The Patient - Patient-Centered Outcomes Research

, Volume 10, Issue 6, pp 739–751 | Cite as

Choosing a Doctor: Does Presentation Format Affect the Way Consumers Use Health Care Performance Information?

  • Patricia Kenny
  • Stephen Goodall
  • Deborah J. Street
  • Jessica Greene
Original Research Article



Choosing a new health service provider can be difficult and is dependent on the type and clarity of the information available. This study examines if the presentation of service quality information affects the decisions of consumers choosing a general medical practice.


The aim was to examine the impact of presentation format on attribute level interpretation and relative importance.


A discrete choice experiment eliciting preferences for a general medical practice was conducted using four different presentation formats for service quality attributes: (1) frequency and percentage with an icon array, (2) star ratings, (3) star ratings with a text benchmark, and (4) percentage alone. A total of 1208 respondents from an online panel were randomised to see two formats, answering nine choices for each, where one was a dominated choice. Logistic regression was used to assess the impact of presentation format on the probability of choosing a dominated alternative. A generalised multinomial logit model was used to estimate the relative importance of the attribute levels.


The probability of incorrectly choosing a dominated alternative was significantly higher when the quality information was presented as a percentage relative to a frequency with icon array, star rating or bench-marked star rating. Preferences for a practice did not differ significantly by presentation format, nor did the probability of finding the information difficult to understand.


Quantitative health service quality information will be more useful to consumers if presented by combining the numerical information with a graphic, or using a star rating if appropriate for the context.


Presentation Format Attribute Level Discrete Choice Experiment Thought Style Star Rating 
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.


Author contributions

Stephen Goodall and Patricia Kenny conceptualised and designed the study with input from Deborah Street and Jessica Greene. Deborah Street produced the design for the discrete choice experiment. Patricia Kenny analysed the data and drafted the manuscript. All authors edited the manuscript and approved the final version.

Compliance with Ethical Standards

The research was part of a programme of research that was approved by the University of Technology Sydney Human Research Ethics Committee (Approval 2015000135). Participants were adult volunteers with an online panel and indicated consent by completing the online survey. Patricia Kenny has no potential conflicts of interest to declare. Stephen Goodall has no potential conflicts of interest to declare. Deborah Street has no potential conflicts of interest to declare. Jessica Greene has no potential conflicts of interest to declare.

Financial support

The research was funded by the Research in the Finance and Economics of Primary Health Care (ReFinE-PHC) Centre of Research Excellence under the Australian Primary Health Care Research Institute’s (APHCRI’s) Centres of Research Excellence funding scheme, which was supported by a grant from the Australian Government’s Department of Health. The paper does not necessarily reflect the views of APHCRI or the Australian Government.

Supplementary material

40271_2017_245_MOESM1_ESM.docx (50 kb)
Supplementary material 1 (DOCX 50 kb)
40271_2017_245_MOESM2_ESM.pdf (45 kb)
Supplementary material 2 (PDF 44 kb)
40271_2017_245_MOESM3_ESM.pdf (49 kb)
Supplementary material 3 (PDF 49 kb)
40271_2017_245_MOESM4_ESM.pdf (49 kb)
Supplementary material 4 (PDF 49 kb)
40271_2017_245_MOESM5_ESM.pdf (30 kb)
Supplementary material 5 (PDF 30 kb)


