IDEAS home Printed from
   My bibliography  Save this article

An Updated Systematic Review of Studies Mapping (or Cross-Walking) Measures of Health-Related Quality of Life to Generic Preference-Based Measures to Generate Utility Values


  • Clara Mukuria

    (University of Sheffield)

  • Donna Rowen

    (University of Sheffield)

  • Sue Harnan

    (University of Sheffield)

  • Andrew Rawdin

    (University of Sheffield)

  • Ruth Wong

    (University of Sheffield)

  • Roberta Ara

    (University of Sheffield)

  • John Brazier

    (University of Sheffield)


Background Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values (HSUVs) from data obtained from another health-related quality of life (HRQoL) measure. There have been several methodological developments in this area since a previous review up to 2007. Objective To provide an updated review of all mapping studies that map from HRQoL measures to target generic preference-based measures (EQ-5D measures, SF-6D, HUI measures, QWB, AQoL measures, 15D/16D/17D, CHU-9D) published from January 2007 to October 2018. Data sources A systematic review of English language articles using a variety of approaches: searching electronic and utilities databases, citation searching, targeted journal and website searches. Study selection Full papers of studies that mapped from one health measure to a target preference-based measure using formal statistical regression techniques. Data extraction Undertaken by four authors using predefined data fields including measures, data used, econometric models and assessment of predictive ability. Results There were 180 papers with 233 mapping functions in total. Mapping functions were generated to obtain EQ-5D-3L/EQ-5D-5L-EQ-5D-Y (n = 147), SF-6D (n = 45), AQoL-4D/AQoL-8D (n = 12), HUI2/HUI3 (n = 13), 15D (n = 8) CHU-9D (n = 4) and QWB-SA (n = 4) HSUVs. A large number of different regression methods were used with ordinary least squares (OLS) still being the most common approach (used ≥ 75% times within each preference-based measure). The majority of studies assessed the predictive ability of the mapping functions using mean absolute or root mean squared errors (n = 192, 82%), but this was lower when considering errors across different categories of severity (n = 92, 39%) and plots of predictions (n = 120, 52%). Conclusions The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions.

Suggested Citation

  • Clara Mukuria & Donna Rowen & Sue Harnan & Andrew Rawdin & Ruth Wong & Roberta Ara & John Brazier, 2019. "An Updated Systematic Review of Studies Mapping (or Cross-Walking) Measures of Health-Related Quality of Life to Generic Preference-Based Measures to Generate Utility Values," Applied Health Economics and Health Policy, Springer, vol. 17(3), pages 295-313, June.
  • Handle: RePEc:spr:aphecp:v:17:y:2019:i:3:d:10.1007_s40258-019-00467-6
    DOI: 10.1007/s40258-019-00467-6

    Download full text from publisher

    File URL:
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL:
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Montse Roset & Xavier Badia & Anna Forsythe & Susan Webb, 2013. "Mapping CushingQoL Scores onto SF-6D Utility Values in Patients with Cushing’s Syndrome," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 6(2), pages 103-111, June.
    2. Gang Chen & Julie Ratcliffe, 2015. "A Review of the Development and Application of Generic Multi-Attribute Utility Instruments for Paediatric Populations," PharmacoEconomics, Springer, vol. 33(10), pages 1013-1028, October.
    3. Rowen, D & Brazier, J & Roberts, J, 2008. "Mapping SF-36 onto the EQ-5D index: how reliable is the relationship?," MPRA Paper 29831, University Library of Munich, Germany.
    4. Caterina Conigliani & Andrea Manca & Andrea Tancredi, 2015. "Prediction of patient-reported outcome measures via multivariate ordered probit models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(3), pages 567-591, June.
    5. Chun Fan Lee & Raymond Ng & Nan Luo & Yin Bun Cheung, 2018. "Development of Conversion Functions Mapping the FACT-B Total Score to the EQ-5D-5L Utility Value by Three Linking Methods and Comparison with the Ordinary Least Square Method," Applied Health Economics and Health Policy, Springer, vol. 16(5), pages 685-695, October.
    6. Christopher McCabe & Katherine Stevens & Jennifer Roberts & John Brazier, 2005. "Health state values for the HUI 2 descriptive system: results from a UK survey," Health Economics, John Wiley & Sons, Ltd., vol. 14(3), pages 231-244, March.
    7. Tomas Mlcoch & Jan Tuzil & Liliana Sedova & Jiri Stolfa & Monika Urbanova & David Suchy & Andrea Smrzova & Jitka Jircikova & Tereza Hrnciarova & Karel Pavelka & Tomas Dolezal, 2018. "Mapping Quality of Life (EQ-5D) from DAPsA, Clinical DAPsA and HAQ in Psoriatic Arthritis," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 11(3), pages 329-340, June.
    8. Monica Hernandez Alava & Allan Wailoo, 2015. "Fitting adjusted limited dependent variable mixture models to EQ-5D," Stata Journal, StataCorp LP, vol. 15(3), pages 737-750, September.
    9. Julie Ratcliffe & Elisabeth Huynh & Katherine Stevens & John Brazier & Michael Sawyer & Terry Flynn, 2016. "Nothing About Us Without Us? A Comparison of Adolescent and Adult Health‐State Values for the Child Health Utility‐9D Using Profile Case Best–Worst Scaling," Health Economics, John Wiley & Sons, Ltd., vol. 25(4), pages 486-496, April.
    Full references (including those not matched with items on IDEAS)


