Advertisement

PharmacoEconomics

, Volume 28, Issue 6, pp 507–520 | Cite as

Does the Inclusion of a Cost Attribute Result in Different Preferences for the Surgical Treatment of Primary Basal Cell Carcinoma?

A Comparison of Two Discrete-Choice Experiments
  • Brigitte A. B. EssersEmail author
  • Debby van Helvoort-Postulart
  • Martin H. Prins
  • Martino Neumann
  • Carmen D. Dirksen
Original Research article

Abstract

Background: Nowadays, an increasing number of discrete-choice experiments (DCEs) incorporate cost as an attribute. However, the inclusion of a cost attribute, particularly within collectively funded healthcare systems, can be challenging because health services or goods are generally not traded in a market situation and individuals are not used to paying for a service or a good at the point of consumption.

Objective: To examine whether the inclusion of a cost attribute in a DCE results in different preferences regarding a surgical treatment for primary basal cell carcinoma (BCC) compared with a DCE without a cost attribute.

Methods: A randomized study was performed in which the impact of a cost attribute on the general public’s preferences for a surgical treatment (Mohs micrographic surgery [MMS] or standard excision [SE]) to remove BCC was examined. This was done by comparing the outcomes of two DCEs, one with a cost attribute (DCE_cost) and one without (DCE_nocost). Six attributes (recurrence, re-excision, travel time, surgical time, waiting time for surgical results, costs) and their levels were selected, based on results of a clinical trial, a cost-effectiveness study, a review and a focus group of patients who had recently received treatment for BCC. Outcomes of both DCEs were compared in terms of theoretical validity, relative importance of the attributes and the rank order of preferences.

Results: A total of 615 respondents (n = 303 for DCE_nocost; n = 312 for DCE_cost) were interviewed by telephone. This gave an overall response rate of 38%.

Respondents in DCE_nocost preferred a surgical treatment with a lower probability of recurrence, lower surgery time, lower waiting time and no risk for a re-excision. Respondents in DCE_cost showed the same preferences, but also preferred a treatment with less travel time and lower costs. Overall, respondents in both DCEs showed the same preference for a surgical treatment: MMS was preferred over SE.

Conclusion: Results suggest that, in this population, the inclusion of a cost attribute in a DCE leads to the same preference regarding a surgical treatment to remove BCC as a DCE without a cost attribute. However, further research in different settings is needed to confirm these findings.

Keywords

Travel Time Basal Cell Carcinoma Dominant Preference Cost Attribute Theoretical Validity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

No sources of funding were used to assist in the preparation of this study. The authors have no conflicts of interest that are directly relevant to the content of this study.

Supplementary material

40273_2012_28060507_MOESM1_ESM.pdf (316 kb)
Supplementary material, approximately 324 KB.

