The Lack of Price Signals in Canadian Healthcare: A Case Study of High Ileostomy Output in Colorectal Surgery Patients and The Case for Explicit Cost Integration in Canadian Healthcare Decision Making
Bibliographic record
Abstract
Healthcare is the most critical social program in Canada; however, it is under increasing pressure to deliver a high volume of services at a high level of quality within a limited budget. This challenge is complicated because the cost of healthcare in Canada is largely hidden. While we may be able to measure aggregate cost in government budgets, understanding healthcare costs on a granular and episodic level is difficult. No money changes hands at the point of care and patients and physicians have little understanding of the cost of different tests and treatments. These hidden costs hamper decision making, resulting in care that largely ignores cost when choosing amongst different investigation and treatment options. From an economic perspective, the lack of price signals results in a loss of consumer and producer surplus and (or in other words, economic efficiency). Without price signals or market mechanisms to help guide the allocation of resources there is no way to assure that healthcare services (be it an appointment, a test, or a treatment) are allocated to those who place the highest value on that service at the least cost. Measured costs may not take this loss of consumer and producer surplus into account, and thus any estimates of cost in Canadian healthcare are likely underestimates as the lack of market mechanisms masks this deadweight loss. Policies that explicitly acknowledge and integrate cost into healthcare are required to increase efficiency. [vii] Such policies can help the healthcare system to run more sustainably, and would encourage cost-effective treatment strategies while avoiding tests and interventions that may have high cost but are unlikely to change treatments or outcomes.
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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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.000 | 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".