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Record W3013517174

Cost-Effectiveness and Social Values in Health Care Priority Setting: Normative Reasons and Public Deliberation

2017· dissertation· en· W3013517174 on OpenAlexaboutno aff
Mônica de Avelar Figueirêdo Mafra Magalhães

Bibliographic record

VenueDigital Access to Scholarship at Harvard (DASH) (Harvard University) · 2017
Typedissertation
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsnot available
Fundersnot available
KeywordsDeliberationNormativePublic healthHealth carePolitical sciencePublic economicsPsychologySocial psychologyMedicinePublic administrationPositive economicsSociologyActuarial scienceEconomicsNursingPoliticsLaw
DOInot available

Abstract

fetched live from OpenAlex

Paper 1 discusses the question of whether health policy should treat drugs for rare diseases (“orphan drugs”) differently from drugs for common diseases. Due to the small number of potential patients, orphan drugs are less likely to be developed and tend to be expensive when they come to market. To promote development of and access to these treatments, many countries have instituted policies that give special consideration to orphan drugs in a variety of ways. This paper asks whether disease prevalence is a morally relevant characteristic that warrants such special treatment. After examining reasons given in the literature for distinguishing between rare and common diseases, I argue that it is not. It is the severity of orphan diseases that drives our judgments that important claims are being overlooked when orphan treatments are unavailable, not their prevalence. Unlike prevalence, severity is an appropriate consideration for priority setting. Therefore, policies aiming to treat all claims equally should make prevalence irrelevant rather than making it the basis of differential treatment.\nPaper 2 is a qualitative study of public values on the question of how the severity of a condition and its prevalence should affect priority setting. As part of two citizens’ juries in Alberta, Canada, participants engaged in a deliberative exercise designed to elicit trade-offs between helping small groups with severe conditions and larger groups with less severe conditions. A thematic analysis of transcripts of the deliberations indicates that the public would support funding high-cost drugs to meet the needs of a few when the interventions for rare conditions are life-saving; extend life enough to give hope of future improvement; and relieve otherwise intractable symptoms, especially pain. Considerations of whether a treatment manages symptoms or alters the underlying condition take low priority. These findings can inform Canada’s current drive to establish a national orphan drug policy.\nPaper 3 examines the use of cost-effectiveness thresholds in the British National Health System (NHS). A recent report states that the NHS’ cost-effectiveness threshold should be lowered from £30,000 to £12,936, to reflect the opportunity cost of a quality-adjusted life-year (QALY) rather than a measure of societal willingness to pay for a QALY. This paper argues that if the threshold is to be determined by opportunity costs, then the understanding of opportunity cost needs to be broadened to include not only QALYs foregone, but also effects on equity, financial protection, and other social values. Even if a broader notion of opportunity cost is considered, deriving the threshold from these costs raises a question of justification: opportunity costs are determined by political factors and facts about the health care system that are unrelated to patients’ claims on the NHS, and may seem arbitrary from their point of view.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.172
metaresearch head score (Gemma)0.177
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.172
Threshold uncertainty score0.908

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1720.177
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0200.157
Scholarly communication0.0230.021
Open science0.0040.019
Research integrity0.0180.017
Insufficient payload (model declined to judge)0.0030.000

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 head0.106
GPT teacher head0.447
Teacher spread0.341 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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