Correction to: Perspective and Costing in Cost‑Effectiveness Analysis, 1974–2018

Kim, David D.; Silver, Madison C.; Kunst, Natalia; Cohen, Joshua T.; Ollendorf, Daniel A.; Neumann, Peter J.

doi:10.1007/s40273-020-00968-6

Cited by 5 publications

(6 citation statements)

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“…Some could have conceivably distinguished ROI analyses from other types of health economic studies by including and monetising non-health benefits. However, only 25% of the identified ROI studies monetised non-health benefits, and these benefits can be included in cost-benefit analyses26 27 and even in a cost-effectiveness analysis when using the societal perspective 28. Thus, the inclusion of monetised non-health benefits does not formally distinguish ROI from cost-benefit analysis.…”

Section: Discussionmentioning

confidence: 99%

“…However, only 25% of the identified ROI studies monetised non-health benefits, and these benefits can be included in cost-benefit analyses 26 27 and even in a cost-effectiveness analysis when using the societal perspective. 28 Thus, the inclusion of monetised nonhealth benefits does not formally distinguish ROI from cost-benefit analysis. An alternative definition could be that ROI only quantifies the fiscal/financial returns from an intervention.…”

Section: Discussionmentioning

confidence: 99%

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Analyses of the return on investment of public health interventions: a scoping review and recommendations for future studies

Turner,

Hori,

Revill

et al. 2023

BMJ Glob Health

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Return on investment (ROI) analysis is increasingly being used for evaluating the value for money of public health interventions. Given its potential role for informing health policies, it is important that there is a more comprehensive understanding of ROI analysis within the global health field. To address this gap in the literature, we conducted a scoping review of recent research articles reporting an ROI metric for a health intervention within the public sector in any country setting. The database search was limited to literature published in English and studies published between 1 January 2018 and 14 June 2021. Uses and settings where the ROI metric is being applied, key methodological features of the calculations and the types of economic benefits included were extracted. 118 relevant studies were included within this scoping review. We found that ROI analyses of health interventions differed between those that only included fiscal savings (such as prevented medical expenses) and those which incorporated a wider range of benefits (such as monetised health benefits). This highlights the variation in the definition of ROI analyses and supports the finding that ROI analyses are used for a range of different research questions/purposes within the healthcare sector. We also found that the methodologies used in ROI calculations were inconsistent and often poorly reported. This review demonstrates that there is notable variation in the methodology surrounding recent ROI calculations of healthcare interventions, as well as the definition of ROI analysis. We recommend that ROI metrics should be carefully interpreted before they are used to inform policy decisions regarding the allocation of healthcare resources. To improve the consistency of future studies, we also set out recommended use cases for ROI analysis and a reporting checklist.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Analyses of the return on investment of public health interventions: a scoping review and recommendations for future studies

Turner,

Hori,

Revill

et al. 2023

BMJ Glob Health

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“…To the extent possible, this study follows the recommendations of the Second Panel on Cost-Effectiveness in Health and Medicine by evaluating cost-effectiveness from both a health payer and societal perspective [ 21 ]. While robust data on COVID-related productivity (e.g., absenteeism, presenteeism, household contributions, and caregiving) in surviving patients and COVID-related impact on other non-healthcare sector (e.g., consumption, social services) elements are not yet available, anchoring productivity losses to mortality allows for a conservative estimate to inform current decision-making following recommended best practices [ 21 , 22 ]. As more data on treatment performance and COVID-19 burden emerge, models will need to evolve accordingly.…”

Section: Discussionmentioning

confidence: 99%

“…Consistent with the themes in this current debate on the value of treatments during a pandemic, the Second Panel on Cost-Effectiveness in Health and Medicine recommended that assessments of new innovations present both a health payer and a societal perspective to support transparent decisions on allocation of healthcare resources [ 21 , 22 ]. Despite these recommendations, recent CEAs of interventions for COVID-19 have either not incorporated a societal perspective or have reported a limited societal perspective based only on limited assumptions from other diseases [ 15 , 23 , 24 ].…”

Section: Introductionmentioning

confidence: 99%

A Cost-Effectiveness Framework for COVID-19 Treatments for Hospitalized Patients in the United States

