AbstractObjectiveTo derive a US-based value set for the EQ-5D-5L questionnaire using an international, standardized protocol developed by the EuroQol Group. MethodsRespondents from the US adult ...population were quota-sampled on the basis of age, sex, ethnicity, and race. Trained interviewers guided participants in completing composite time trade-off (cTTO) and discrete choice experiment (DCE) tasks using the EuroQol Valuation Technology software and routine quality control measures. Data were modeled using a Tobit model for cTTO data, a mixed logit model for DCE data, and a hybrid model that combined cTTO and DCE data. Model performance was compared on the basis of logical ordering of coefficients, statistical significance, parsimony, and theoretical considerations. ResultsOf 1134 respondents, 1062, 1099, and 1102 respondents provided useable cTTO, DCE, and cTTO or DCE responses, respectively, on the basis of quality control criteria and interviewer judgment. Respondent demographic characteristics and health status were similar to the 2015 US Census. The Tobit model was selected as the preferred model to generate the value set. Values ranged from −0.573 (55 555) to 1 (11 111), with 20% of all predicted health states scores less than 0 (ie, worse than dead). ConclusionsA societal value set for the EQ-5D-5L was developed that can be used for economic evaluations and decision making in US health systems. The internationally established, standardized protocol used to develop this US-based value set was recommended by the EuroQol Group and can facilitate cross-country comparisons.
Background
The COVID-19 pandemic has resulted in negative impacts on the economy, population health, and health-related quality-of-life (HRQoL).
Objective
To assess the impact of COVID-19 on US ...population HRQoL using the EQ-5D-5L.
Design
We surveyed respondents on physical and mental health, demographics, socioeconomics, brief medical history, current COVID-19 status, sleep, dietary, financial, and spending changes. Results were compared to online and face-to-face US population norms. Predictors of EQ-5D-5L utility were analyzed using both standard and post-lasso OLS regressions. Robustness of regression coefficients against unmeasured confounding was analyzed using the E-Value sensitivity analysis.
Subjects
Amazon MTurk workers (
n
=2776) in the USA.
Main Measures
EQ-5D-5L utility and VAS scores by age group.
Key Results
We received
n
=2746 responses. Subjects 18–24 years reported lower mean (SD) health utility (0.752 (0.281)) compared with both online (0.844 (0.184),
p
=0.001) and face-to-face norms (0.919 (0.127),
p
<0.001). Among ages 25–34, utility was worse compared to face-to-face norms only (0.825 (0.235) vs. 0.911 (0.111),
p
<0.001). For ages 35–64, utility was better during pandemic compared to online norms (0.845 (0.195) vs. 0.794 (0.247),
p
<0.001). At age 65+, utility values (0.827 (0.213)) were similar across all samples. VAS scores were worse for all age groups (
p
<0.005) except ages 45–54. Increasing age and income were correlated with increased utility, while being Asian, American Indian or Alaska Native, Hispanic, married, living alone, having history of chronic illness or self-reported depression, experiencing COVID-19-like symptoms, having a family member diagnosed with COVID-19, fear of COVID-19, being underweight, and living in California were associated with worse utility scores. Results were robust to unmeasured confounding.
Conclusions
HRQoL decreased during the pandemic compared to US population norms, especially for ages 18–24. The mental health impact of COVID-19 is significant and falls primarily on younger adults whose health outcomes may have been overlooked based on policy initiatives to date.
Online longitudinal surveys may be subject to potential biases due to sample attrition. This study was designed to identify potential predictors of attrition using a longitudinal panel survey ...collected during the COVID-19 pandemic. Three waves of data were collected using Amazon Mechanical Turk (MTurk), an online crowd-sourced platform. For each wave, the study sample was collected by referencing a US national representative sample distribution of age, gender, and race, based on US census data. Variables included respondents' demographics, medical history, socioeconomic status, COVID-19 experience, changes of health behavior, productivity, and health-related quality of life (HRQoL). Results were compared to pre-pandemic US norms. Measures that predicted attrition at different times of the pandemic were identified via logistic regression with stepwise selection. 1467 of 2734 wave 1 respondents participated in wave 2 and, 964 of 2454 wave 2 respondents participated in wave 3. Younger age group, Hispanic origin (p less than or equai to 0.001) and higher self-rated survey difficulty (p less than or equai to 0.002) consistently predicted attrition in the following wave. COVID-19 experience, employment, productivity, and limited physical activities were commonly observed variables correlated with attrition with specific measures varying by time periods. From wave 1, mental health conditions, average daily hours worked (p = 0.004), and COVID-19 impact on work productivity (p < 0.001) were associated with a higher attrition rate at wave 2, additional to the aforementioned factors. From wave 2, support of social distancing (p = 0.032), being Republican (p < 0.001), and having just enough money to make ends meet (p = 0.003) were associated with predicted attrition at wave 3. Attrition in this longitudinal panel survey was not random. Besides commonly identified demographic factors that contribute to panel attrition, COVID-19 presented novel opportunities to address sample biases by correlating attrition with additional behavioral and HRQoL factors in a constantly evolving environment. While age, ethnicity, and survey difficulty consistently predicted attrition, other factors, such as COVID-19 experience, changes of employment, productivity, physical health, mental health, and financial situation impacted panel attrition during the pandemic at various degrees.
