Minnesota: Leading the Way on Canadian Prescription Medicine Importation
Bibliographic record
Abstract
In the United States, about $160 billion is spent on prescription medicines each year, with Minnesotans spending about $3 billion. The costs of prescription medicines receive so much attention in large part because, although prescription medicine costs constitute only 10.5% of total health care spending, they account for 23% of the total out-of-pocket costs that people incur when purchasing health care. Minnesota has been a leader in controlling prescription medicine costs. It has aggressively used purchasing pools when possible, and encouraged the use of lower cost, generic prescription medicines when appropriate. Even with these efforts to control costs, prescription medicines were still becoming too costly for many Minnesotans to afford. Busloads of senior citizens headed north for Canada. Others used Internet pharmacies, some of which were unsafe. The need for lower cost prescription medicine alternatives and a desire to protect the safety of Minnesotans who seek them caused Governor Pawlenty, in September of 2003, to direct the Minnesota Department of Human Services to examine the feasibility of importing prescription medicines from Canada and other international sources. He directed the Commissioner of Human Services to examine methods to address the needs of Minnesota state employees, the citizens served through the state’s public assistance programs, and the state’s citizens at large. In response to this directive, a three-phase plan was developed. The plan called for the development of a website to empower Minnesota consumers to purchase mail-order prescription medicines for personal use from approved Canadian pharmacies; the option for Minnesota state employees to voluntarily obtain prescriptions for maintenance medications from Canadian pharmacies; and the establishment of a pilot project that allows Minnesotans to purchase Canadian prescription medicines from their local pharmacies.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.053 | 0.006 |
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".