Verbal Probability Expressions in Peri-operative Risk

Shared decision-making is central to the consent process prior to surgery and anaesthesia. Verbal probability expressions are commonly used by clinicians to help describe the level of risk. Common examples of verbal probability expressions are shown below with the estimated numerical risk shown in parentheses:

• High risk (1:100)
• Moderate risk (1:100-1:1000)
• Low risk (1:1000-1:10 000)
• Standard risk (varies depending on patient/procedure etc.)
• Very low risk (1:10 000)
• Minimal risk (1:100 000)
• Negligible risk (1:1 000 000)

Verbal probability expressions are commonly used because they are perceived as being easier to understand than, for example, percentage risk, as this is affected by how numerate a patient is. Clinicians often prefer verbal probability expressions as they avoid assigning an exact percentage of risk; this is because risk prediction is an inexact science and from an individual patient perspective, risk of complications is often a dichotomous outcome - their individual experience will be either a 0% or 100% incidence of complications, depending on whether it happens to them or not. Percentage risk only really applies to large populations, not individual patients.

Shared decision-making is central to the consent process prior to surgery and anaesthesia. With pre-operative clinics, risk indices are often described according to Calman's verbal scale illustrated above (high, moderate, low, very low etc.). However, the actual level of harm that is perceived by the patient and clinician may differ, due a variety of factors, not least a lack of understanding of the underlying numerical concepts. In addition, the level of risk assigned to these by clinicians and the level perceived by patients may differ. For example, a clinician may view a 20% probability of a complication after cancer surgery is high-risk, when compared to their own experience of the procedure; the patient who is living with the disease may see this as a low-risk, given their individual perception of the disease.

This study aims to investigate this and to see if verbal probability expressions are still useful for communication of pre-operative risk. If the study finds large inter-individual variability between patients, then this would suggest that the use of verbal probability expressions in discussions should be reviewed. This may include the need for verbal probability expressions to be used in conjunction with a numerical estimate of risk, or for the terms used (high-risk, low-risk) to be revised. The results of this study may have significant implications at national level in terms of the consent process for surgical procedures.

After gaining consent, a questionnaire with various verbal probability expressions will be completed by clinicians and patients. Each participant will be asked to assign a percentage of likelihood (i.e. a numerical translation) of an adverse outcome according to each verbal probability expression. For example, one patient may perceive the phrase 'high-risk" as an incidence risk in excess of 50%, whilst another may perceive the risk to be 20%.

A researcher will be available to answer any questions will occur during the completion of the questionnaire.

The study is observational.

The numerical translation of different verbal probability expressions will be displayed graphically to illustrate variation (if any). For example, if the phrase 'high-risk" is perceived by patients as a percentage risk ranging from 20-70%, whilst anaesthetists and surgeons perceive 'high-risk' as 10-20%, then this particular verbal probability expression would be of limited value.

We will use ANOVA to analyse if there is any difference in the level risk assigned to different verbal probability expressions by patients and anaesthetists (after testing for normality of data distribution). For example, do patients recognise a meaningful difference between low and minimal risk?

Regression analyses will also be undertaken to determine if any patient factors alter the perception of risk. This will include: sex; calculated Surgical Outcome Risk Tool score; cancer vs. non-cancer surgery; ethnicity; and surgical speciality.