Limited studies have directly compared health-related quality of life (HRQoL) in different countries during the COVID-19 global pandemic. The objective of this study was to evaluate the HRQoL ...outcomes in the US, Sweden, and Norway during the first year under the pandemic.
In April 2020, during early phase of the pandemic, separately in the US, Sweden, and Norway, we surveyed 2,734, 1,003 and 1,020 respondents, then again in January 2021, we collected 2,252, 1,013 and 1,011 respondents. The survey was first developed in English and translated into Swedish and Norwegian. Selected variables were used for the current study. We collected respondents' HRQoL using the EQ-5D-5L. Respondents' background information included their sociodemographic data, medical history, and COVID-19 status. We reported the EQ-5D-5L utility, EQ-VAS, and the proportion of problems with each of the EQ-5D-5L health subdomains. Population quality-adjusted life year (QALY) changes based on EQ-5D-5L utility scores were also calculated. Outcomes were stratified by age. One-way ANOVA test was used to detect significant differences between countries and Student's t-tests were used to assess the differences between waves.
Respectively for the US, Sweden, and Norway, mean EQ-5D-5L utilities were 0.822, 0.768, and 0.808 in April 2020 (p < 0.001); 0.823, 0.783, and 0.777 in January 2021 (p < 0.001); mean EQ-VAS scores were 0.746, 0.687, and 0.692 in April 2020 (p < 0.001), 0.764, 0.682, and 0.678 in January 2021 (p < 0.001). For both waves, EQ-5D-5L utilities and EQ-VAS scores in the US remained higher than both Sweden and Norway (p < 0.001). Norwegians reported considerably lowered HRQoL over time (p < 0.01). Self-reported problems with anxiety/depression were highest for the US and Sweden, while Norwegians reported most problems with pain/discomfort, followed by anxiety/depression. The population QALYs increased in the US and Sweden, but decreased in Norway.
In the first year of the pandemic, a rebound in HRQoL was observed in the US, but not in Sweden or Norway. Mental health issues during the pandemic warrant a major public health concern across all 3 countries.
Area under the time–concentration curve (AUC) -guided dosing provides better estimates of exposure than vancomycin trough concentrations. Though clinical benefits have been reported, the costs of ...AUC-guided dosing are uncertain. The objective of this study was to quantify the costs of single-sample Bayesian or two-sample AUC strategies versus trough-guided dosing.
A cost–benefit analysis from the institutional perspective was conducted using a decision tree to model the probabilities and costs of acute kidney injury (AKI) associated with vancomycin administered over 48 hours up to 21+ days. Costs included vancomycin concentrations, Bayesian software and AKI hospitalization costs, and probabilities were obtained from primary literature. Robustness was assessed via both one-way and probabilistic sensitivity analyses.
In the base-case model, two-sample AUC versus trough dosing saved an average of US$ 846 per patient encounter, and single-sample Bayesian AUC versus trough dosing saved an average of US$ 2065 per patient encounter. This translates into annual cost-savings of US$ 846 810 and US$ 2 065 720 for two-sample and single-sample Bayesian methods versus trough dosing, respectively, assuming 1000 vancomycin-treated patients per year. Assuming a budget of US$ 100 000 per year for Bayesian software, an institution would need to treat ≥41 patients with vancomycin for at least 48 hours to break even.
There are significant institutional cost benefits using two-sample AUC or single-sample Bayesian methods over trough dosing, even after accounting for the annual costs of Bayesian programs. The potential to decrease rates of AKI, improve clinical outcomes and reduce costs to the institution strongly warrants consideration of improved dosing methods for vancomycin.
