Estimating the EQ-5D-5L value set for the Philippines.

BACKGROUND: The Philippines has recommended the use of Quality-Adjusted Life Years (QALYs) in government health technology assessments (HTA). We aimed to develop a value set for the EQ-5D-5L based on health preferences of the healthy general adult population in the Philippines. METHODS: Healthy, literate adults were recruited from the Philippine general population with quota targets based on age, sex, administrative region, type of residence, education, income, and ethnolinguistic groups. Each participant's preference was elicited by completing Composite Time Trade-Off (C-TTO) and Discrete Choice Experiment (DCE) tasks. Tasks were computer-assisted using the EuroQol Valuation Technology 2.0. To estimate the value set, we explored 20- and 8-parameter models that either use c-TTO-only data or both c-TTO and DCE (also called hybrid models). Final model choice was guided by principles of monotonicity, out-of-sample likelihood, model fit, and parsimony. RESULTS: We recruited 1000 respondents with demographic characteristics that approximate the general population such as 49.6% Female, 82% Roman Catholic, 40% in urban areas, and 55% finished high school. None of the 20-parameter models demonstrated monotonicity (logical worsening of coefficients with increasing severity). From the 8-parameter models, the homoscedastic TTO-only model exhibited the best fit. From this model, mobility and pain/ discomfort had the highest effect on utilities. CONCLUSION: The selected model for representing the Philippine general population preferences for EQ-5D-5L health states was an 8-parameter homoscedastic TTO-only model. This value set is recommended for use in QALY calculations in support of HTA-informed coverage decisions in the Philippines.

A cross-sectional study on the determinants of health-related quality of life in the Philippines using the EQ-5D-5L.

PURPOSE: The purpose of this study was to identify the determinants of Filipinos' health-related quality of life (HRQoL). METHODS: Data were collected from 1000 Filipinos across the nation who reported that they did not have known active disease or disability. HRQoL was measured through EuroQoL's (EQ) 5-level tool (EQ-5D-5L) and the EQ Visual Analog Scale (EQ-VAS). Both were implemented via the EQ Valuation Technology software. HRQoL was regressed on socioeconomic characteristics (age, sex, marital status, educational attainment, employment, poverty status, and availability of savings), social support factors (religion, religious attendance, and caregiving status), community- or societal-level factors (type and major island group of residence), and disease status. RESULTS: Majority of respondents reported that they did not have any problems across all EQ-5D-5L dimensions, namely mobility, self-care, usual activity, pain or discomfort, and anxiety or depression. Pain or discomfort had the highest rate of respondents reporting slight to extreme problems followed by anxiety or depression. Having savings was positively associated with HRQoL, while religious attendance, caregiver status, living in an urban area, living in Visayas or Mindanao, and having a diagnosed disease were negatively associated with HRQoL. CONCLUSION: This current study confirms that HRQoL varied across socioeconomic statuses and communities in the Philippines.

COVID-19 Death Rates Are Higher in Rural Counties With Larger Shares of Blacks and Hispanics.

PURPOSE: This study compared the average daily increase in COVID-19 mortality rates by county racial/ethnic composition (percent non-Hispanic Black and percent Hispanic) among US rural counties. METHODS: COVID-19 daily death counts for 1,976 US nonmetropolitan counties for the period March 2-July 26, 2020, were extracted from USAFacts and merged with county-level American Community Survey and Area Health Resource File data. Covariates included county percent poverty, age composition, adjacency to a metropolitan county, health care supply, and state fixed effects. Mixed-effects negative binomial regression with random intercepts to account for repeated observations within counties were used to predict differences in the average daily increase in the COVID-19 mortality rate across quartiles of percent Black and percent Hispanic. FINDINGS: Since early March, the average daily increase in the COVID-19 mortality rate has been significantly higher in rural counties with the highest percent Black and percent Hispanic populations. Compared to counties in the bottom quartile, counties in the top quartile of percent Black have an average daily increase that is 70% higher (IRR = 1.70, CI: 1.48-1.95, P < .001), and counties in the top quartile of percent Hispanic have an average daily increase that is 50% higher (IRR = 1.50, CI: 1.33-1.69, P < .001), net of covariates. CONCLUSION: COVID-19 mortality risk is not distributed equally across the rural United States, and the COVID-19 race penalty is not restricted to cities. Among rural counties, the average daily increase in COVID-19 mortality rates has been significantly higher in counties with the largest shares of Black and Hispanic residents.