Estimating The Marginal Productivity Of Health Technology Adoption

Published: May 3, 2024
Category: Bibliography
Authors: C Yan, J Mohamed, J Round, M Saini, R Bacigalupo, S Bayat
Countries: Canada
Language: English
Types: Equality of Care
Settings: Province


Decisions to adopt health technologies rely, in part, on judgements about cost effectiveness. Cost effectiveness is commonly assessed against a willingness-to-pay threshold for health gains. Building an evidence base on the marginal productivity of health spending to inform the value of the threshold is increasingly of interest for resource allocation decision-making and technology implementation. We report on an in-progress analysis to inform a threshold for policy purposes in British Columbia, Canada.


We developed a ten-year panel-data model with instrumental variables, which lessens the degree of time-invariant confounding and addresses biased causal inferences caused by unobserved factors, to provide estimates of the marginal cost per health unit measured using quality-adjusted life-years (QALYs). We use the Johns Hopkins Adjusted Clinical Group (ACG) system and a British Columbia Health System Matrix to classify patients into six resource use bands (RUBs) ranging from ‘healthy’ to ‘very high morbidity’. Patients are also classified by chronic conditions and types of services. Place of residence and geographical region of health authorities are considered. Variables included age, gender, mortality and comorbidity rates, costs of hospitalizations, emergency department and physician visits, residential and home care, laboratory services, diagnosis and medications, and quality of life. Instrumental variables included sociodemographic characteristics as reported in the Canadian census.


The largest RUB was ‘moderate’ morbidity (39.3%), while the smallest was ‘healthy’ (1.5%). The youngest was the ‘low’ morbidity (mean 31, standard deviation [SD] 21) and the oldest was ‘very high’ (mean 69, SD 17). The healthy group had the smallest mean costs (CND563, SD CND4,121; equivalent to USD421, SD USD3,083). In contrast, the ‘very high’ group had the largest (CND20,398, SD CND36,188; equivalent to USD15,258, SD USD27,069). Age and gender standardized comorbidity index scores ranged from 0.05 to 6.41 (median 0.98). Additional analyses (e.g., costs per QALY) are ongoing and the results will be reported at the conference.


Our empirical approach is robust and flexible, allowing estimates of marginal productivity according to factors such as disease, geographical region, service type, and care sector. This work has applications at the provincial and national levels and adds to methodological literature in the field.

quality,utilization,RUBs, QALYs


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