Contributions of Second Opinions,Outcome Forecasts,and Testimonials to Patient Decisions about Knee Replacement Surgery

Abstract

Background. Decision aids are now a well-established means of supporting patients in their medical decision making. The widespread use of decision aids invites questions about how their components contribute to patient decisions. Objective. The objective of this study was to measure the importance of second opinions, patient-specific outcome forecasts, and patient testimonials relative to patient clinical and socioeconomic factors and the primary physician recommendation on the decision to undergo full knee replacement surgery to treat knee osteoarthritis. Methods. Middle-aged and older members of the RAND American Life Panel (N = 1616) chose whether to recommend surgery as a treatment for each of 3 hypothetical patients (vignettes) presented in a video-enhanced internet survey. Vignettes randomly sampled levels of scenario attributes. Results. Second opinions, person-specific outcome forecasts, and 2 consistent patient testimonials strongly affected respondents’ decision making; a single testimonial, however, did not significantly affect decisions. Conclusions. Information provided in a decision aid, including person-specific outcome forecasts and testimonials, can affect patient choices. The strong effect of testimonials and respondents’ interest in reviewing them reinforces concerns about unwanted influence when testimonials are biased.

Keywords

medical decision making knee replacement surgery stated-choice experiment decision guides person-specific outcome forecasts patient testimonials

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References

International Patient Decision Aids Standards Collaboration (IPDAS). Available from: URL: http://ipdas.ohri.ca/index.html

Bekker

Winterbottom

Fowler

. 2012 Updated chapter E: using personal stories. In: Volk

Llwellyn-Thomas

eds. Update of the International Patient Decision Aids Standards (IPDAS) Collaboration Background Document. Available from: URL: http://ipdas.ohri.ca/IPDAS-Chapter-E.pdf

Winterbottom

Bekker

Conner

Mooney

. Does narrative information bias individual’s decision making? A systematic review. Soc Sci Med. 2008;67:2079–88.

Betsch

Ulshofer

Renkewitz

Betsch

. The influence of narrative v. statistical information on perceiving vaccination risks. Med Decis Making. 2011;31(5):742–53.

Chaiken

Wood

Eagly

. Principles of persuasion. In: Higgins

Kruglanski

, eds. Social Psychology: Handbook of Basic Principles. New York: Guilford Press; 1996:702–42.

March

. A Primer on Decision Making: How Decisions Happen. New York: The Free Press; 1994.

Rossi

Anderson

. The factorial survey approach: an introduction. In Rossi

Nock

, eds. Measuring Social Judgments: The Factorial Survey Approach. Beverly Hills (CA): Sage; 1982.

Louviere

Hensher

Swait

. Stated Choice Methods: Analysis and Application. New York: Cambridge University Press; 2000.

Johnson

Kanninen

Bingham

Ozdemir

. Experimental designs for stated choice studies. In: Kanninen

, ed. Valuing Environmental Amenities Using Stated Choice Studies. Dordrecht (Netherlands): Springer; 2007:159–92.

10.

Caro

McFadden

Gottlieb

Yee

Winter

. Using the internet to administer more realistic vignette experiments. Soc Sci Comput Rev. 2012;30(2):184–201.

11.

Health Dialog. Treatment Choices for Knee Osteoarthritis. Boston (MA): Foundation for Informed Medical Decision Making; 2007.

12.

Gurmankin

Baron

Hershey

Ubel

. The role of physicians recommendations in medical treatment decisions. Med Decis Making. 2002;22(3):262–71.

13.

Moumjid

Gafni

Bremond

Carrere

. Seeking a second opinion: do patients need a second opinion when practice guidelines exist? Health Policy. 2007;80(1):43A–50.

14.

Van Dalen

Groothoff

Stewart

Spreeuwenberg

Groenewegen

van Horn

. Motives for seeking a second opinion in orthopedic surgery. J Health Serv Res Policy. 2001;6(4):195–201.

15.

RAND American Life Panel. Available from: URL: https://mmicdata.rand.org/alp/index.php?page=panel

16.

Chang

Krosnick

. National surveys via RDD telephone interviewing versus the Internet: comparing sample representativeness and response quality. Public Opin Q. 2009;73:641–78.

17.

Yeager

Krosnick

Chang

. Comparing the accuracy of RDD telephone surveys and internet surveys conducted with probability and non-probability samples. Public Opin Q. 2011;75(4):709–47.

18.

The American Association for Public Opinion Research. Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys. 7th edition. AAPOR, Deerfield (IL): AAPOR; 2011.

19.

US Census Bureau American FactFinder. Population 60 years and over in the United States. 2011 American Community Survey 1-year estimates. Available from: URL: http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml

20.

Gallup-Healthways Well-Being Index. Available from: URL: http://www.gallup.com/poll/154169/chronic-pain-rates-shoot-until-americans-reach-late-50s.aspx

21.

Greene

Campo

Banerjee

. Comparing normative, anectotal, and statistical risk evidence to discourage tanning bed use. Commun Q. 2010;58(2):111–32.

22.

McHugh

Luker

. Influences on individuals with osteoarthritis in deciding to undergo a hip or knee joint replacement: a qualitative study. Disabil Rehabil. 2009;31(15):1257–66.

23.

Toye

Barlow

Wright

Lamb

. Personal meanings in the construction of need for total knee replacement surgery. Soc Sci Med. 2006;63(1):43–53.

24.

Hawker

Wright

Badley

Coyte

. Perceptions of, and willingness to consider, total joint arthroplasty in a population-based cohort of individuals with disabling hip and knee arthritis. Arthritis Care Res. 2004;51(4):635–41.

25.

Sampietro-Colom

Espallargues

Rodriguez

. Wide social participation in prioritizing patients on waiting lists for joint replacement: a conjoint analysis. Med Decis Making. 2008;28(4):554–66.

26.

Allepuz

Espallargues

Moharra

Comas

Pons

. Prioritisation of patients on waiting lists for hip and knee arthroplasties and cataract surgery: instruments validation. BMC Health Serv Res. 2008;8:76.

27.

Diamond

Hausman

. Contingent valuation: is some number better than no number? J Econ Perspect. 1994;8(4):45–64.

28.

Hensher

. Hypothetical bias, choice experiments and willingness to pay. Working Paper ITLS-WP-09-01. 2009. p 1–29. Available from: URL: http://sydney.edu.au/business/__data/assets/pdf_file/0009/25479/itls_wp_09_01.pdf.

29.

Mark

Swait

. Using stated preference and revealed preference modeling to evaluate prescribing decisions. Health Econ. 2004;13:563–73.

30.

Harrison

. Hypothetical bias over uncertain outcomes. In: List

, ed. Using Experimental Methods in Environmental and Resource Economics. Northampton (MA): Edward Elgar; 2006. p 41–69.

31.

Kesternich

Heiss

McFadden

Winter

. Suit the action to the word, the word to the action: hypothetical choices and real decisions in Medicare Part D. J Health Econ. 2013;32(6);1313–24.

32.

Baddeley

. Human Memory: Theory and Practice. Needham Heights (MA): Allyn & Bacon; 1990.

33.

Shaffer

Zikmund-Fisher

. All stories are not alike: a purpose-, content-, and valence-based taxonomy of patient narratives in decision aids. Med Decis Making. 2013;33(1):4–13.

34.

Gaissmaier

Anderson

Schulkin

. How do physicians provide statistical information about antidepressants to hypothetical patients? Med Decis Making. 2014;34(2):206–15.

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