QALYs for COVID-19: A Comparison of US EQ-5D-5L Value Sets

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Abstract

Background

In economic evaluations, quality-adjusted life-years (QALYs) can serve as a unit of measurement for disease burden. Obtaining QALY values for COVID-19 presents a challenge owing to the availability of two US EQ-5D-5L value sets and the potentially asymptomatic presentation of the disease. The first value set was completed allowing for the discounting of future health outcomes while the second value set is undiscounted.

Objective

The objective of this study was to compare the distribution of QALY values using a national survey and the two published value sets; and to estimate the association between COVID-19 outcomes and QALY losses.

Methods

Between 9 and 11 November, 2020, 1153 US adults completed the EQ-5D-5L instrument (five items and a visual analog scale) as well as self-reported their demographics, COVID-19 symptoms, and memberships to populations that are at risk of COVID-19 infection. The two US value sets were applied to the EQ-5D-5L responses to produce QALY values. We estimated the mean QALYs by visual analog scale decile and a generalized linear model of COVID-19 outcomes.

Results

The discounted values are higher than the undiscounted values for each visual analog scale decile owing to methodological differences. Persons at increased risk, with a fever in the past day, and with one or more other symptoms have significantly greater QALY losses ( p < 0.01). Overall, non-institutionalized individuals at risk of symptomatic clinical COVID-19 equal 0.68 for the 2016 value set (95% confidence interval 0.49–0.87) and 0.10 for the 2017 value set (95% confidence interval − 0.31 to 0.51) QALYs.

Conclusions

Multiple studies have shown that decision makers discount future health outcomes, which increase QALY values. This study confronts the practical implications of these methodological advances for use in COVID-19 economic evaluations. Health economists will be able to use the QALY values in this study to better evaluate health interventions against COVID-19.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40271-021-00509-z.

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Most cited references 13

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EQ-5D and the EuroQol Group: Past, Present and Future

Nancy J Devlin, Richard Brooks (2017)

Over the period 1987–1991 an inter-disciplinary five-country group developed the EuroQol instrument, a five-dimensional three-level generic measure subsequently termed the ‘EQ-5D’. It was designed to measure and value health status. The salient features of its development and its consolidation and expansion are discussed. Initial expansion came, in particular, in the form of new language versions. Their development raised translation and semantic issues, experience with which helped feed into the design of two further instruments, the EQ-5D-5L and the youth version EQ-5D-Y. The expanded usage across clinical programmes, disease and condition areas, population surveys, patient-reported outcomes, and value sets is outlined. Valuation has been of continued relevance for the Group as this has allowed its instruments to be utilised as part of the economic appraisal of health programmes and their incorporation into health technology assessments. The future of the Group is considered in the context of: (1) its scientific strategy, (2) changes in the external environment affecting the demand for EQ-5D, and (3) a variety of issues it is facing in the context of the design of the instrument, its use in health technology assessment, and potential new uses for EQ-5D outside of clinical trials and technology appraisal. Electronic supplementary material The online version of this article (doi:10.1007/s40258-017-0310-5) contains supplementary material, which is available to authorized users.

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Health-related quality of life measured using the EQ-5D–5L: South Australian population norms

Nikki McCaffrey, Billingsley Kaambwa, David Currow … (2016)

Background Although a five level version of the widely-used EuroQol 5 dimensions (EQ-5D) instrument has been developed, population norms are not yet available for Australia to inform the future valuation of health in economic evaluations. The aim of this study was to estimate HrQOL normative values for the EQ-5D-5L preference-based measure in a large, randomly selected, community sample in South Australia. Methods The EQ-5D-5L instrument was included in the 2013 South Australian Health Omnibus Survey, an interviewer-administered, face-to-face, cross-sectional survey. Respondents rated their level of impairment across dimensions (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression) and global health rating on a visual analogue scale (EQ-VAS). Utility scores were derived using the newly-developed UK general population-based algorithm and relationships between utility and EQ-VAS scores and socio-demographic factors were also explored using multivariate regression analyses. Results Ultimately, 2,908 adults participated in the survey (63.4 % participation rate). The mean utility and EQ-VAS scores were 0.91 (95 CI 0.90, 0.91) and 78.55 (95 % CI 77.95, 79.15), respectively. Almost half of respondents reported no problems across all dimensions (42.8 %), whereas only 7.2 % rated their health >90 on the EQ-VAS (100 = the best health you can imagine). Younger age, male gender, longer duration of education, higher annual household income, employment and marriage/de facto relationships were all independent, statistically significant predictors of better health status (p < 0.01) measured with the EQ-VAS. Only age and employment status were associated with higher utility scores, indicating fundamental differences between these measures of health status. Conclusions This is the first Australian study to apply the EQ-5D-5L in a large, community sample. Overall, findings are consistent with EQ-5D-5L utility and VAS scores reported for other countries and indicate that the majority of South Australian adults report themselves in full health. When valuing health in Australian economic evaluations, the utility population norms can be used to estimate HrQOL. More generally, the EQ-VAS score may be a better measure of population health given the smaller ceiling effect and broader coverage of HrQOL dimensions. Further research is recommended to update EQ-5D-5L population norms using the Australian general population specific scoring algorithm once this becomes publically available.

