Relative diagnostic yield of tests for disseminated tuberculosis among inpatients living with HIV
Bibliographic record
Abstract
Introduction: Canada is committed to reducing avoidable health inequalities associated with infectious diseases.However, conventional economic evaluation, a critical component of health technology assessments informing health resource allocation, fails to account for health equity issues.Conducting equity-informative economic evaluation requires understanding the extent to which Canadians are averse to health inequalities.Therefore, the objective of our study was to elicit Canadians' aversion to reduce health inequalities, and whether these preferences varied when evaluating interventions specific to infectious diseases. Methods:We conducted three online surveys among representative samples of adult Canadians to elicit value judgements about reducing health inequality between populations with the highest and lowest income (i.e., household income quintiles) vs. improving overall health irrespective of its distribution (i.e., life expectancy).The first survey was specific to infectious diseases, and respondents were asked to choose between a universal and a tailored vaccination program.Tailored vaccination (e.g., special outreach for underserved populations) had a more equitable distribution of additional life years, while universal vaccination was more efficient.The second survey compared universal vs. tailored prevention programs.Finally, the third survey presented generic health programs (program A vs. program B).We used benefit trade-off analysis to estimate health inequality aversion.Results: We recruited 3,0 0 0 adult Canadians (1,0 0 0 for each survey).Preferences for the vaccine, prevention, and generic programs were distributed as follows: minimizing inequalities (i.e., egalitarians): 54%, 55%, and 57%, respectively; maximizing the health of the population with the highest income (i.e., pro-rich): 31%, 22%, and 16% respectively; willingness to trade some health to reduce inequalities (i.e., weighted prioritarians): 13%, 19%, and 22% respectively; and maximizing total health, regardless of how life years were distributed (i.e., health maximizers): 2%, 3%, and 2%, respectively.The median respondent preferred minimizing health inequalities, across the three surveys.A stronger aversion for health inequality was observed among females, younger respondents (18-40 years old), and populations with lower income ( < $50,0 0 0 household income per year).Discussion: Preferences for reducing health inequality were impacted by the type of interventions being compared.When evaluating vaccine-specific programs, most respondents were located at the extremes of the distribution (i.e., pro-rich or egalitarians), while utilizing generic terminology (i.e., generic programs) reduced the proportion of inequality-seeking preferences.However, over half of the respondents were consistently willing to minimize health inequalities regardless of the cost to efficiency, suggesting a strong aversion to health inequality among Canadians.Conclusion: Canadians have a considerable level of health inequality aversion when evaluating vaccine and non-vaccine interventions.These results allow conducting equity-informed eco-nomic evaluation to inform resource allocation and priority setting in Canada.
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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 | 0.006 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".