Inconsistencies in eligibility criteria for medication assessment programs
Bibliographic record
Abstract
I found the January/February 2014 issue of CPJ to be fabulous. I literally read the issue from cover to cover. Kudos to all of the authors and editors. I had one comment on Pammett and Jorgenson’s1 article about eligibility requirements for community pharmacy medication review services. Table 1 in this article summarizes community pharmacy medication review programs in Canada. I note that the eligibility requirements for the Saskatchewan Medication Assessment Program (SMAP) in the table are missing a bit of information—not all individuals age 65 and over and living in the community can access this program. While our pharmacy has embraced the new Medication Assessment Program, it is unfortunate that we cannot provide this service to the 40% of our patients who are First Nations individuals, due to their federal (rather than provincial) drug coverage. In October 2013, I forwarded correspondence to a variety of stakeholders requesting that SMAP coverage be extended to all residents of the province. The only reply I received was from Saskatchewan Health’s Drug Plan and Extended Benefits Branch, which stated, “A decision on the provision of professional pharmacy services such as medication assessments to First Nations individuals would rest with the NIHB [Non-Insured Health Benefits program] at Health Canada.” I have no expectations of any response from NIHB. The conclusion of Pammett and Jorgenson’s article states, “The eligibility criteria used by provincially funded medication review programs in Canada are inconsistent and highly variable, raising doubt that all patients in need of such services are eligible to receive them as an insured health benefit.” Isn’t it unfortunate that across Canada we have such inconsistencies and that even within provinces there are ethnicity-based gaps in program access!
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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 | 0.288 | 0.520 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.013 | 0.009 |
| Research integrity | 0.012 | 0.016 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".