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      Mapping the Minnesota living with heart failure questionnaire (MLHFQ) to EQ-5D-5L in patients with heart failure

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          Abstract

          Background

          Mapping algorithms can be used to convert scores from a non-preference based instrument to health state utilities. The objective of this study was to develop mapping algorithms which will enable the Minnesota Living with Heart Failure Questionnaire (MLHFQ) scores to be converted into EQ-5D-5L utility scores that can be used in heart failure related cost utility studies.

          Method

          Patients diagnosed with heart failure were recruited from Australia. Mapping algorithms were developed using both direct and indirect response mapping approach. Three model specifications were considered to predict the EQ-5D-5 L utility score using MLHFQ total score (Model 1), MLHFQ domain scores (Model 2), or MLHFQ item scores (Model 3). Six regression techniques, each of which has the capability to cope with either skewness, heteroscedasticity, ceiling effects and/or the potential presence of outliers in the data set were used to identify the optimal mapping functions for each of the three models. Goodness-of-fit of the models were assessed using six indicators. In the absence of an external validation dataset, predictive performance of was assessed using three-fold cross validation method. In the indirect response mapping, EQ. 5D 5 L responses were predicted separately using the MLHFQ item scores using ordered logit model.

          Results

          A total of 141 patients participated in the study. The lowest mean absolute error (MAE) was recorded from the multivariable fractional polynomials (MFP) model in all three-model specifications. Regarding the indirect response mapping, results showed that the performance was comparable with the direct mapping approach based on root mean squared error (RMSE) but was worse based on MAE.

          Conclusion

          The MLHFQ can be mapped onto EQ-5D-5 L utilities with good predictive accuracy using both direct and indirect response mapping techniques. The reported mapping algorithms would facilitate calculation of health utility for economic evaluations related to heart failure.

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          Heart failure: preventing disease and death worldwide

          Piotr Ponikowski, Stefan D. Anker, Khalid AlHabib … (2014)
          Heart failure is a life-threatening disease and addressing it should be considered a global health priority. At present, approximately 26 million people worldwide are living with heart failure. The outlook for such patients is poor, with survival rates worse than those for bowel, breast or prostate cancer. Furthermore, heart failure places great stresses on patients, caregivers and healthcare systems. Demands on healthcare services, in particular, are predicted to increase dramatically over the next decade as patient numbers rise owing to ageing populations, detrimental lifestyle changes and improved survival of those who go on to develop heart failure as the final stage of another disease. It is time to ease the strain on healthcare systems through clear policy initiatives that prioritize heart failure prevention and champion equity of care for all. Despite the burdens that heart failure imposes on society, awareness of the disease is poor. As a result, many premature deaths occur. This is in spite of the fact that most types of heart failure are preventable and that a healthy lifestyle can reduce risk. Even after heart failure has developed, premature deaths could be prevented if people were taught to recognize the symptoms and seek immediate medical attention. Public awareness campaigns focusing on these messages have great potential to improve outcomes for patients with heart failure and ultimately to save lives. Compliance with clinical practice guidelines is also associated with improved outcomes for patients with heart failure. However, in many countries, there is considerable variation in how closely physicians follow guideline recommendations. To promote equity of care, improvements should be encouraged through the use of hospital performance measures and incentives appropriate to the locality. To this end, policies should promote the research required to establish an evidence base for performance measures that reflect improved outcomes for patients. Continuing research is essential if we are to address unmet needs in caring for patients with heart failure. New therapies are required for patients with types of heart failure for which current treatments relieve symptoms but do not address the disease. More affordable therapies are desperately needed in the economically developing world. International collaborative research focusing on the causes and treatment of heart failure worldwide has the potential to benefit tens of millions of people. Change at the policy level has the power to drive improvements in prevention and care that will save lives. It is time to make a difference across the globe by confronting the problem of heart failure.
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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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              A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures.

              John Brazier, Yaling Yang, Aki Tsuchiya … (2010)
              Clinical studies use a wide variety of health status measures to measure health related quality of life, many of which cannot be used in cost-effectiveness analysis using cost per quality adjusted life year (QALY). Mapping is one solution that is gaining popularity as it enables health state utility values to be predicted for use in cost per QALY analysis when no preference-based measure has been included in the study. This paper presents a systematic review of current practice in mapping between non-preference based measures and generic preference-based measures, addressing feasibility and validity, circumstances under which it should be considered and lessons for future mapping studies. This review found 30 studies reporting 119 different models. Performance of the mappings functions in terms of goodness-of-fit and prediction was variable and unable to be generalised across instruments. Where generic measures are not regarded as appropriate for a condition, mapping does not solve this problem. Most testing in the literature occurs at the individual level yet the main purpose of these functions is to predict mean values for subgroups of patients, hence more testing is required.
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                Author and article information

                Contributors
                Sameera Senanayake: sameerajayan.senanayake@hdr.qut.edu.au
                Journal
                Journal ID (nlm-ta): Health Qual Life Outcomes
                Journal ID (iso-abbrev): Health Qual Life Outcomes
                Title: Health and Quality of Life Outcomes
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1477-7525
                Publication date (Electronic): 29 April 2020
                Publication date PMC-release: 29 April 2020
                Publication date Collection: 2020
                Volume: 18
                Electronic Location Identifier: 115
                Affiliations
                [1 ]GRID grid.1024.7, ISNI 0000000089150953, Australian Centre for Health Service Innovation, School of Public Health and Social Work, Institute of Health and Biomedical Innovation, , Queensland University of Technology, ; 60 Musk Avenue, Kelvin Grove, QLD, 4059 Australia
                [2 ]Centre for Health Economics, Building H, Dandenong Rd, 900 Australia
                [3 ]GRID grid.1002.3, ISNI 0000 0004 1936 7857, Monash University, ; Caulfield East, VIC 3145 Australia
                [4 ]GRID grid.416100.2, ISNI 0000 0001 0688 4634, Royal Brisbane and Women’s Hospital, ; Butterfield St, Herston, QLD 4029 Australia
                Article
                Publisher ID: 1368
                DOI: 10.1186/s12955-020-01368-2
                PMC ID: 7189529
                PubMed ID: 32349782
                SO-VID: 7d0fa595-0940-44d3-9926-2e6b3b176450
                Copyright © © The Author(s) 2020
                License:

                Open AccessThis 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.

                History
                Date received : 21 June 2019
                Date accepted : 16 April 2020
                Funding
                Funded by: Heart Foundation, Australia
                Award ID: ID- 101407 VG2016
                Award Recipient :
                Categories
                Subject: Research
                Custom metadata
                issue-copyright-statement © The Author(s) 2020

                ScienceOpen disciplines: Health & Social care
                Keywords: mapping,minnesota living with heart failure (mlhfq),eq-5d-5 l,utility,direct mapping,indirect response mapping
                Data availability:
                ScienceOpen disciplines: Health & Social care
                Keywords: mapping, minnesota living with heart failure (mlhfq), eq-5d-5 l, utility, direct mapping, indirect response mapping

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