primarily in patients > 65 years old. Inpatient care accounts for the majority of colorectal cancer-related expenditures.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".