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Presentation on theme: "COMMUNICATING RISK."— Presentation transcript:



3 NEWSFLASH!! Breaking News…..Mrs Dumpty sues GP for failing to explain adequately risks of sitting on walls…

4 ! “Mr Smith, your serum potassium is at the upper limit of normal.”
“What does that mean?” “Nothing really, you shouldn’t worry.” “Well, why did you tell me?” “I thought you wanted to be kept informed.”

5 Defining Risk : Richard Smith, BMJ
A risk is a combination of a probability of something happening (where statisticians might be able to help you but often can’t), a feeling of the dreadfulness of that event (which is very personal), and a context for the event.

6 Estimate in terms of probability the following “risks”:
Unlikely A chance Occasionally Rarely Probably Usually

7 Successful risk communication depends on establishing a relationship of mutual respect and trust between those concerned The professional values of competence, expertise, empathy, honesty and commitment are all relevant to communicating risk: getting the facts right and conveying them in an understandable way are not enough. Adrian Edwards BMJ 2003;327:693

8 Risk Assessment Clarity Context Uncertainty
Woloshin et al BMJ 2003;327:696-7

9 Elements of risk and selected sources Clarity about the risk
What risk is being discussed? What are the numbers? What is the time period? How dangerous is the disease? Sources: Getting and dying from most cancers at specified times (National Cancer Institute's surveillance, epidemiology and end results website, Getting breast cancer in the next 5 years (National Cancer Institute's breast cancer risk assessment tool, Myocardial infarction or cardiac death in next 10 years (National Cholesterol Education Program heart risk calculator, = prof) Getting lung cancer in the next 10 years (long term smokers) (Memorial Sloan Kettering Cancer Center lung cancer risk assessment tool, Get context How does my risk compare to risk of an average person? similar disease? leading causes of death? all-cause mortality? Dying from various and all causes in the next 10 years (risk charts Acknowledge uncertainty Has the risk factor been shown to change risk (is it really a risk factor)? Does the risk factor really cause disease? How precise is the risk estimate? No single data source See BMJ 's BestTreatments website: How to use research to support your treatment decisions6 Source: Steven Woloshin et al BMJ 2003;327:696

10 Bowel symptoms 71 year old woman, rectal bleeding, loose stool >6 weeks. 58 year old man change in bowel habit, no rectal bleeding, >6weeks. 39 year old man, single episode rectal bleeding, worried re bowel Ca. What do you do? How do you explain? What words do you use?

11 What factors influence how we present risk to patients?
What we know (is our knowledge sufficient and accurate?) Communication skills Engaging patient (discovering their beliefs etc) What outcome we want??

12 “Parents seem to neglect the most obvious risks to their children (such as road crashes), reject expert assessment (as over BSE), and amplify a virtually non-existent risk (autism from vaccination).” BMJ 2003;327:727


14 Editor's choice Think harm always How do you deal with something unpleasant? The commonest way is not to think about it. That, I suspect, is why medicine has paid so little attention to the harm it may cause—despite the ancient instruction "first, do no harm." Many people try to deal with death by not thinking about it, but Montaigne advises us to do the opposite and think about it all the time. The same advice might apply to thinking about harm: every intervention by a doctor, even a throwaway comment or a test "just to be sure," carries the potential for harm, whereas many of those interventions have no possibility of bringing benefit. This long overdue theme issue explores some of the many ways in which health care might result in harm. Very few people attend a doctor thinking that they may come out worse than when they went in. But many do. When referring a patient to hospital should a doctor say: "I must warn you that the simple fact of being admitted to hospital means that you have something above a one in 10 chance of suffering an adverse event and a one in a 100 chance of dying"? I put this point to the Helsinki meeting of the World Medical Association, a body that has made its name (and possibly created harm) by promoting informed consent. The audience looked quizzical, and I've never heard of a doctor issuing such a warning. But doctors will regularly warn patients of much less common risks attached to particular interventions. Imagine an applicant to medical school answering the universal question of "Why do you want to study medicine?" with "My main ambition is to try to do less harm than good" or "I'd like to devote myself to exploring the harms caused by doctors." The applicant would be thought very odd even though he or she would be enlarging on "first, do no harm." Yet the balance between doing good and creating harm in a lifelong medical career undertaken with commitment and compassion may be fine. The harm is omnipresent, the benefit sometimes fleeting. As a junior doctor I dutifully prescribed lignocaine to many patients who had had heart attacks. The logic was, I believe, that the drug would prevent the arrhythmias that might kill patients. It never occurred to me that this might kill patients rather than save them, but I learnt years later that the result of my hard work was more not fewer deaths. As my parents took me to hospital as a 7 year old and left me alone (on the hospital's instructions) to have my tonsils removed they never for an instant thought that the harm of the procedure might outweigh the benefit—but it probably did. The hospital admission certainly made me miserable and caused me to miss my big break playing the Archangel Gabriel. Hard and uncomfortable as it may be, we need to think about harm all the time. Richard Smith, editor

