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Record W314854400

Cost Recovery and the Future of the Medical Device Regulation Program in Canada

2008· article· en· W314854400 on OpenAlexvenueaboutno aff
Sheri A. Alpert

Bibliographic record

VenueHealth law review · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
Fundersnot available
KeywordsRevenueBusinessGovernment (linguistics)CertificationTreasurySubsidyFinanceEconomicsLawPolitical scienceManagement
DOInot available

Abstract

fetched live from OpenAlex

It is a perennial problem that some government programs seemingly have an abundance of financial capacity while others seem chronically under-funded. Over the years, legislators, ministers, and other government officials have tried a variety of methods to address under-funding. One such method was announced by the Treasury Board on April 16,1997--the cost recovery policy--which established a framework of fees for activities such as food inspection, agricultural services, and certification of drugs. (1) Among the Departments instituting user fees was Health Canada, which collects fees from the industries it regulates (e.g., pharmaceutical and medical device manufacturers) to offset the cost of services provided by Health Canada (HC) (e.g., reviewing applications for new drugs and devices). In the case of HC and other regulatory authorities, the user fees have become a vital source of revenue, upon which program operations rely. This is certainly the case with the Medical Devices Bureau (MDB) within the Therapeutic Products Directorate of the Health Products and Food Branch. According to a 2006 Auditor General's report (2) user fees are one of four sources of funding for Health Canada's programs. The primary source is core i.e., direct appropriations, which requires parliamentary approval. A second source (also requiring parliamentary approval) is funding for special initiatives (specific activities the relevant department would otherwise be unable to undertake absent the additional funding). In addition to the user fees, the final source of funding comes from internal departmental reallocations of funds from one program to another. (3) (Obviously, this is also a potential way for programs to lose funding, as well, which the MDB has experienced. (4)) This article will focus on user fees as a way to finance the medical device program and the impact they may increasingly have on the process of regulating medical devices in Canada. Background and Issues Before getting into the user fees specific to the medical devices program, it is worthwhile to briefly examine the government's stated rationale for instituting user fees in general. As described in a Treasury Board of Canada background document, there are essentially two arguments for charging user fees for government services: economic arguments and political/managerial arguments. (5) The economic arguments state that user fees promote economic efficiency in the expenditure of public funds by providing information to public sector suppliers on how much clients are actually willing to pay for particular services.... (6) The political/managerial argument claims that user fees promote government accountability (particularly if they incorporate service standards and penalties for nonperformance). The applicability of both rationales can be questioned, especially in the context of medical device regulation, although the political/managerial argument is probably stronger. The potentially more controversial aspect of user fees, generally, and their applicability to medical device regulation comes from the original policy document on cost recovery when describing the criteria for setting fees. (7) This policy objective has not changed with subsequent policy documents on the topic. It is government policy to implement user charges for services that provide identifiable recipients with direct benefits beyond those received by the general public, unless overriding policy objectives would be compromised ... (8) Examples offered from the cost recovery document of the appropriate application of federal user charges include: national park entrance, race track supervision, grain inspection, fishing licenses, broadcasting licenses, specific statistical services, aircraft landing, terminal rentals and concessions, passports, scientific services (mapping, remote sensing), small business loan administration, import/export permits, and publications. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.802
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.292
GPT teacher head0.431
Teacher spread0.139 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2008
Admission routes2
Has abstractyes

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