    Blog mentions

    As found by, the blog aggregator for Economics research:
    1. Rachel Houten’s journal round-up for 8th July 2019
      by Rachel Houten in The Academic Health Economists' Blog on 2019-07-08 11:00:07


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Matthew Franklin & James Lomas & Gerry Richardson, 2020. "Conducting Value for Money Analyses for Non-randomised Interventional Studies Including Service Evaluations: An Educational Review with Recommendations," PharmacoEconomics, Springer, vol. 38(7), pages 665-681, July.
    2. Nicholas Mitsakakis & Karen E. Bremner & George Tomlinson & Murray Krahn, 2020. "Exploring the Benefits of Transformations in Health Utility Mapping," Medical Decision Making, , vol. 40(2), pages 183-197, February.
    3. Aurelie Meunier & Alexandra Soare & Helene Chevrou-Severac & Karl-Johan Myren & Tatsunori Murata & Louise Longworth, 2022. "Indirect and Direct Mapping of the Cancer-Specific EORTC QLQ-C30 onto EQ-5D-5L Utility Scores," Applied Health Economics and Health Policy, Springer, vol. 20(1), pages 119-131, January.
    4. Asrul Akmal Shafie & Irwinder Kaur Chhabra & Jacqueline Hui Yi Wong & Noor Syahireen Mohammed, 2021. "Mapping PedsQL™ Generic Core Scales to EQ-5D-3L utility scores in transfusion-dependent thalassemia patients," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(5), pages 735-747, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kim Dalziel & Max Catchpool & Borja García-Lorenzo & Inigo Gorostiza & Richard Norman & Oliver Rivero-Arias, 2020. "Feasibility, Validity and Differences in Adolescent and Adult EQ-5D-Y Health State Valuation in Australia and Spain: An Application of Best–Worst Scaling," PharmacoEconomics, Springer, vol. 38(5), pages 499-513, May.
    2. Donna Rowen & Oliver Rivero-Arias & Nancy Devlin & Julie Ratcliffe, 2020. "Review of Valuation Methods of Preference-Based Measures of Health for Economic Evaluation in Child and Adolescent Populations: Where are We Now and Where are We Going?," PharmacoEconomics, Springer, vol. 38(4), pages 325-340, April.
    3. Valentina Prevolnik Rupel & Marko Ogorevc, 2021. "EQ-5D-Y Value Set for Slovenia," PharmacoEconomics, Springer, vol. 39(4), pages 463-471, April.
    4. Donna Rowen & Clara Mukuria & Philip A. Powell & Allan Wailoo, 2022. "Exploring the Issues of Valuing Child and Adolescent Health States Using a Mixed Sample of Adolescents and Adults," PharmacoEconomics, Springer, vol. 40(5), pages 479-488, May.
    5. Roberta Ara & Donna Rowen & Clara Mukuria, 2017. "The Use of Mapping to Estimate Health State Utility Values," PharmacoEconomics, Springer, vol. 35(1), pages 57-66, December.
    6. Paul Mark Mitchell & Samantha Husbands & Sarah Byford & Philip Kinghorn & Cara Bailey & Tim J. Peters & Joanna Coast, 2021. "Challenges in developing capability measures for children and young people for use in the economic evaluation of health and care interventions," Health Economics, John Wiley & Sons, Ltd., vol. 30(9), pages 1990-2003, September.
    7. Ratcliffe, Julie & Huynh, Elisabeth & Chen, Gang & Stevens, Katherine & Swait, Joffre & Brazier, John & Sawyer, Michael & Roberts, Rachel & Flynn, Terry, 2016. "Valuing the Child Health Utility 9D: Using profile case best worst scaling methods to develop a new adolescent specific scoring algorithm," Social Science & Medicine, Elsevier, vol. 157(C), pages 48-59.
    8. Ning Gu & Chris Bell & Marc Botteman & Xiang Ji & John Carter & Ben Hout, 2012. "Estimating Preference-Based EQ-5D Health State Utilities or Item Responses from Neuropathic Pain Scores," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 5(3), pages 185-197, September.
