A Discrete Choice Experiment to Understand the Value of Equity
Author(s)
Spackman E1, Steele D2, Wagner D1, Nathoo AN2, Hazlewood G1
1University of Calgary, Calgary, AB, Canada, 2Alberta Health Services, Calgary, AB, Canada
Presentation Documents
OBJECTIVES: To understand trade-offs between health and equity and provide a framework to incorporate equity in funding decisions.
METHODS: We developed a discrete choice experiment using attributes and levels of importance to the local decision maker. Attributes were based on health provided, life-expectancy and quality-of-life, whether the treatment had the potential for conflict with patients’ beliefs, population characteristics, the average time with disease, whether the population had experienced unfair treatment by society, and whether it was a rare disease.
We contacted 1,445 respondents between May and July 2021 using probability sampling of adults in Alberta, Canada. The main survey consisted of 10 questions. The specific levels shown to each respondent were determined by a balanced overlap fractional factorial experimental design. Validity was tested, and a multinomial logit model was used.RESULTS: Of those contacted, 891 (62%) opened the survey, and of those 574 (64%) completed it. Straight lining and attribute dominance did not appear to be a concern. 539 (94%) of respondents chose the dominant warm-up scenario. Baseline life-expectancy or quality-of-life, time with disease and whether the disease was rare did not have a statistically significant effect on utility. Gain in life-expectancy increased utility by 0.21 per year gained, utility increased by 0.05 for each 0.01 improvement in quality-of-life, treatments for patients that had been treated unfairly by society increased utility by 0.09 and treatments that respected all patients’ beliefs increased utility by 0.17. These preferences were used to develop a calculator to combine the health, cost and equity impacts of interventions and compare them to an opportunity cost threshold.
CONCLUSIONS: This research demonstrates the willingness of respondents to trade-off health maximization for treatments that respect all patients’ beliefs and populations that have been treated unfairly by society and allows decision makers to incorporate equity impacts into their decision making.
Conference/Value in Health Info
Value in Health, Volume 25, Issue 12S (December 2022)
Acceptance Code
P51
Topic
Economic Evaluation, Health Technology Assessment, Patient-Centered Research, Study Approaches
Topic Subcategory
Novel & Social Elements of Value, Stated Preference & Patient Satisfaction, Surveys & Expert Panels, Value Frameworks & Dossier Format
Disease
no-additional-disease-conditions-specialized-treatment-areas
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