Plain Numbers. Presenting numbers in ways that engage your members and patients. October 2015

Transcription

1 Plain Numbers Presenting numbers in ways that engage your members and patients October 2015

2 Who We Are Katy Magee Director of Editorial Strategy Karen Baker Vice President, Mission Initiatives Chad Parmet Medical Content Specialist

3 Agenda o Health literacy and numeracy overview o Plain numbers at Healthwise o Presenting numerical data Best practices Thorny issues o Resources

4 What Is Health Literacy? the degree to which an individual has the capacity to obtain, process, communicate, and understand basic health information and services to make appropriate health decisions. --Affordable Care Act, 2010

5 Health Literacy Matters a stronger predictor of an individual s health status than age, income, employment status, education level and race. 1. Berkman et al. Ann Intern Med

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7 What Is Health Numeracy? New drug reduces heart attack risk by 33% Mortality rate is 3 in 1,000 in 5 years Symptom relief is 2.5 times more likely with therapy You have to treat 150 people to benefit 1 person Test has a 5% risk of complications some, most, a few, many, a lot, nearly all, rarely, frequently, sometimes, often

8 Conveying Risk and Benefit: A Mission-Critical Venture

9 Uses of Risk and Benefit Data o Marketing/advertising Build interest, sell o Public health campaigns Persuade, motivate o Shared decision making Inform, support

10 The Challenge

11 A Teaching Challenge o Complex numbers about complex subjects o Data squishiness and uncertainty o Lots of qualifiers o Quality-of-evidence issues

12 An Engagement Challenge

13 An Engagement Challenge (or possibly Leonard H. Courtney)

14 An Engagement Challenge

15 Why Now? o Momentum in shared decision making o Evolving role of patient o Numeracy challenge o Mission-critical o No obvious path to follow

16 Past Learnings = New Directions

17 Lessons From Plain Language o Use familiar words. o Teach important medical terms. o Use clear, simple visuals. o Focus on the need-to-know. o What does this mean to me?

18 The Plain Numbers Project Evidence quality Charts, graphs, icon arrays Positive and negative framing Denominators Data inconsistency Rare, common, many, most, few Cognitive overload

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20 5 Tips for Plain Numbers in Shared Decision Making

21 Risk Communication Team Collie Nelson Senior Research Associate Marianne Flagg Medical Writer Steve Graepel Senior Art Director Terrina Coffer Associate Editor And building on the work of Julie Beauregard, Katy Magee, Suzanne Brodney, Carrie Levin, Casey Godbout, Claire Anderson, Morgan MacCuaig!

22 Overview o What is a plain number? o 5 tips o Unsolved mysteries

23 What Is a Plain Number? 1. Clear 2. Helpful

24 What Is a Plain Number? 3. Balanced

25 Why Bother? People taking statins commonly report muscle aches. = about 10% Estimate = 2. Joy et al, Ann Int Med 2009

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27 5 Tips 1. Use outcomes that matter 2. Give both sides of risk/benefit 3. Say when 4. Compare apples to apples 5. Use absolute numbers

28 1. Use Outcomes That Matter to Patients o Stomach pain o Sore throat o Knee pain o Heart attack o Death

29 Example Taking this drug raises your liver enzymes by 20%. Taking this drug raises your chance of liver disease from 2/100 to 17/100. or If you take this drug, you ll need monthly blood tests. Fictional data

30 2. Give Both Sides of a Risk/Benefit Out of 100 people who have this surgery: o 7 people have a complication. o 93 people do not have a complication. Recommendation = 3. IPDAS Checklist Epstein et al JAMA, Spiegelhalter et al Science 2011.

31 Example Graphic Healthwise, Incorporated

32 Example Graphic Healthwise, Incorporated

33 3. Say When Two years after knee replacement: o About 80 in 100 people have major pain relief. o About 20 in 100 people say they still have pain. Data = 6. Beswick et al 2012 Recommendation = 3. IPDAS Checklist Fagerlin et al 2011.

34 4. Compare Apples to Apples Aim to use the same: o Outcome o Time period o Denominator 3. IPDAS 2005; 8. Zipkin et al 2014; 9. Trevena et al 2013; 10. McCaffery et al 2012; 11. FDA 2011; 12. Woloshin et al 2011; 13. Garcia-Retamero et al 2010

35 Example Physical therapy 40 out of 100 people have less pain 1 year later. Aspirin 3 out of 10 people have more function. Fictional data

36 Which Risk Is Less Common? 4 in 10,000 risk of muscle problems 1 in 100 risk of liver problems 60% said this is less common (wrong) 12. Woloshin et al, Ann Int Med 2011.

