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      Measuring health-related quality of life of older people with frailty receiving acute care: feasibility and psychometric performance of the EuroQol EQ-5D


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          Although outcome goals for acute healthcare among older people living with frailty often include Health-Related Quality of Life (HRQoL) and other patient-reported outcome measures (PROMs), current quality metrics usually focus on waiting times and survival. Lay and patient review have identified the EuroQol EQ-5D as a candidate measure for this setting. This research appraised the EQ-5D for feasibility, psychometric performance, and respondents’ outcomes in the acute frailty setting.


          People aged 65 + with Clinical Frailty Scale (CFS) 5–8 were recruited from eight UK hospitals’ emergency care and acute admissions settings. They completed the five-level EQ-5D and the EQ-VAS. Feasibility was assessed with completion times and completeness. For reliability, response distributions and internal consistency were analysed. Finally, EQ-Index values were compared with demographic characteristics and service outcomes for construct validity.


          The 232 participants were aged 65–102. 38% responded in emergency departments and 62% in admissions wards. Median completion time was 12 (IQR, 11) minutes. 98% responses were complete. EQ-5D had acceptable response distribution (SD 1.1–1.3) and internal consistency (Cronbach’s alpha 0.69). EQ-VAS demonstrated a midpoint response pattern. Median EQ-Index was 0.574 (IQR, 0.410) and was related positively with increasing age ( p = 0.010) and negatively with CFS ( p < 0.001). Participants with higher CFS had more frequent problems with mobility, self-care, and usual activities.


          Administration of the EQ-5D was feasible in these emergency and acute frailty care settings. EQ-5D had acceptable properties, while EQ-VAS appeared problematic. Participants with more severe frailty had also poorer HRQoL.

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          Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L)

          Purpose This article introduces the new 5-level EQ-5D (EQ-5D-5L) health status measure. Methods EQ-5D currently measures health using three levels of severity in five dimensions. A EuroQol Group task force was established to find ways of improving the instrument’s sensitivity and reducing ceiling effects by increasing the number of severity levels. The study was performed in the United Kingdom and Spain. Severity labels for 5 levels in each dimension were identified using response scaling. Focus groups were used to investigate the face and content validity of the new versions, including hypothetical health states generated from those versions. Results Selecting labels at approximately the 25th, 50th, and 75th centiles produced two alternative 5-level versions. Focus group work showed a slight preference for the wording ‘slight-moderate-severe’ problems, with anchors of ‘no problems’ and ‘unable to do’ in the EQ-5D functional dimensions. Similar wording was used in the Pain/Discomfort and Anxiety/Depression dimensions. Hypothetical health states were well understood though participants stressed the need for the internal coherence of health states. Conclusions A 5-level version of the EQ-5D has been developed by the EuroQol Group. Further testing is required to determine whether the new version improves sensitivity and reduces ceiling effects.
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            A global clinical measure of fitness and frailty in elderly people.

            There is no single generally accepted clinical definition of frailty. Previously developed tools to assess frailty that have been shown to be predictive of death or need for entry into an institutional facility have not gained acceptance among practising clinicians. We aimed to develop a tool that would be both predictive and easy to use. We developed the 7-point Clinical Frailty Scale and applied it and other established tools that measure frailty to 2305 elderly patients who participated in the second stage of the Canadian Study of Health and Aging (CSHA). We followed this cohort prospectively; after 5 years, we determined the ability of the Clinical Frailty Scale to predict death or need for institutional care, and correlated the results with those obtained from other established tools. The CSHA Clinical Frailty Scale was highly correlated (r = 0.80) with the Frailty Index. Each 1-category increment of our scale significantly increased the medium-term risks of death (21.2% within about 70 mo, 95% confidence interval [CI] 12.5%-30.6%) and entry into an institution (23.9%, 95% CI 8.8%-41.2%) in multivariable models that adjusted for age, sex and education. Analyses of receiver operating characteristic curves showed that our Clinical Frailty Scale performed better than measures of cognition, function or comorbidity in assessing risk for death (area under the curve 0.77 for 18-month and 0.70 for 70-month mortality). Frailty is a valid and clinically important construct that is recognizable by physicians. Clinical judgments about frailty can yield useful predictive information.
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              Interim scoring for the EQ-5D-5L: mapping the EQ-5D-5L to EQ-5D-3L value sets.

              A five-level version of the EuroQol five-dimensional (EQ-5D) descriptive system (EQ-5D-5L) has been developed, but value sets based on preferences directly elicited from representative general population samples are not yet available. The objective of this study was to develop values sets for the EQ-5D-5L by means of a mapping ("crosswalk") approach to the currently available three-level version of the EQ-5D (EQ-5D-3L) values sets. The EQ-5D-3L and EQ-5D-5L descriptive systems were coadministered to respondents with conditions of varying severity to ensure a broad range of levels of health across EQ-5D questionnaire dimensions. We explored four models to generate value sets for the EQ-5D-5L: linear regression, nonparametric statistics, ordered logistic regression, and item-response theory. Criteria for the preferred model included theoretical background, statistical fit, predictive power, and parsimony. A total of 3691 respondents were included. All models had similar fit statistics. Predictive power was slightly better for the nonparametric and ordered logistic regression models. In considering all criteria, the nonparametric model was selected as most suitable for generating values for the EQ-5D-5L. The nonparametric model was preferred for its simplicity while performing similarly to the other models. Being independent of the value set that is used, it can be applied to transform any EQ-5D-3L value set into EQ-5D-5L index values. Strengths of this approach include compatibility with three-level value sets. A limitation of any crosswalk is that the range of index values is restricted to the range of the EQ-5D-3L value sets. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

                Author and article information

                BMC Emerg Med
                BMC Emerg Med
                BMC Emergency Medicine
                BioMed Central (London )
                19 November 2023
                19 November 2023
                : 23
                : 137
                [1 ]College of Life Sciences, George Davies Centre, University of Leicester, ( https://ror.org/04h699437) Leicester, UK
                [2 ]Emergency and Specialist Medicine, University Hospitals of Leicester NHS Trust, ( https://ror.org/02fha3693) Leicester, UK
                [3 ]GRID grid.268922.5, ISNI 0000 0004 0427 2580, MRC Unit for Lifelong Health and Ageing, University College London, ; London, UK
                [4 ]Department of Family Medicine, National University Health System, ( https://ror.org/05tjjsh18) Singapore, Singapore
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                : 5 July 2023
                : 11 November 2023
                Funded by: FundRef http://dx.doi.org/10.13039/501100000272, National Institute for Health and Care Research;
                Award ID: Doctoral Research Fellowship 300901
                Award ID: Senior Investigator
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2023

                Emergency medicine & Trauma
                frailty,geriatric emergency medicine,patient-reported outcome,quality of life


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