    9. Michela Meregaglia & Amanda Whittal & Elena Nicod & Michael Drummond, 2020. "‘Mapping’ Health State Utility Values from Non-preference-Based Measures: A Systematic Literature Review in Rare Diseases," PharmacoEconomics, Springer, vol. 38(6), pages 557-574, June.
    10. Richard De Abreu Lourenço & Nancy Devlin & Kirsten Howard & Jason J. Ong & Julie Ratcliffe & Jo Watson & Esther Willing & Elisabeth Huynh, 2021. "Giving a Voice to Marginalised Groups for Health Care Decision Making," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 14(1), pages 5-10, January.
    11. Sampson, C. & Garau, M., 2019. "How Should We Measure Quality of Life Impact in Rare Disease? Recent Learnings in Spinal Muscular Atrophy," Briefings 002146, Office of Health Economics.
    12. Marisa Santos & Monica A. C. T. Cintra & Andrea L. Monteiro & Braulio Santos & Fernando Gusmão-filho & Mônica Viegas Andrade & Kenya Noronha & Luciane N. Cruz & Suzi Camey & Bernardo Tura & Paul Kin, 2016. "Brazilian Valuation of EQ-5D-3L Health States," Medical Decision Making, , vol. 36(2), pages 253-263, February.
    13. Rowen, D & Brazier, J & Tsuchiya, A & Hernández, M & Ibbotson, R, 2009. "The simultaneous valuation of states from multiple instruments using ranking and VAS data: methods and preliminary results," MPRA Paper 29841, University Library of Munich, Germany.
    14. McCabe, C & Brazier, J & Gilks, P & Tsuchiya, A & Roberts, J & O'Hagan, A & Stevens, K, 2004. "Estimating population cardinal health state valuation models from individual ordinal (rank) health state preference data," MPRA Paper 29759, University Library of Munich, Germany.
    15. Ramesh Lamsal & Jennifer D. Zwicker, 2017. "Economic Evaluation of Interventions for Children with Neurodevelopmental Disorders: Opportunities and Challenges," Applied Health Economics and Health Policy, Springer, vol. 15(6), pages 763-772, December.
    16. Brazier, John & Rowen, Donna & Tsuchiya, Aki & Yang, Yaling & Young, Tracy A., 2011. "The impact of adding an extra dimension to a preference-based measure," Social Science & Medicine, Elsevier, vol. 73(2), pages 245-253, July.
    17. Wenjing Zhou & Anle Shen & Zhihao Yang & Pei Wang & Bin Wu & Michael Herdman & Nan Luo, 2021. "Patient-caregiver agreement and test–retest reliability of the EQ-5D-Y-3L and EQ-5D-Y-5L in paediatric patients with haematological malignancies," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(7), pages 1103-1113, September.
    18. Christopher McCabe & Richard Edlin & David Meads & Chantelle Brown & Samer Kharroubi, 2013. "Constructing Indirect Utility Models: Some Observations on the Principles and Practice of Mapping to Obtain Health State Utilities," PharmacoEconomics, Springer, vol. 31(8), pages 635-641, August.
    19. Hernández-Alava, Mónica & Pudney, Stephen, 2017. "Econometric modelling of multiple self-reports of health states: The switch from EQ-5D-3L to EQ-5D-5L in evaluating drug therapies for rheumatoid arthritis," Journal of Health Economics, Elsevier, vol. 55(C), pages 139-152.
    20. Oliver Rivero-Arias & Melissa Ouellet & Alastair Gray & Jane Wolstenholme & Peter M. Rothwell & Ramon Luengo-Fernandez, 2010. "Mapping the Modified Rankin Scale (mRS) Measurement into the Generic EuroQol (EQ-5D) Health Outcome," Medical Decision Making, , vol. 30(3), pages 341-354, May.

    More about this item


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:aphecp:v:17:y:2019:i:3:d:10.1007_s40258-019-00467-6. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.