Relative diagnostic yield of tests for disseminated tuberculosis among inpatients living with HIV
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,048 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».