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Respiratory syncytial virus (RSV) hospitalizations have increased since the 2014 guideline update recommended against the use of palivizumab for preterm infants born ≥29 0/7 weeks' gestational age ...(GA) without additional risk factors. A novel drug candidate, nirsevimab, has been developed for this population. We analyzed the cost-effectiveness of palivizumab/nirsevimab vs. no prophylaxis in this population.
A hybrid-Markov model predicted the RSV clinical course in the first year of life and sequelae in the subsequent four years for preterm infants from the healthcare and societal perspectives. Model parameters were derived from the literature. We calculated costs and quality-adjusted life-years (QALYs) to produce an incremental cost-effectiveness ratio (ICER) evaluated at a willingness-to-pay threshold of $150,000/QALY. Sensitivity analyses assessed model robustness. A threshold analysis examined nirsevimab pricing uncertainty.
Compared to no prophylaxis, palivizumab costs $9572 and $9584 more from the healthcare and societal perspectives, respectively, with 0.0019 QALYs gained per patient over five years, resulting in ICERs >$5 million per QALY from each perspective. Results were robust to parameter uncertainties; probabilistic sensitivity analysis revealed that no prophylaxis had a 100% probability of being cost-effective. The threshold analysis suggested that nirsevimab is not cost-effective when compared to no prophylaxis if the price exceeds $1962 from a societal perspective.
Palivizumab is dominated by no prophylaxis for preterm infants 29 0/7–34 6/7 weeks' GA with no additional risk factors. Relevant stakeholders should consider alternatives to palivizumab for this population that are both effective and economical.
The role of altruism in the acceptance of novel preventive healthcare technologies like vaccines has not been thoroughly elucidated.
We 1:1 randomized n = 2004 Amazon Mechanical Turk (MTurk) ...participants residing in the USA into a control or treatment arm with vaccination decisions framed altruistically, to elicit their preferences for COVID-19 vaccination using web-based discrete choice experiments. We used conditional and mixed logit models to estimate the impact of framing decisions in terms of altruism on vaccination acceptance.
Valid responses were provided by 1674 participants (control, n = 848; treatment, n = 826). Framing vaccination decisions altruistically had no significant effect on vaccination acceptance. Further, respondents' degree of altruism had no association with vaccination acceptance.
The MTurk sample may not be representative of the American population. We were unable to ascertain concordance between stated and revealed preferences.
Framing vaccination decisions in terms of altruism does not appear to significantly influence vaccination acceptance and may not be an effective nudging mechanism to increase the uptake of novel vaccines. Instead, a favorable vaccination profile appears to be the primary driver of uptake.
Treatment of Clostridioides difficile infection (CDI) has undergone significant change in recent years with the introduction of fidaxomicin and bezlotoxumab. This study evaluated the ...cost-effectiveness of fidaxomicin and bezlotoxumab for initial CDI compared with standard therapy with oral vancomycin.
A Markov model with eight health states was built based on transition probabilities, costs and health utilities derived from literature to evaluate the cost-effectiveness of standard fidaxomicin, bezlotoxumab plus vancomycin, and extended-pulsed fidaxomicin versus standard oral vancomycin over a lifetime horizon from the US societal perspective.
For overall CDI treatment, oral vancomycin had a cost of $39 178 and was associated with a gain of 11.64 quality-adjusted life-years (QALYs). Extended-pulsed fidaxomicin had a higher QALY gain of 11.65 at a lower cost of $37 613, and therefore was dominant over vancomycin. Standard fidaxomicin had a QALY gain of 11.94 versus vancomycin at an incremental cost of $495 per QALY. Bezlotoxumab plus vancomycin led to a QALY gain of 11.77 at an incremental cost of $17 746 per QALY. At the willingness-to-pay (WTP) threshold of $150 000 per QALY, extended-pulsed fidaxomicin, bezlotoxumab plus vancomycin and standard fidaxomicin were more cost-effective compared with vancomycin alone, yielding incremental net monetary benefits of $3248, $17 011 and $44 308, respectively. One-way sensitivity analysis suggested that the probabilities of sustained cure from the initial episode were the most sensitive inputs, and results were overall not particularly sensitive to any drug costs.
Based on a WTP threshold of $150 000, standard fidaxomicin was estimated to be the most cost-effective treatment. Standard-of-care vancomycin was dominated by extended-pulsed fidaxomicin for treating an episode of CDI and preventing further recurrence, and the addition of bezlotoxumab to vancomycin was dominated by standard fidaxomicin.
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