15 Balancing benefits and harms in health care
Letter Balancing benefits and harms in health care Editor's choice was sensationalist but not true EDITOR—I have for a long time thought that one of the chief obstacles to the public's understanding of medicine is the inability of the average punter to understand the concepts of probability and risk-benefit analysis that underpin most of the treatment decisions we make, and our failure as a profession to dispel that ignorance. It was disappointing to read Smith's Editor's choice, in which he bemoans the fact that doctors seldom say to their patients: "I must warn you that the simple fact of being admitted to hospital means that you have... a one in a 100 chance of dying."1 We don't say it because it's not true. It may well be the case that 1% of patients admitted to hospital die, but very few patients enter hospital with a one in 100 chance of dying—for most, it's much less than that. Would Smith have us tell a young, fit patient admitted for a hernia repair that there is one chance in 100 that he or she won't come out alive? If not, which patient would he choose as the recipient of this alarming message? The patient in a road crash with multiple fractures and an aortic laceration perhaps? But in that case, of course, 1:100 would be a significant underestimate of his or her chance of dying. This is not just statistical semantics; for individual patients the 1% death rate is a complete irrelevance, and suggesting that this figure is something that they need to worry about is grossly misleading. Such a figure may make for a headline grabbing editorial (and making a splash in the tabloids seems to have overtaken the impact factor as a measure of success for the BMJ), but it is not science. Bob Bury, consultant radiologist

16 Hormones and Cancer – up to date information
Dear Patient The media continually report a threatening increase in cancer in connection with the use of HRT during menopause. In what follows we give you an up to date review of the proven facts so that you have an objective basis for making a decision. Breast cancer: HRT may be associated with a minimal increase in the incidence of breast cancer. Usually about 60 out of 1000 women develop breast cancer in a lifetime; after 10 years of treatment with HRT, 6 more women develop breast cancer. That is, the risk may possibly increase by 0.6% (6 in 1000) Other cancers: Not only does HRT not increase colorectal cancer, which is relatively frequent, but it has been proven to protect women against colorectal cancer by up to more than 50 per cent. That is, women who receive HRT develop colorectal cancer only half as often.

17 Risks Unnecessary worry and fear of cancer Physical harm from investigations: Colonoscopy 1: deaths and 1:1000 perforations Barium enema 1: deaths

18 HOW CAN WE DO IT? “Effective Options” “Preference Sensitive Options”
Where evidence is clear-cut, e.g. with smoking cessation Issues relate to implementation. “Preference Sensitive Options” Where balance between risk and benefit less clear Need to help patient balance risks and come to a personal decision

19 Numerical representations
Single Event Probabilities Conditional Probabilities Relative Risk

20 Conditional probabilities
The probability that a woman has breast cancer is 0.8%. If she has breast cancer, the probability that a mammogram will show a positive result is 90%. If a woman does not have breast cancer the probability of a positive result is 7%. Take, for example, a woman who has a positive result. What is the probability that she actually has breast cancer?

21 Natural frequencies Eight out of every 1000 women have breast cancer. Of these eight women with breast cancer seven will have a positive result on mammography. Of the 992 women who do not have breast cancer some 70 will still have a positive mammogram. Take, for example, a sample of women who have positive mammograms. How many of these women actually have breast cancer?


23 Strategies / Aids “Most patients assessment of risk is primarily determined not by facts but by emotions.” Start by reminding patients that all treatments have some risk of possible harm.

24 Visual Aids Paling Perspective Scale Paling Palette
Revised Paling Perspective Scale

25 Analogies Driving to hospital GM vs Mobiles Diabetic leaving the house
Car crashes

26 Conclusions

27 Remember you cannot predict the future, so don’t pretend you can!
Finally……. Remember you cannot predict the future, so don’t pretend you can!



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