Sheinson¹,

Dang²,

Shah³

et al. 2021

Adv Ther

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Introduction The COVID-19 pandemic is a global crisis impacting population health and the economy. We describe a cost-effectiveness framework for evaluating acute treatments for hospitalized patients with COVID-19, considering a broad spectrum of potential treatment profiles and perspectives within the US healthcare system to ensure incorporation of the most relevant clinical parameters, given evidence currently available. Methods A lifetime model, with a short-term acute care decision tree followed by a post-discharge three-state Markov cohort model, was developed to estimate the impact of a potential treatment relative to best supportive care (BSC) for patients hospitalized with COVID-19. The model included information on costs and resources across inpatient levels of care, use of mechanical ventilation, post-discharge morbidity from ventilation, and lifetime healthcare and societal costs. Published literature informed clinical and treatment inputs, healthcare resource use, unit costs, and utilities. The potential health impacts and cost-effectiveness outcomes were assessed from US health payer, societal, and fee-for-service (FFS) payment model perspectives. Results Viewing results in aggregate, treatments that conferred at least a mortality benefit were likely to be cost-effective, as all deterministic and sensitivity analyses results fell far below willingness-to-pay thresholds using both a US health payer and FFS payment perspective, with and without societal costs included. In the base case, incremental cost-effectiveness ratios (ICER) ranged from $22,933 from a health payer perspective using bundled payments to $8028 from a societal perspective using a FFS payment model. Even with conservative assumptions on societal impact, inclusion of societal costs consistently produced ICERs 40–60% lower than ICERs for the payer perspective. Conclusion Effective COVID-19 treatments for hospitalized patients may not only reduce disease burden but also represent good value for the health system and society. Though data limitations remain, this cost-effectiveness framework expands beyond current models to include societal costs and post-discharge ventilation morbidity effects of potential COVID-19 treatments. Supplementary Information The online version contains supplementary material available at 10.1007/s12325-021-01654-5.

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“…Hence, while it is very relevant for HTA to consider both payer and society perspectives of treatment benefits for an optimized resource allocation, especially for innovative and breakthrough therapies including GTs, the adoption of the societal perspectives cannot be assumed to occur in the short- or medium terms in countries where this perspective is presently not considered due to a tight administrative or time constraints ( 48 ).…”

Section: Economic Analysismentioning

confidence: 99%

Gene Therapy Evidence Generation and Economic Analysis: Pragmatic Considerations to Facilitate Fit-for-Purpose Health Technology Assessment

Qiu

Pochopien²,

Liang

et al. 2022

Front. Public Health

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Gene therapies (GTs) are considered to be a paradigm-shifting class of treatments with the potential to treat previously incurable diseases or those with significant unmet treatment needs. However, considerable challenges remain in their health technology assessment (HTA), mainly stemming from the inability to perform robust clinical trials to convince decision-makers to pay the high prices for the potential long-term treatment benefits provided. This article aims to review the recommendations that have been published for evidence generation and economic analysis for GTs against the feasibility of their implementation within current HTA decision analysis frameworks. After reviewing the systematically identified literature, we found that questions remain on the appropriateness of GT evidence generation, considering that additional, broader values brought by GTs seem insufficiently incorporated within proposed analytic methods. In cases where innovative methods are proposed, HTA organizations remain highly conservative and resistant to change their reference case and decision analysis framework. Such resistances are largely attributed to the substantial evidence uncertainty, resource-consuming administration process, and the absence of consensus on the optimized methodology to balance all the advantages and potential pitfalls of GTs.

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Correction to: Perspective and Costing in Cost‑Effectiveness Analysis, 1974–2018

Abstract: The article Perspective and Costing in Cost-Effectiveness Analysis.

Cited by 5 publications

References 0 publications

Analyses of the return on investment of public health interventions: a scoping review and recommendations for future studies

Analyses of the return on investment of public health interventions: a scoping review and recommendations for future studies

A Cost-Effectiveness Framework for COVID-19 Treatments for Hospitalized Patients in the United States

Gene Therapy Evidence Generation and Economic Analysis: Pragmatic Considerations to Facilitate Fit-for-Purpose Health Technology Assessment

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