Health Care Utilization and Costs in Lung Cancer Screening Participants—A Propensity-Matched Economic Analysis
Bibliographic record
Abstract
Introduction: Lung cancer screening (LCS) for high-risk populations has been firmly established to reduce lung cancer mortality, but concerns exist regarding unintended downstream costs.Methods: Mean health care utilization and costs were compared in the Alberta Lung Cancer Screening Study in a cohort undergoing LCS versus a propensity-matched control group who did not.Results: A cohort of 651 LCS participants was matched to 336 unscreened controls.Over the study period (mean 3.6 y), a modest increase in the number of claims (22.4 versus 21.9 per person-year [PY]; D 0.50 [95% confidence interval: 0.15-0.86],p 0.006) and outpatient visits (4.01 versus 3.50 per PY; D 0.51 [0.37-0.65],p <0.0001), but not in inpatient admissions, was noted in the screened cohort.Claims payments, inpatient costs, and cancer care costs were similar in the screening arm versus the unscreened.Outpatient encounter costs per participant were higher in the screened group ($2662.18versus $2040.67 per PY; D $621.51 [1118.05 to 124.97], p 0.014).Removing the additional computed tomography screening examinations rendered differences not significant.Mean total costs were not significantly different at $6461.10 per PY in the screening group and $6125.31 in the unscreened group (D $335.79 [2009.65 to 1338.07], p 0.69).Conclusions: Modest increases in outpatient costs are noted in individuals undergoing LCS, in part attributable to the screening examinations, without differences in overall health care costs.Health care costs and utilization seem otherwise similar in individuals participating in LCS and those who do not.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".