  1. 1.
    Australian Institute of Health and Welfare. Performance and Accountability Framework. 2016. Accessed 26th October 2016.
  2. 2.
    Rechel B, McKee M, Haas M, Marchildon GP, Bousquet F, Blümel M, et al. Public reporting on quality, waiting times and patient experience in 11 high-income countries. Health Policy. 2016;120(4):377–83.CrossRefPubMedGoogle Scholar
  3. 3.
    Victoor A, Delnoij DM, Friele RD, Rademakers JJ. Determinants of patient choice of healthcare providers: a scoping review. BMC Health Serv Res. 2012;12:272.CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Hildon Z, Allwood D, Black N. Impact of format and content of visual display of data on comprehension, choice and preference: a systematic review. Int J Qual Health Care. 2012;24(1):55–64.CrossRefPubMedGoogle Scholar
  5. 5.
    Kurtzman ET, Greene J. Effective presentation of health care performance information for consumer decision making: a systematic review. Patient Educ Couns. 2016;99(1):36–43.CrossRefPubMedGoogle Scholar
  6. 6.
    Trevena LJ, Zikmund-Fisher BJ, Edwards A, Gaissmaier W, Galesic M, Han PK, et al. Presenting quantitative information about decision outcomes: a risk communication primer for patient decision aid developers. BMC Med Inform Decis Mak. 2013;13(2):1–15.Google Scholar
  7. 7.
    West SL, Squiers LB, McCormack L, Southwell BG, Brouwer ES, Ashok M, et al. Communicating quantitative risks and benefits in promotional prescription drug labeling or print advertising. Pharmacoepidemiol Drug Saf. 2013;22(5):447–58.CrossRefPubMedGoogle Scholar
  8. 8.
    Peters E, Hart PS, Tusler M, Fraenkel L. Numbers matter to informed patient choices: a randomized design across age and numeracy levels. Med Decis Mak. 2014;34(4):430–42.CrossRefGoogle Scholar
  9. 9.
    Sinayev A, Peters E, Tusler M, Fraenkel L. Presenting numeric information with percentages and descriptive risk labels: a randomized trial. Med Decis Mak. 2015;35(8):937–47.CrossRefGoogle Scholar
  10. 10.
    Hibbard JH, Greene J, Daniel D. What is quality anyway? Performance reports that clearly communicate to consumers the meaning of quality of care. Med Care Res Rev. 2010;67(3):275–93.CrossRefPubMedGoogle Scholar
  11. 11.
    Peters E, Dieckmann N, Dixon A, Hibbard JH, Mertz CK. Less is more in presenting quality information to consumers. Med Care Res Rev. 2007;64(2):169–90.CrossRefPubMedGoogle Scholar
  12. 12.
    Harrison M, Rigby D, Vass C, Flynn T, Louviere J, Payne K. Risk as an attribute in discrete choice experiments: a systematic review of the literature. Patient Patient Centered Outcomes Res. 2014;7(2):151–70.CrossRefGoogle Scholar
  13. 13.
    Veldwijk J, Lambooij MS, van Til JA, Groothuis-Oudshoorn CGM, Smit HA, de Wit GA. Words or graphics to present a discrete choice experiment: does it matter? Patient Educ Couns. 2015;98(11):1376–84.CrossRefPubMedGoogle Scholar
  14. 14.
    Primary Health Care Advisory Group. Better outcomes for people with chronic and complex health conditions. Final report. Canberra: Commonwealth of Australia; 2015Google Scholar
  15. 15.
    Kenny P, De Abreu Lourenco R, Wong CY, Haas M, Goodall S. Community preferences in general practice: important factors for choosing a general practitioner. Health Expect. 2016;19(1):26–38.CrossRefPubMedGoogle Scholar
  16. 16.
    Australian Bureau of Statistics. Patient experiences in Australia: summary of findings, 2013–14. Canberra: Australian Bureau of Statistics; 2014.Google Scholar
  17. 17.
    England NHS. GP Patient Survey—National summary report. London: Ipsos MORI Social Research Institute; 2015.Google Scholar
  18. 18.
    Street D, Burgess L. The construction of stated choice experiments. Hoboken NJ: John Wiley & Sons Inc; 2007.CrossRefGoogle Scholar
  19. 19.
    Burgess L, Street DJ, Wasi N. Comparing designs for choice experiments: a case study. J Stat Theory Pract. 2011;5(1):25–46.CrossRefGoogle Scholar
  20. 20.
    de Bekker-Grob EW, Donkers B, Jonker MF, Stolk EA. Sample size requirements for discrete-choice experiments in healthcare: a practical guide. Patient Patient Centered Outcomes Res. 2015;8(5):373–84.CrossRefGoogle Scholar
  21. 21.
    McNaughton CD, Cavanaugh KL, Kripalani S, Rothman RL, Wallston KA. Validation of a short, 3-item version of the Subjective Numeracy Scale. Med Decis Mak. 2015;35:932–6.CrossRefGoogle Scholar
  22. 22.
    Fiebig D, Keane M, Louviere JJ, Wasi N. The generalized multinomial logit model: accounting for scale and coefficient heterogeneity. Mark Sci. 2010;29:393–421.CrossRefGoogle Scholar
  23. 23.
    Fiebig DG, Viney R, Haas M, Knox S, Street D, Weisberg E, et al. Complexity and doctor choices when discussing contraceptives. Working Paper 15/14. York: Health, Econometrics and Data Group, University of York; 2015 September 2015.Google Scholar
  24. 24.
    Gu Y, Hole AR, Knox S. Fitting the generalized multinomial logit model in Stata. Stata J. 2013;13(2):382–97.Google Scholar
  25. 25.
    Fagerlin A, Zikmund-Fisher BJ, Ubel PA, Jankovic A, Derry HA, Smith DM. Measuring numeracy without a math test: development of the Subjective Numeracy Scale. Med Decis Mak. 2007;27(5):672–80.CrossRefGoogle Scholar
  26. 26.
    Cheraghi-Sohi S, Hole AR, Mead N, McDonald R, Whalley D, Bower P, et al. What patients want from primary care consultations: a discrete choice experiment to identify patients’ priorities. Ann Fam Med. 2008;6(2):107–15.CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Longo MF, Cohen DR, Hood K, Edwards A, Robling M, Elwyn G, et al. Involving patients in primary care consultations: assessing preferences using discrete choice experiments. Br J Gen Pract. 2006;56(522):35–42.PubMedPubMedCentralGoogle Scholar
  28. 28.
    Philips H, Mahr D, Remmen R, Weverbergh M, De Graeve D, Van Royen P. Predicting the place of out-of-hours care–a market simulation based on discrete choice analysis. Health Policy. 2012;106(3):284–90.CrossRefPubMedGoogle Scholar
  29. 29.
    Scott A, Watson MS, Ross S. Eliciting preferences of the community for out of hours care provided by general practitioners: a stated preference discrete choice experiment. Soc Sci Med. 2003;56:803–14.CrossRefPubMedGoogle Scholar
  30. 30.
    Townsend C, Kahn BE. The “visual preference heuristic”: the influence of visual versus verbal depiction on assortment processing, perceived variety, and choice overload. J Consum Res. 2014;40(5):993–1015.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • Patricia Kenny
    • 1
  • Stephen Goodall
    • 1
  • Deborah J. Street
    • 1
  • Jessica Greene
    • 2
  1. 1.Centre for Health Economics Research and EvaluationUniversity of Technology SydneyUltimoAustralia
  2. 2.Marxe School of Public and International Affairs, Baruch CollegeCity University of New YorkNew YorkUSA

Personalised recommendations