Communicating Risk Lecture for Week 4 of Endocrine Systems module Peter Washer Lecturer in Communication Skills Academic Centre for Medical Education [email protected]

Communicating Risk

Lecture for Week 4 of Endocrine Systems module

Peter Washer

Lecturer in Communication Skills

Academic Centre for Medical Education

[email protected]

Aim

This lecture introduces the issues of risk communication. It examines different ways of communicating risk and their relative effectiveness in changing attitudes and behavior and will raise questions around the ethics of risk communication.

Learning Objectives

By the end of this lecture and SGW session that follows you should be able to:

• Describe different models of risk• Have an awareness of the ethical dimension of risk

communication• Be able to describe the relative effectiveness of different

methods of communicating risk

Risk is…

Noun:a. Hazard, danger; exposure to mischance or peril.b. Freq. in phrase to run a or the (also one's) risk.

Verb1. trans. To hazard, endanger; to expose to the chance of

injury or loss.2. To venture upon, take the chances of.

Or……“the chances that a hazard will give rise to harm”

What are we trying to achieve in communicating risk?

• At a population level – messages which aim to reduce risk and improve the population’s health

• At individual level - inform people about risks, enabling them to make their own choices

What are we trying to achieve in communicating risk?

Are we trying to simply reduce risk and improve the population’s health? Or are we trying to inform people, enabling them to make their own choices, regardless of whether this reduces risk?

Shared decision making: a middle ground between the ‘doctor / nurse / midwife knows best’ approach and rampant health consumerism

Ethics of communicating risk

• Doctors can manipulate patients (and populations) by framing a risk positively or negatively

• Even if doctors have explained risks to patients clearly, the patient’s attitudes and perception of that risk will differ

• Uncertainty changes – e.g. the risks associated with taking hormone replacement therapy

So we need to…

• Take account of the patient’s attitudes and perception of the risk

• Respect patient autonomy i.e. their right to make an informed choice

• ‘Do no harm’ – beware manipulating patients by framing a risk positively or negatively

What GMC says about information patients may want or ought to know, before consent:

• details of the diagnosis / prognosis & likely prognosis if the condition is left untreated;

• uncertainties about the diagnosis • options for treatment (or non-treatment) or management

of the condition• the purpose of a proposed investigation or treatment

including common & serious side effects; • explanations of the likely benefits & the probabilities of

success; & discussion of any serious or frequently occurring risks

Patient Charter

‘You have the right to have any proposed treatment, including the risks involved in that

treatment and any alternatives, clearly explained to you before you decide what to do’

Models of risk

There is a large social-scientific literature on the topic of risk, with different models of risk:

• The Realist Model• The Social Constructionist Model

Models of risk: Realist Model

Where risk is seen as an objective hazard, threat or danger that exists 'out there' and can be measured independently of social or cultural forces.

In the techno-scientific literature, there is often a thinly disguised contempt for lay people's unscientific, 'correct' knowledge about risk. The calculations the 'expert' provides about risk tend to be treated as if they were value-free, unbiased 'objective' facts.

Models of risk: Risk as a social construction

Social constructionists argue:

• ideas about risk are constructed both through individual experience and by the mass media, as well as by experts.

• why are some risks are highlighted and politicised more than others?

• risk provides a rational, scientific, calculable explanation for misfortune (illness, accidents etc)

• the concept of risk is used politically to attribute blame for danger threatening a particular social group.

Giving information about risks

• What information?

• How should it be presented?

• Conducting the consultation





Giving information

• How much does the patient know?• How much information do they want?• Present information appropriately• Explore patient’s views on information• Share decision making• Check understanding





Ways of representing numbers

• Positive or negative framing

• Single event probabilities

• Conditional probabilities

• Relative risks





• Relative risks

Numerical representations

Positive or negative framing:

• There is a 5% chance of this surgery being fatal • There is a 95% chance of surviving this surgery

Remember all treatments inevitably carry some degree of risk. Also there are always at least two options (one being non-treatment). There is no such thing as risk free medicine.





• Relative risks

Single event probabilities

Doctor says:“There is a 30% chance of developing impotence

with this drug”

• Patient might understand 30% of people taking the drug become impotent

or• In 30% of my sexual encounters I may be impotent

How might we re-phrase the doctor’s statement to avoid this confusion?





• Relative risks

Conditional Probabilities

Many diseases, e.g. cancers, have screening programmes where individuals at risk are encouraged to be tested to see if they have the early stages of the disease.

The chance of a particular screening test (mammograms, prostate specific antigen [PSA] etc) actually detecting the disease is known as the sensitivity of the test.

This is typically communicated as a conditional probability.

Conditional Probabilities

A patient has a positive mammogram. Her doctor has the following data:

“The probability that a woman has breast cancer is 0.8%. If she does have 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%. ”

What is the probability that she actually has breast cancer? (In other words, what is the positive predictive value, the PPV, of the test?)

Translating Conditional Probabilities into Natural frequencies

Translate the information on the previous slide into natural frequencies:

“ [ ] out of every 1000 women have breast cancer. Of these [ ], [ ] will have a positive result on mammography. Of the [ ] who do not have breast cancer some [ ] will still have positive mammograms.”

Again take for example the woman who has a positive result. What is the probability that she actually has breast cancer?

