A Systematic Review of Economic Evaluations of COVID-19 Interventions: Considerations of Non-Health Impacts and Distributional Issues

Podolsky, Meghan I; Present, Isabel; Neumann, Peter J.; Kim, David D.

doi:10.1016/j.jval.2022.02.003

Cited by 15 publications

(8 citation statements)

References 55 publications

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“…To the best of our knowledge, this is the first DCEA conducted in the United States following methods outlined by Cookson and colleagues 15 and the only DCEA to examine COVID-19 treatments. 8 Although the reporting of results aligns with DCEAs conducted in other settings, direct interpretation and comparison are difficult given the many unique features of the US population and healthcare system. For example, we found that more socially vulnerable groups experienced more health benefits from inpatient COVID-19 treatments across all subgroups.…”

Section: Discussionmentioning

confidence: 95%

“…To promote efficient resource allocation when budgets are limited, cost-effectiveness analysis (CEA) is being leveraged to inform decision making on funding and reimbursement for COVID-19 treatments in the United States. 8 , 9 , 10 , 11 , 12 , 13 , 14 CEA focuses on the total costs and health effects across the whole population eligible for treatment. Nevertheless, CEAs rarely provide information on the distribution of costs and effects—that is, who gains and who loses—which depends on differences among people at various steps in the “inequality staircase” including differences in health risks (eg, who is at the highest risk), access (eg, who is most likely to receive treatment), capacity to benefit (eg, who benefits most from treatment), and who bears the opportunity costs of diverting scarce resources from other uses.…”

Section: Introductionmentioning

confidence: 99%

“…The equity impact of funding COVID-19 interventions in the United States has not yet been established. 8 , 14 Given the disproportionate impact of COVID-19 on disadvantaged populations, it is essential to understand how decisions on the funding of treatments may affect health disparities. Building on previous work to outline a framework for estimating the cost-effectiveness of COVID-19 inpatient treatments, 13 we conducted the first application of DCEA to evaluate how US Medicare funding of inpatient COVID-19 treatments for hospitalized patients might affect health equity in the United States.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Impact of Funding Inpatient Treatments for COVID-19 on Health Equity in the United States: A Distributional Cost-Effectiveness Analysis

Kowal¹,

Ng²,

Schuldt³

et al. 2023

Value in Health

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Section: Discussionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Impact of Funding Inpatient Treatments for COVID-19 on Health Equity in the United States: A Distributional Cost-Effectiveness Analysis

Kowal¹,

Ng²,

Schuldt³

et al. 2023

Value in Health

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“…In addition, we perform our investigation in Latin America, where restrictions were particularly strict and where a context of high inequality highlights the importance of studying the heterogeneous effects. Economic evaluations of the cost-effectiveness of public health measures to deal with the pandemic have concentrated in high and middle income countries and have overlooked distributional concerns [ 20 , 21 ]. This makes our contributions particularly relevant, both from an academic perspective as well as an input for policy-making.…”

Section: Discussionmentioning

confidence: 99%

The Impacts of COVID-19 Restrictions on Quality Adjusted Life Years (QALY): Heterogeneous effects and post-pandemic recovery

Atal,

Bedregal,

Carrasco

et al. 2024

PLoS ONE

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Objectives Estimate the effects of non-pharmacological interventions used to prevent the spread of COVID-19 on the quality of life, measured by Quality Adjusted Life Years (QALYs). Methods A survey on 1,506 heads of households from Chile in May of 2022. Respondents were asked basic socioeconomic questions and a version of the EQ-5D-5L questionnaire that was used to calculate the evolution of HRQoLs. Comparisons of means in HRQoLs measures before the pandemic, at the peak of restrictions, and at the moment of the survey were performed. Results The average HRQoL of the population before the pandemic was similar to other countries in the region (0.96). At the peak of restrictions (June 2020–August 2021), the average HRQoL decreased to 0.87 (-9%). At the time of survey (May 2022), the average HQRoL was 0.91 (4%). Assuming the recovery trend continued, pre-pandemic HRQoLs would be reached by January 2024. Altogether, the pandemic would have reduced QALYs by 0.2 in average. The effect is larger and the recovery slower among women. Our estimates imply that the restrictions to manage the pandemic came at a cost of 2.4 months of life years for the average (surviving) person, 1.8 months for men and 3.4 for women. Conclusions Our results suggest that COVID-19 had worse effects on life quality than previously thought. These effects are more significant among women than among men. Efforts to improve life quality and speed up its recovery could have large positive consequences for the population.

