Public preferences for allocating health system resources in Canada: a systematic review
Bibliographic record
Abstract
BACKGROUND: Conventional economic evaluations are based on the principle of health maximization. However, this approach does not consider societal preferences to prioritize health care for certain social groups and health conditions, and the public concern over health disparities. In recent years, equity-informative economic evaluation methods have been developed to incorporate societal concerns over for health inequities. These methods use quantitative evidence based on preference elicitation exercises to inform allocation of health system resources. OBJECTIVE: To systematically review Canadian studies that quantify public preferences for allocating health care resource across social groups and health conditions. METHODS: Three electronic databases were searched on January 1st, 2024: Ovid Embase, Ovid MEDLINE, and EBSCO EconLit. In addition, the reference lists of relevant papers were also scanned to detect any other suitable studies. The systematic review included studies that met the following criteria: they were survey-based, sampled Canadian residents and involved preference elicitation, where participants made decisions about resource allocation or responded to hypothetical scenarios about redistributing lifetime health. Qualitative studies and non-preference-based studies were excluded. Risk of Bias was assessed using the CLARITY Group's tool for evaluating cross-sectional surveys of attitudes and practices. Two reviewers conducted screening, full-text review, and data extraction. Studies were narratively synthesized. RESULTS: Eight studies, with 8,969 participants, were identified that investigated public preferences for prioritizing health care in relation to age, income, disease rarity, and baseline health. Age-related preferences tended to favor children and younger patients over older patients. Aversion to socioeconomic-related health inequality was heterogeneous and was associated with respondent characteristics. No clear preference was found for treatments for rare diseases over common conditions, or for baseline quality of life and life expectancy. Two studies exposed participants to moral reasoning exercises that led to slightly lower levels of preference for prioritization of specific conditions or groups. CONCLUSION: While the identified studies in the review were heterogenous, they provide some evidence supporting the prioritization of healthcare resources for children and younger patients over older patients. There is limited Canadian evidence on societal values related to health inequity associated with socioeconomic status, sex/gender, race/ethnicity, and other social determinants of health. Future research can help bridge this gap.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.144 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.045 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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; both teacher heads agree on what is shown here.
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".