WHOSE QUALITY OF LIFE? Exploring Discrepancies Between Health State Evaluations of Patients and the General Public

1. WHOSE QUALITY OF LIFE?Exploring Discrepancies Between Health State Evaluations of Patients and the General Public Peter A. Ubel, M.D. Program for Improving Health Care Decisions Ann Arbor VAMC University of Michigan Health System

2. Acknowledgements • George Loewenstein • Jack Hershey • Jonathan Baron • Christopher Jepson • Norbert Schwarz • Angie Fagerlin • Jason Riis • Dylan Smith • Andrew Siderowf

3. And, of course . . . David Asch

4. “Disability Paradox” • People with disabilities are often much happier than non-disabled people think they would be

5. Lottery Winners Vs. Accident Victims

6. Lottery Winners Vs. Accident Victims • In a famous study, happiness was measured one year after: • winning the lottery

7. Lottery Winners Vs. Accident Victims • In a famous study, happiness was measured one year after: • winning the lottery • developing paraplegia or quadriplegia from an automobile accident Vs.

8. Lottery Winners Vs. Accident Victims • Results: Relatively little difference in quality of life and happiness Vs.

9. Discrepancy Between Patients and Non-patients • Utility of dialysis • patients = 0.56 • non-patients = 0.39 • Utility of having a colostomy • patients = 0.92 • non-patients = 0.80

10. Economic Importance of This “Discrepancy” • Who’s utilities should we include in cost effectiveness analyses?

11. Clinical Importance of this “Discrepancy” • Who’s quality of life should guide clinical decision making?

12. Goals of Talk • Discuss possible factors contributing to discrepancies between health state evaluations of patients and the general public • Show that an answer to the question of “who’s values” to measure depends on source(s) of the discrepancy.

13. From the Outset • Agnostic view of “who’s to blame” for discrepancies • Clearly public mispredicts • how they would answer QoL questions • But that doesn’t mean they mispredict • QoL • Patients might give “faulty” QoL reports

14. From the Outset • I will explore potential sources of discrepancies arising from • patient error • public error • different points of view

15. From the Outset • I will focus on physical disabilities • Where the discrepancy usually takes the following form: • QoL patient > QoL public • I will ignore illnesses/disabilities that have a big affect on mood • e.g. depression, pain, chronic fatigue

16. From the Outset • There is no gold standard for measuring • utility • happiness • QoL • life satisfaction • What’s more, all these concepts are • multifaceted, complex, • viewed differently by different people

17. Potential Source of Discrepancies: Incomplete health state descriptions

18. Incomplete Health State Descriptions • Health state descriptions by definition are incomplete • patients will be able to fill in much of the missing data • but non-patients will not • they might leave the details out • or they might fill it in as best they can, with or without bringing their own biases to bear

19. Global versus Momentary QoL

20. Global versus Momentary QoL • People have difficulty describing average emotions over time • There may be a discrepancy between • moment to moment SWB • general evaluation of SWB

21. No pain, no gain High Pain Pain Low 60 60 90 Time Time

22. Imagine a Dialysis Patient’s Quality of Life • How happy are you right now (0 - 10)? • 6 • 5 • 5 • 6 • 8 • How happy do you feel generally? • 7

23. Are Dialysis Patients as happy as they say? • Collected momentary and global health ratings from dialysis patients • Dialysis patients often experience hour to hour shifting of energy levels • How well do they sum up these experiences?

25. Subjects Patients • 6 dialysis centers. All 203 patients asked to participate • 116 couldn’t or wouldn’t • 63 participated (35%) Controls • Newspaper ads • Screened for major health conditions • 35 participated

26. 1 Excellent 2 Very Good 3 Good 4 Fair 5 Poor Self Reported Health In general, would you say your health is: CONTROLS … 2.3 PATIENTS … 3.7

27. Three stages of data collection • Entry Interview • Palm-pilot data • Exit Interview

28. +2 Very pleasant +1 Slightly pleasant 0 Neutral -1 Slightly unpleasant -2 Very unpleasant 100 Entry: Percentage of time, during a typical week, that you are in each of the following moods?

29. Palm Week • Carried Palms for 1 week • Palms beeped ~8 times per day • The Palm could be put to sleep

30. Palm Week

31. Predicted Mood Patients .78 Controls .61 Predicted Moods

32. Actual Mood Patients .78 .66 Controls .61 .80 Predicted vs. Actual Mood Predicted Mood p = .19

33. 4 positive measures 5 negative measures Patients 3.21 1.00 Controls 3.23 .99 Specific Moods (0-6 scale)- Palm Data -

34. Selection Effect? The 116 non-participating patients were asked for their average mood. M = .74 56% were +2 or +1 9% were –2 or –1

35. Actual Mood Typical Mood DialysisMood Patients .66 .63 Controls .80 .64 Dialysis

36. Actual Mood Typical Mood DialysisMood Patients .66 .63 .47 p = .072 Controls .80 .64 Dialysis

37. Actual Mood Typical Mood DialysisMood Patients .66 .63 .47 Controls .80 .64 -.17 p < .001 Dialysis

38. Actual Mood Typical Mood DialysisMood Patients .66 .63 .47 Controls .80 .64 -.17 p < .001 Dialysis

39. Actual Mood Typical Mood Dialysis Mood Healthy Mood Patients .66 .63 .47 1.10 p < .001 Controls .80 .64 -.17 Healthy (Never had kidney problems …)

40. Actual Mood Typical Mood Dialysis Mood Healthy Mood Patients .66 .63 .47 1.10 Controls .80 .64 -.17 p = .028 Healthy (Never had kidney problems …)

41. Conclusions • Dialysis patients show hedonic adaptation. • Healthy people do not anticipate this adaptation and this can explain at least part of the discrepancy. • Patients themselves do not seem to appreciate the extent to which they have adapted.

42. Who Wants to Know?

43. Who wants to Know? • Imagine a person with PKS disease receiving the following phone call • “We are calling people with Parkinson’s Disease to find out about their quality of life. . .” • How does the conversational context influence responses? • “I know that he knows that I have Parkinson’s . . .”

44. Who wants to know? • Conversational context likely to push in two directions • QOL up: “Given that I have Parkinsons, I am doing rather well . . .” • QOL down by priming effect: “How happy am I? . . . Well now that you have reminded me about my Parkinsons . . .”

45. Who wants to know Study Design • Call PKS patients cared for at UPENN • half given intro like above • half given other intro: “We are calling people in the Northeastern portion of the United States . . .”

46. Who wants to know Study Design • Ask them the following questions • Life satisfaction • Health Satisfaction • Why in that order? • Let me take a quick detour

47. Is there more to life than love? • Q1: How satisfied are you with your love life? • Q2: How satisfied are you with your life overall • correlation 0.7 • Ask the second question before the first • correlation -0.1

48. Who wants to know results • No difference in life satisfaction between two groups • both groups had high satisfaction • Big change in how important health appeared to be in determining people’s overall satisfaction • Parkinson group - life satisfaction explained 50% by health satisfaction • Northeastern USA group: life satisfaction explained < 10% by health satisfaction

49. Focusing Illusion

50. Focusing Illusion • What do people think about when they imagine paraplegia? • being in a wheel chair • activities affected by paraplegia • What will they probably not consider? • activities unaffected by paraplegia • watching T.V. • enjoying a good conversation • savoring a tasty meal …