ESTABLISHING VALIDITY AND DEVELOPING A PREDICTOR TOOL FOR ESTIMATION OF WILLINGNESS TO PAY BASED THRESHOLD FOR INDIA
Author(s)
Yashika Chugh, PhD1, Aarti Goyal, PhD1, Gaurav Jyani, MD1, Kritika Kapoor, MPH1, Mehak Vijayvargiya, Student2, Pvm Lakshmi, MD1, Cam Donaldson, PhD3, Shankar Prinja, MD1.
1Department of Community Medicine & School of Public Health, Postgraduate Institute of Medical Education and Research, Chandigarh, India, 2College of Health and Human Development, The Pennsylvania State University, Pennsylvania, PA, USA, 3Yunus Centre for Social Business & Health, Glasgow Caledonian University, Glasgow, Scotland, United Kingdom.
1Department of Community Medicine & School of Public Health, Postgraduate Institute of Medical Education and Research, Chandigarh, India, 2College of Health and Human Development, The Pennsylvania State University, Pennsylvania, PA, USA, 3Yunus Centre for Social Business & Health, Glasgow Caledonian University, Glasgow, Scotland, United Kingdom.
OBJECTIVES: This study advances existing work on cost-effectiveness threshold (CET) estimation for India by validating the findings, developing a predictive tool for threshold estimation, and exploring behavioural determinants of willingness to pay (WTP).
METHODS: A mixed-methods approach was used. The quantitative component assessed various forms of validity for WTP per QALY across six Indian states. This included content, face, convergent, discriminant, concurrent, and predictive validity assessment. While all validity assessments used data from India CET study, predictive validity was evaluated using individual-level data from Punjab state of India. Using a multistage stratified random approach, a sample of 227 was collected to estimate observed WTP per QALY, followed by construction of Bland-Altman Plot for agreement. Secondly, a regression-based predictor tool was developed. Thirdly, behavioural determinants of WTP were explored through in-depth interviews with 18 participants, analyzed using the socio-ecological model.
RESULTS: High correlations were observed for convergent measures (r=0.838 for EQ-5D-5L and VAS; p<0.001). Discriminant validity was established with weak correlations (r=0.021 between QALY gains and consumption expenditure). Predictive validity showed a high correlation between predicted and observed values (r=0.59) and 96% agreement was reported by Bland-Altman Plot. The predictor tool indicated that age, household consumption expenditure, education, unemployment and insurance coverage demonstrates significant associations. Median WTP per QALY varied, Uttarakhand (Rs 9,81,548) and Andaman and Nicobar Islands (Rs 7,29,238) had the highest WTP per QALY and the lowest values were reported for Jharkhand (Rs.12,645) and Meghalaya (Rs 18,549). Qualitative analysis revealed income, employment status, education and perceptions of illness as key determinants of WTP.
CONCLUSIONS: The predictor tool can be used to predict CETs over time, for different states and at the national levels in another country with similar characteristics.
METHODS: A mixed-methods approach was used. The quantitative component assessed various forms of validity for WTP per QALY across six Indian states. This included content, face, convergent, discriminant, concurrent, and predictive validity assessment. While all validity assessments used data from India CET study, predictive validity was evaluated using individual-level data from Punjab state of India. Using a multistage stratified random approach, a sample of 227 was collected to estimate observed WTP per QALY, followed by construction of Bland-Altman Plot for agreement. Secondly, a regression-based predictor tool was developed. Thirdly, behavioural determinants of WTP were explored through in-depth interviews with 18 participants, analyzed using the socio-ecological model.
RESULTS: High correlations were observed for convergent measures (r=0.838 for EQ-5D-5L and VAS; p<0.001). Discriminant validity was established with weak correlations (r=0.021 between QALY gains and consumption expenditure). Predictive validity showed a high correlation between predicted and observed values (r=0.59) and 96% agreement was reported by Bland-Altman Plot. The predictor tool indicated that age, household consumption expenditure, education, unemployment and insurance coverage demonstrates significant associations. Median WTP per QALY varied, Uttarakhand (Rs 9,81,548) and Andaman and Nicobar Islands (Rs 7,29,238) had the highest WTP per QALY and the lowest values were reported for Jharkhand (Rs.12,645) and Meghalaya (Rs 18,549). Qualitative analysis revealed income, employment status, education and perceptions of illness as key determinants of WTP.
CONCLUSIONS: The predictor tool can be used to predict CETs over time, for different states and at the national levels in another country with similar characteristics.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
PCR41
Topic
Patient-Centered Research
Topic Subcategory
Instrument Development, Validation, & Translation
Disease
No Additional Disease & Conditions/Specialized Treatment Areas