The concept of health risk is difficult for the public to understand. A patient’s perception of risk arises from the way risks are communicated to them, the rapport they have with their doctor and what they bring to the conversation: personal values, previous experience, family history and cultural norms.¹ Such perceptions affect not only the extent to which a treatment will be acceptable to a patient, but also their level of dissatisfaction if complication occurs. This article deals with influences on decision-making from the way we frame risk and benefit in our discussions with patients about treatments and procedures.

This issue is heightened in today’s health environment where advances in technology make more advanced and complex treatments possible. Discussion about risk carries more importance in situations that are elective (where the status quo is an option); where there are multiple treatment options, especially in the absence of medical consensus; or where there is high potential for an adverse outcome. In such situations, how we discuss risk is perhaps the most important component of the consenting process. Data uncertainty is one of the challenges in risk communication.²

Uncoupling risk and benefit

Many of our patients may see risk and benefit as inversely proportional, if risk is low then benefit must be high, and vice versa. As perceived risk increases, perceived benefit may decrease. Metaphorically, they see risk and benefit as a ‘seesaw’. This can set up unrealistic expectations of benefit on one hand or underestimating potential for benefit on the other. In reality, risk and benefit are more akin to two lifts that can move up or down with a degree of independence from each other.

We need to uncouple risk and benefit in consenting conversations with our patients. This can be done by discussing the potential benefits of a treatment, determining which benefits a patient attributes value to, and then determining whether those perceived benefits remain valued in light of the risks of that treatment. Whether benefits continue to be valued in light of the risks can be significantly influenced by the way we frame risk.

Framing of risk

The way information is presented can have significant effects on decisions made.³ Where patients considering angioplasty were randomised as to how risk was ‘framed’ and shown a brief video that stated ‘99 per cent of patients undergoing this procedure do not have any major complications’ (positive framing), or alternatively ‘one in 100 people who undergo this procedure suffer a complication’ (negative framing), 52 per cent of the positively framed group stated they would definitely or probably undertake the procedure, falling to 27 per cent of those for negative framing.⁴ To understand this, with the first statement the probability of a good outcome is accented; as if the patient’s unconscious thought is ‘surely I’ll have a good outcome’. In contrast, with the second statement, the focus is on the possibility of an adverse outcome; the subconscious thought being ‘that could be me’. In short, we are shifting the patient’s reference point from a perception of benefit to one of harm.

Furthermore, there is the possibility that how we frame risk can be magnified by the degree to which individual patients may be risk-accepting or risk-avoiding; that is, their inherent risk-framing. A patient who is risk-avoiding by nature is very unlikely to choose a treatment where the risk has been framed negatively. In order to minimise the impact of both practitioner and patient framing of risk, we need to consider providing ‘balanced framing’. As an example, stating ’for this procedure, 99 per cent of people do not have any serious complication; however, one per cent do’ is balanced and with subsequent conversation, it is likely that the degree to which the patient is risk-accepting or avoidant may be revealed. Further discussion can then tease out why the patient has concerns about risk that seem greater than other patients.

Another example of framing is that of ‘loss or gain’ framing, where perceived losses in not acting are revealed in order to motivate a treatment action as well as, or rather than, perceived gains likely to result from that action.⁵ Consistently, loss-framing has been shown to be more effective in increasing uptake of an action than gain-framing.³ Again, being aware of both techniques can be of benefit. For example, where it seems to a doctor that a patient is unexpectedly reluctant to consider a low-risk treatment readily accepted by most patients, exploring why there is reluctance (such as previous experience or cultural norms) and then loss-framing the discussion may increase uptake.

Other techniques to describe risk

It is important to use plain language in description of risk and to take into account how our patients understand those descriptions, by moving our terminology and conversational style toward their own.

Studies have looked at whether using verbal or numerical descriptors of risk can affect decision-making. For example, in a study of the use of European Union risk descriptors, words such as ‘common’ (1–10 per cent frequency) and ‘rare’ (0.01–0.1 per cent frequency) were provided. Use of the verbal rather than numerical descriptor led to overestimation of the chance of harm, with increased wariness of accepting a treatment action than when numerical descriptors were used. Accuracy of immediate recall is also better with numerical descriptors.⁶ Though there are few significant studies on this comparison, suffice it to suggest that verbal descriptors alone are best avoided. A statement incorporating both numerical and verbal descriptors seems best.

Inclusion of visual representation may also improve understanding. Written information is a useful reinforcement of risk realities, as they are for other aspects of consent.⁷ College information pamphlets are excellent examples. Such decision aids may improve accurate risk perception when probabilities are included.⁹ Thus, 1:100 and 1:10 may not seem very dissimilar to those patients with low numeracy skills, whereas ‘one in 100’ and ‘ten in every 100’ will provide an improved understanding of the relative risks.

Presenting more data points in a risk discussion appears to lead to more cautious treatment decisions.¹ Therefore, we need to be careful that we show some judgment as to which risks are more relevant to our patient’s decision-making. Determining the number of data points we present can be based on our professional consensus on one hand and the patient’s value system on the other. If a patient seems too ready to accept a procedure, seemingly without due consideration to risks and benefit, adding data points may introduce some due caution.

Summary

In communicating risk with our patients, ‘multiple complementary formats’ best enable our patients to make a choice that they will continue to believe is right for them.¹⁰ To facilitate this, we need to remember:

• It is essential that we normalise risk for our patients by discussing the risks related to all their options, including the risk for taking no therapeutic action.
• Use both positive and negative framing.
• Loss-framing may be useful.
• Use the same denominator when comparing risks.
• Use simple numerical data, verbal descriptors and visual aids to enhance understanding.

Finally, it is important that the patient receives all the risk and benefit information that satisfies them, and we must also ensure that they understand this information and assess their emotional response.

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7. Stacey D et al, Decision aids for people facing health treatment or screening decisions. JHSO Cochrane Database Syst Rev 2014.

9. It is also apparent that the higher the numerator in a risk ratio, the higher the perceived risk.⁸Knapp P et al, Comparison of two methods of presenting risk information to patients about the side effects of medicines. Qual Safety in Health Care. 2004;13(3):176-80.Lipkus IM, Numeric, verbal and visual formats of conveying health risks: suggested best practices and future recommendations. Med Decision Making. 2007;27(5):696-713.

10. Hux JE, Naylor CD, Communicating the benefits of chronic preventive therapy: does the format of efficacy data determine patient’s acceptance of treatment?, Med Decision Making. 1995;15:152-7.