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Long-term consequences of COVID-19: research needs

Dana Yelin, Eytan Wirtheim, Pauline Vetter … (2020)

Weeks and months after the onset of acute COVID-19, people continue to suffer. Paul Garner, a professor of epidemiology at Liverpool School of Tropical Medicine, UK, wrote on the 95th day after the onset of symptoms that “I am unable to be out of bed for more than three hours at a stretch, my arms and legs are permanently fizzing as if injected with Szechuan peppercorns, I have ringing in the ears, intermittent brain fog, palpitations, and dramatic mood swings.” 1 Other people also describe similar complaints.2, 3 78 of 100 patients in an observational cohort study who had recovered from COVID-19 had abnormal findings on cardiovascular MRI (median of 71 days after diagnosis) and 36 of those reported dyspnoea and unusual fatigue. 4 We are seeing patients in clinics dedicated to COVID-19 convalescents, and for some of these patients the return to their former health trajectory is slow and painful. These patients are not only those recovering from the severe form of the acute disease (ie, post intensive care syndrome), but also those who had mild and moderate disease. A summary of the most common complaints, based on our clinical impressions, is shown in the appendix (p 1). Rare long-term sequelae can result after other viral infections—eg, infectious mononucleosis, measles, and hepatitis B. Long-term sequelae of COVID-19 are unknown (as are many aspects of the acute disease). Long-term consequences were observed in survivors of severe acute respiratory syndrome (SARS)5, 6 but it is unknown whether lessons from SARS are applicable to COVID-19. Other concerns are rising: does acute COVID-19 cause diabetes? 7 Or other metabolic disorders? Will patients develop interstitial lung disease? We are still in the first months of the pandemic and we do not know what to tell our patients when they are asking about the course and prognosis of their ongoing complaints. The number of people affected by COVID-19 is unprecedented. We owe good answers on the long-term consequences of the disease to our patients and health-care providers. The obvious answer is in research. In the appendix (p 2) we have compiled a list of questions we think should be answered. This list is based on the authors' views and experience rather than on the literature, which is scant. For efficient research and for research that our patients (and we) can trust, some common problems in the description and research of acute COVID-19 should be avoided. The main problem is fragmentation. For example, Wynants and colleagues 8 described 47 models for predicting COVID-19 infection and 16 prognostic models for COVID-19 patients. Most of these models had a high risk of bias and most of them did not have external validation. Additionally, randomised controlled trials on interventions to treat the acute disease were stopped before enlisting the planned sample size. Although much effort was invested in these studies, we have learned little. Fragmentation also happens by discipline,6, 7 and the follow-up (for clinical and research purposes) should be multinational, multidisciplinary, comprehensive, and homogenous. Careful recording of symptoms and patient examination should allow understanding of which part of the sequelae is common to all severe infections, which symptoms might be explained by the anxiety caused by a new disease and by the isolation, 9 and which symptoms are secondary to a complicated form of COVID-19 (eg, pulmonary involvement during the acute disease). If indeed COVID-19 is causing long-term sequelae then are the mechanisms underlying the long-term consequences immunological? Or caused by new or relapsing inflammation, ongoing infection, or side-effects of immunomodulatory treatment? Such data can serve to point at candidate management strategies to be tested in trials. Support for research is needed on the trajectory of people recovering from COVID-19. To avoid the problems we have witnessed in the research of the acute phase of the disease, a clear definition of patient inclusion criteria, a common protocol, and uniform definitions of outcomes and ways to measure them are required. Additionally, data should be collected in real time and computational tools are needed to be able to do this (appendix p 3). The participation of an international and interdisciplinary group of researchers is essential. Multisite and multinational projects are needed because a description from one group or one site cannot discern between universal features and features of the local health system or the local population. By comparing data from different sites and countries we can learn which characteristics of the disease are universal and which are local. In addition to improving the care of our patients with long-term consequences of COVID-19, we hope to be able to join such necessary research efforts soon.

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Author and article information

Contributors

Stephen Poteet:

ORCID: http://orcid.org/0000-0002-4502-6461

poteet.stephen@spcollege.edu

Benjamin M. Craig: bcraig@usf.edu

Journal

Journal ID (nlm-ta): Patient

Journal ID (iso-abbrev): Patient

Title: The Patient

Publisher: Springer International Publishing (Cham )

ISSN (Print): 1178-1653

ISSN (Electronic): 1178-1661

Publication date (Electronic): 30 March 2021

Pages: 1-7

Affiliations

[1 ]GRID grid.422533.1, ISNI 0000 0001 0513 3222, Department of Social/Behavioral Sciences, , St. Petersburg College, ; 2465 Drew St, ES313D, Clearwater, FL 33765 USA

[2 ]GRID grid.170693.a, ISNI 0000 0001 2353 285X, Department of Economics, , University of South Florida, ; Tampa, FL USA

Author information

Stephen Poteet http://orcid.org/0000-0002-4502-6461

Article

Publisher ID: 509

DOI: 10.1007/s40271-021-00509-z

PMC ID: 8007385

PubMed ID: 33782840

SO-VID: a6c82f01-4075-4e92-b3dd-0448a45c9a80

License:

This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

QALYs for COVID-19: A Comparison of US EQ-5D-5L Value Sets

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Abstract

Background

Objective

Methods

Results

Conclusions

Supplementary Information

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Novel Coronavirus Disease COVID-19

Most cited references 13

EQ-5D and the EuroQol Group: Past, Present and Future

Health-related quality of life measured using the EQ-5D–5L: South Australian population norms

Long-term consequences of COVID-19: research needs

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