37 5. Use Absolute Numbers Article: Recommendation: 7. Fagerlin et al 2011; 8. Zipkin et al 2014; 14. Akl et al 2011; 15. Visschers et al 2009.

38 Example For men ages followed for 13 years o The PSA test reduces your risk of dying from prostate cancer by 17%. 16. Schröder et al, Lancet 2014.

39 Chances of Dying of Prostate Cancer Without PSA testing With PSA testing about 6 out of 1000 men about 5 out of 1000 men Absolute difference o 1 out of 1000 saved from dying of PCa o 999 out of 1000 didn t benefit 16. Schröder et al, Lancet 2014.

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41 40% Off of What? or = 2 cents off = $30,000 off

42 * That means in a large clinical study, 3% of patients taking a sugar pill or placebo had a heart attack compared to 2% of patients taking Lipitor.

43 5 Tips 1. Use outcomes that matter 2. Give both sides of risk/benefit 3. Say when 4. Compare apples to apples 5. Use absolute numbers

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45 Examples of Mysteries o Number overload? o Use words. But how? o Graphics? o Apples & oranges? o Quality-of-evidence issues?

46 How to Present a Small Chance? o 0.5% or 0.5/100? o Decimals? 0.5% risk o 5/1000? o Big denominator amplifies small chances o Less than 1/100? o What if 5/1000 vs 6/1000? o Don t mention it? o What if it s death? o Where s the line?

47 Graphics for Small Chances Dr. Andrew Lazris s work as shown in:

48 Comparing Small Chances

49 Comparing Small Chances

50 Evolving Through User Testing Graphics Healthwise, Incorporated

51 What ideas do you have to solve these mysteries?

52 Wrap-Up

53 Plain Numbers Begin at Home ^ PLAIN

54 Great Resources Visualizing Health gallery of data graphics (UMichigan) Icon array generator (UMichigan) Healthnewsreview.org Zipkin et al 2014: Evidence-based risk comm. Peters et al 2014: Numeracy and the ACA Trevena et al 2012: Presenting probabilities Fagerlin et al 2011: 10 steps to better risk comm. IPDAS: International patient decision aid standards

55 Some Experts o Angie Fagerlin o Brian Zikmund-Fisher o David Spiegelhalter o Edward Tufte o Ellen Peters o Gerd Gigerenzer o Holly Witteman o Jessica Ancker o Lisa Schwartz & Steve Woloshin o Mirta Galesic o Peter Ubel...and more

56 References 1. Berkman ND et al (2011). Low health literacy and health outcomes: an updated systematic review. Ann Intern Med, 155(2): Joy T, et al. (2009). Narrative review: Statin-related myopathy. Ann Intern Med, 150(12): IPDAS-Checklist (2005). IPDAS 2005: Criteria for Judging the Quality of Patient Decision Aids. Available at: Accessed October 27, Epstein RM et al (2004). Communicating evidence for participatory decision making. JAMA, 291(19): Spiegelhalter DM et al (2011). Visualizing uncertainty about the future. Science, 333(6048): Beswick AD et al (2012). What proportion of patients report long-term pain after total hip or knee replacement for osteoarthritis? A systematic review of prospective studies in unselected patients. BMJ Open 2(1): e Fagerlin A et al (2011). Helping patients decide: ten steps to better risk communication. J Natl Cancer Inst, 103(19): Zipkin DA et al (2014). Evidence-based risk communication: a systematic review. Ann Intern Med, 161(4): Trevena LJ et al (2013). Presenting quantitative information about decision outcomes: a risk communication primer for patient decision aid developers. BMC Med Inform Decis Mak, 13 Suppl 2:S McCaffery K et al (2012). Addressing Health Literacy. In Volk R et al 2012 Update of the International Patient Decision Aids Standards (IPDAS) Collaboration s Background Document. Chapter J. Available at: Accessed October 27, FDA (2011). Communicating risks and benefits: an evidence-based user's guide. Available at: Accessed October 27, Woloshin et al (2011), Communicating data about the benefits and harms of treatment: a randomized trial. Ann Intern Med, 155(2): Garcia-Retamero R et al (2010). How to reduce the effect of framing on messages about health. J Gen Intern Med, 25(12): Akl EA et al (2011). Using alternative statistical formats for presenting risks and risk reductions. Cochrane Database Syst Rev, 3:CD Visschers VH et al (2009). Probability information in risk communication: a review of the research literature. Risk Anal, 29(2): Schröder FH, et al. (2014). Screening and prostate-cancer mortality: Results of the European Randomised Study of Screening for Prostate Cancer (ERSPC) at 13 years of follow-up. Lancet, 384(9959):