Samer A Kharroubi1, Donna Rowen2. 1. Department of Nutrition and Food Sciences, Faculty of Agricultural and Food Sciences, American University of Beirut, P.O.BOX: 11-0236, Riad El Solh, Beirut, 1107-2020, Lebanon. sk157@aub.edu.lb. 2. Health Economics and Decision Science, School of Health and Related Research, The University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK.
Abstract
BACKGROUND: Different countries have different preferences regarding health, and there are different value sets for popular preference-based measures across different countries. However, the cost of collecting data to generate country-specific value sets can be prohibitive for countries with smaller population size or low- and middle-income countries (LMIC). This paper explores whether existing preference weights could be modelled alongside a small own country valuation study to generate representative estimates. This is explored using a case study modelling UK data alongside smaller US samples to generate US estimates. METHODS: We analyse EQ-5D valuation data derived from representative samples of the US and UK populations using time trade-off to value 42 health states. A nonparametric Bayesian model was applied to estimate a US value set using the full UK dataset and subsets of the US dataset for 10, 15, 20 and 25 health states. Estimates are compared to a US value set estimated using US values alone using mean predictions and root mean square error. RESULTS: The results suggest that using US data elicited for 20 health states alongside the existing UK data produces similar predicted mean valuations and RMSE as the US value set, while 25 health states produce the exact features. CONCLUSIONS: The promising results suggest that existing preference data could be combined with a small valuation study in a new country to generate preference weights, making own country value sets more achievable for LMIC. Further research is encouraged.
BACKGROUND: Different countries have different preferences regarding health, and there are different value sets for popular preference-based measures across different countries. However, the cost of collecting data to generate country-specific value sets can be prohibitive for countries with smaller population size or low- and middle-income countries (LMIC). This paper explores whether existing preference weights could be modelled alongside a small own country valuation study to generate representative estimates. This is explored using a case study modelling UK data alongside smaller US samples to generate US estimates. METHODS: We analyse EQ-5D valuation data derived from representative samples of the US and UK populations using time trade-off to value 42 health states. A nonparametric Bayesian model was applied to estimate a US value set using the full UK dataset and subsets of the US dataset for 10, 15, 20 and 25 health states. Estimates are compared to a US value set estimated using US values alone using mean predictions and root mean square error. RESULTS: The results suggest that using US data elicited for 20 health states alongside the existing UK data produces similar predicted mean valuations and RMSE as the US value set, while 25 health states produce the exact features. CONCLUSIONS: The promising results suggest that existing preference data could be combined with a small valuation study in a new country to generate preference weights, making own country value sets more achievable for LMIC. Further research is encouraged.
Keywords:
EQ-5D; Nonparametric Bayesian methods; Preference-based health measures; Time trade-off
Authors: Samer A Kharroubi; Yara Beyh; Marwa Diab El Harake; Dalia Dawoud; Donna Rowen; John Brazier Journal: Int J Environ Res Public Health Date: 2020-02-06 Impact factor: 3.390