References

  1. 1.
    Lancsar E, Louviere J. Conducting discrete choice experiments to inform healthcare decision making. Pharmacoeconomics 2008; 26 (8): 661–77PubMedCrossRefGoogle Scholar
  2. 2.
    Aristides M, Weston AR, Fitzgerald P, et al. Patient preference and willingness to pay for Humalog Mix25 relative to Humulin 30/70: a multicountry application of a discrete-choice experiment. Value Health 2004; 7 (4): 442–54PubMedCrossRefGoogle Scholar
  3. 3.
    Phillips KA, Maddala T, Reed Johnson F. Measuring preferences for health care interventions using conjoint analysis: an application to HIV testing. Health Serv Res 2002; 37: 1681–705PubMedCrossRefGoogle Scholar
  4. 4.
    Hanson K, McPake B, Nakamba P, et al. Preferences for hospital quality in Zambia: results from a discrete choice experiment. Health Econ 2005; 14: 687–701PubMedCrossRefGoogle Scholar
  5. 5.
    Ossa DF, Briggs A, McIntosh E, et al. Recombinant erythropoietin for chemotherapy-related anaemia. Pharmacoeconomics 2007; 25 (3): 223–37PubMedCrossRefGoogle Scholar
  6. 6.
    Porteous T, Ryan M, Bond CM, et al. Preferences for selfcare or professional advice for minor illness: a discretechoice experiment. Br J Gen Pract 2007; 57: 911–7Google Scholar
  7. 7.
    Chuck A, Adamowicz W, Jacobs P, et al. The willingness to pay for reducing pain and pain related disability. Value Health 2008; 12 (4): 498–506PubMedCrossRefGoogle Scholar
  8. 8.
    Slothuus Skjoldborg U, Gyrd-Hansen D. Conjoint analysis: the cost-variable. An Achilles’heel? Health Econ 2003; 212: 479–91CrossRefGoogle Scholar
  9. 9.
    Verlegh PWJ, Schifferstein HNJ, Wittink DR. Range and number-of-levels in derived and stated measures of attribute importance. Market Lett 2002; 13: 41–52CrossRefGoogle Scholar
  10. 10.
    Bryan S, Buxton M, Sheldon R, et al. Magnetic resonance imaging for the investigation of knee injuries: an investigation of preferences. Health Econ 1998; 7 (7): 595–603PubMedCrossRefGoogle Scholar
  11. 11.
    De Vries E, van de Poll-Franse LV, Louwman WJ, et al. Predictions of skin cancer incidence in the Netherlands up to 2015. Br J Dermatol 2005; 152 (3): 481–8PubMedCrossRefGoogle Scholar
  12. 12.
    Essers BA, Dirksen CD, Nieman FH, et al. Cost-effectiveness of Mohs micrographic surgery vs surgical excision for basal cell carcinoma of the face. Arch Dermatol 2006; 142 (2): 187–94PubMedCrossRefGoogle Scholar
  13. 13.
    Mosterd K, Krekels GA, Nieman FH, et al. Surgical excision versus Mohs micrographic surgery for primary and recurrent basal cell carcinoma of the face: a prospective randomised trial with 5-years’ follow-up. Lancet Oncol 2008; 12: 1149–56CrossRefGoogle Scholar
  14. 14.
    Smeets NWJ, Krekels GAM, Ostertag JU, et al. Surgical excision versus Mohs micrographic surgery for basal cell carcinoma of the face: a prospective randomised trial. Lancet 2004; 364: 1766–72PubMedCrossRefGoogle Scholar
  15. 15.
    Thissen MR, Neumann HA, Schouten LJ. A systematic review of treatment modalities or primary basal cell carcinoma. Arch Dermatol 1999; 135: 1177–83PubMedCrossRefGoogle Scholar
  16. 16.
    Louviere JJ, Hensher DA, Swait JD. Stated choice methods: analysis and application. Cambridge: University Press, 2000CrossRefGoogle Scholar
  17. 17.
    Huber J, Zwerina K. The importance of utility balance in efficient choice designs. J Mark Res 1996; 8: 307–17CrossRefGoogle Scholar
  18. 18.
    Vick S, Scott A. Agency in health care: examining patients preferences for attributes of the doctor-patient relationship. J Health Econ 1998; 17: 587–605PubMedCrossRefGoogle Scholar
  19. 19.
    Scott A. Eliciting GPs’ preferences for pecuniary and non-pecuniary job characteristics. J Health Econ 2001; 20: 329–47PubMedCrossRefGoogle Scholar
  20. 20.
    Ryan M, Wordsworth S. Sensitivity of willingness to pay estimates to the level of attributes in discrete choice experiments. Scott J Polit Econ 2000; 47: 504–24CrossRefGoogle Scholar
  21. 21.
    Greene WH. Limdep version 8.0. users manual. New York: Econometric Software Inc., 1995Google Scholar
  22. 22.
    Malhotra NK, Birks DF. Marketing research: an applied approach [updated 2nd european edition]. Harlow: Prentice Hall, 2006Google Scholar
  23. 23.
    Richardson G, Bojke C, Kennedy A, et al. What outcomes are important to patients with long term conditions? A discrete choice experiment. Value Health 2009; 12: 331–9PubMedCrossRefGoogle Scholar
  24. 24.
    McIntosh E. Using discrete choice experiments within a cost-benefit analysis framework. Pharmacoeconomics 2006; 24 (9): 855–68PubMedCrossRefGoogle Scholar
  25. 25.
    Kjaer T, Bech M, Gyrd-Hansen D, et al. Ordering effects and price sensitivity in discrete-choice experiments: need we worry? Health Econ 2006; 15: 1217–28PubMedCrossRefGoogle Scholar
  26. 26.
    Islam T, Louviere JJ, Burke PF. Modeling the effects of including/excluding attributes in choice experiments on systematic and random components. Int J Res Market 2007; 24 (4): 289–300CrossRefGoogle Scholar

Copyright information

© Adis Data Information BV 2010

Authors and Affiliations

  • Brigitte A. B. Essers
    • 1
    Email author
  • Debby van Helvoort-Postulart
    • 1
  • Martin H. Prins
    • 1
    • 2
  • Martino Neumann
    • 3
  • Carmen D. Dirksen
    • 1
  1. 1.Department of Clinical Epidemiology and Medical Technology Assessment (KEMTA)University Hospital MaastrichtMaastrichtthe Netherlands
  2. 2.Department of EpidemiologyUniversity Hospital MaastrichtMaastrichtthe Netherlands
  3. 3.Department of DermatologyErasmus Medical Centre RotterdamRotterdamthe Netherlands

Personalised recommendations