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“…This comes at a pivotal point in time, where there is increasing debate about how to consider equity-related aspects in health economic analyses. For example, there has been a collective effort to show that lack of health equity consideration within a health technology assessment (HTA) could result in neglecting an important aspect of the value of interventions and potentially misallocation of healthcare resources (Cookson et al, 2017;Podolsky et al, 2022). Furthermore, the Institute for Clinical and Economic Review has recently published a whitepaper on the use of methods that support equity-informed analyses for HTA in the United States (Agboola et al, 2023).…”

Section: Discussionmentioning

confidence: 99%

Quantifying the impact of novel metastatic cancer therapies on health inequalities in survival outcomes

Zebrowska,

Banuelos,

Rizzo

et al. 2023

Front. Pharmacol.

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Background: Novel therapies in metastatic cancers have contributed to improvements in survival outcomes, yet real-world data suggest that improvements may be mainly driven by those patient groups who already had the highest survival outcomes. This study aimed to develop and apply a framework for quantifying the impact of novel metastatic cancer therapies on health inequalities in survival outcomes based on published aggregate data.Methods: Nine (N = 9) novel therapies for metastatic breast cancer (mBC), metastatic colorectal cancer (mCRC), and metastatic non–small cell lung cancer (mNSCLC) were identified, 3 for each cancer type. Individual patient data (IPD) for overall survival (OS) and progression-free survival (PFS) were replicated from published Kaplan-Meier (KM) curves. For each cancer type, data were pooled for the novel therapies and comparators separately and weighted based on sample size to ensure equal contribution of each therapy in the analyses. Parametric (mixture) distributions were fitted to the weighted data to model and extrapolate survival. The inequality in survival was defined by the absolute difference between groups with the highest and lowest survival for 2 stratifications: one for which survival was stratified into 2 groups and one using 5 groups. Additionally, a linear regression model was fitted to survival estimates for the 5 groups, with the regression coefficient or slope considered as the inequality gradient (IG). The impact of the pooled novel therapies was subsequently defined as the change in survival inequality relative to the pooled comparator therapies. A probabilistic analysis was performed to quantify parameter uncertainty.Results: The analyses found that novel therapies were associated with significant increases in inequalities in survival outcomes relative to their comparators, except in terms of OS for mNSCLC. For mBC, the inequalities in OS increased by 13.9 (95% CI: 1.4; 26.6) months, or 25.0%, if OS was stratified in 5 groups. The IG for mBC increased by 3.2 (0.3; 6.1) months, or 24.7%. For mCRC, inequalities increased by 6.7 (3.0; 10.5) months, or 40.4%, for stratification based on 5 groups; the IG increased by 1.6 (0.7; 2.4) months, or 40.2%. For mNSCLC, inequalities decreased by 14.9 (−84.5; 19.0) months, or 12.2%, for the 5-group stratification; the IG decreased by 2.0 (−16.1; 5.1) months, or 5.5%. Results for the stratification based on 2 groups demonstrated significant increases in OS inequality for all cancer types. In terms of PFS, the increases in survival inequalities were larger in a relative sense compared with OS. For mBC, PFS inequalities increased by 8.7 (5.9; 11.6) months, or 71.7%, for stratification based on 5 groups; the IG increased by 2.0 (1.3; 2.6) months, or 67.6%. For mCRC, PFS inequalities increased by 5.4 (4.2; 6.6) months, or 147.6%, for the same stratification. The IG increased by 1.3 (1.1; 1.6) months, or 172.7%. For mNSCLC, inequalities increased by 18.2 (12.5; 24.4) months, or 93.8%, for the 5-group stratification; the IG increased by 4.0 (2.8; 5.4) months, or 88.1%. Results from the stratification based on 2 groups were similar.Conclusion: Novel therapies for mBC, mCRC, and mNSCLC are generally associated with significant increases in survival inequalities relative to their comparators in randomized controlled trials, though inequalities in OS for mNSCLC decreased nonsignificantly when stratified based on 5 groups. Although further research using real-world IPD is warranted to assess how, for example, social determinants of health affect the impact of therapies on health inequalities among patient groups, the proposed framework can provide important insights in the absence of such data.

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A Systematic Review of Economic Evaluations of COVID-19 Interventions: Considerations of Non-Health Impacts and Distributional Issues

Cited by 15 publications

References 55 publications

The Impact of Funding Inpatient Treatments for COVID-19 on Health Equity in the United States: A Distributional Cost-Effectiveness Analysis

The Impact of Funding Inpatient Treatments for COVID-19 on Health Equity in the United States: A Distributional Cost-Effectiveness Analysis

The Impacts of COVID-19 Restrictions on Quality Adjusted Life Years (QALY): Heterogeneous effects and post-pandemic recovery

Quantifying the impact of novel metastatic cancer therapies on health inequalities in survival outcomes

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