Using natural frequencies

• 8 out of every 1000 women have breast cancer• Of these 8 , 7 will have a positive result on

mammography. • Of the 992 who do not have breast cancer some 64.9 will

still have positive mammograms.”





• Relative risks

Relative risk reduction

How would you interpret the following statement?

“Mammography screening reduces a woman’s risk of dying from breast cancer by 25%”.



Treatment Deaths per 1,000 women

No mammography screening 4

Mammography screening 3



But this 25% figure represents an absolute risk reduction of only 1 in 1000 or 0.1 % because:– Of 1000 women who do not undergo mammography,

about 4 will die from breast cancer in 10 years– Whereas out of those who do undergo

mammography, about 3 in 1000 die

Relative Risks Exercise 1: Mr X is a patient who has high cholesterol. He has read an

article in the newspaper that says that “People with high cholesterol can reduce their risk of death by 22 per cent by taking a cholesterol reducing drug”.

His GP has the following information table from the clinical trials of the drug.

Treatment Deaths per 1000 people with high cholesterol over 5 years

Cholesterol reducing drug 32

Placebo 41

Try and answer the following yourselves:

What does “reduce their risk of death by 22%” mean?

What is the absolute risk reduction (as a %)? What is the number of people who would need to treated to

save one life?

How might his GP put this information into natural frequencies?

Answers:

“Reduce their risk of death by 22%” means the mortality reduction was from 41 to 32 in every 1000 (9/41 = 22%)

The absolute risk reduction is 9 in 1000 or 0.9%

The number of people who would need to treated to save one life is 111 (roughly 9 in 1000 deaths are prevented using the drug)

Translating data into information

How might his GP put this information into natural frequencies?...

“If you imagine 1000 people with high cholesterol like yourself. Without any medication, you would expect 41 of them to die from related causes like a heart attack over a five year period. However, if these 1000 people were taking a cholesterol lowering drug for the five year period, then only 32 of them would be expected to die from related causes.”

Relative Risk Exercise 2: change into natural frequencies

The standard test for colorectal cancer is the faecal occult blood test (FOTB). For symptom-free people over 50 screened using this test, the probability that one of these people has colorectal cancer is 0.3%. If they do have cancer, there is a 50% probability that they will have a positive FOTB. If they don’t, the probability of a positive test is 3%. Imagine a person over 50 with no symptoms who has a positive test. What is the probability that they have cancer?

Exercise 2: Natural frequencies format

[ ] out of every [ ] people have colorectal cancer. Of these [ ] people with colorectal cancer, [ ] will have a positive FOTB test result. Of the remaining [ ] people without cancer, [ ] will still have a positive FOTB. So of [ ] people who have a positive test, only [ ] have cancer, which is a probability of [ ]% or 1 in [ ].

[ ] people

[ ] colorectal cancer [ ] no colorectal cancer

[ ] positive [ ] negative [ ] positive [ ] negative

Exercise 2: Natural frequencies format

Thirty out of every 10,000 people have colorectal cancer. Of these 30 people with colorectal cancer, 15 will have a positive FOTB test result. Of the remaining 9,970 people without cancer, 300 will still have a positive FOTB. So of 315 people who have a positive test, only 15 have cancer, which is a probability of 4.8% or 1 in 20.

10,000 people

30 colorectal cancer 9,970 no colorectal cancer

15 positive 15 negative 300 positive 9670 negative





Conducting the consultation:

• Avoid using descriptive terms only (e.g. ‘low risk’) • Offer both positive and negative outcomes • Use absolute numbers or actual numbers wherever

possible, rather than relative risks• Use natural frequency format rather than percentages

i.e. one in 5 people rather than 20%• Use consistent denominators e.g 40 out of 1000 versus

5 out of 1000 rather than1 in 25 and 1 in 200. • Use visual aids where available (e.g. pie charts)

Some general rules:

• Patients should be able to trust the information they are being given

• Show a competent and caring approach, • Explore the significance of the risk to the

individual. • Be honest and acknowledge and share your

uncertainty

Learning Objectives

By the end of this lecture and SGW session that follows you should be able to:

• Describe different models of risk• Have an awareness of the ethical dimension of risk

communication• Be able to describe the relative effectiveness of different

methods of communicating risk

References and Further reading:

Key reading:Gigerenzer and Edwards (2003) Simple tools for understanding risks.

British Medical Journal 327 (7417) p741-744

Further reading:Gigerenzer G (2002) Reckoning with Risk. London, Penguin.

(Recommended but only one copy in library)The British Medical Journal 327 (7417) at

http://bmj.bmjjournals.com/content/vol327/issue7417/ Berry, D. (2004). Risk, communication and health psychology.

Maidenhead: Open University Press.Department of Health Risk Research Web pages:

http://www.dh.gov.uk/PolicyAndGuidance/HealthAndSocialCareTopics/RiskResearch/

HIV information taken from: http://www.thebody.com/Forums/AIDS/SafeSex/Archive/PreventionSexual/Q93372.html

http://bmj.bmjjournals.com/content/vol327/issue7417/



http://www.thebody.com/Forums/AIDS/SafeSex/Archive/PreventionSexual/Q93372.html

http://www.thebody.com/Forums/AIDS/SafeSex/Archive/PreventionSexual/Q93372.html

Documents

Communicating Risk Lecture for Week 4 of Endocrine Systems module Peter Washer Lecturer in Communication Skills Academic Centre for Medical Education [email protected]