Module 4.6 How can I help my patient make a decision?

Joint clinical decision making must include:

  • Effective communication about the benefits and risks of alternatives.
  • Use of language and concepts that the patient understands and outcomes they care about:
    • Survival
    • Side effects
    • Time away from work or home
    • Hospitalisation
    • Quality of life
  • Contextualising benefits and risks for that patient’s situation.
  • Exploring that patient’s values and preferences about the alternatives and outcomes.

 

Is the language I use to discuss risks and benefits with my patients important?

The language you use to discuss risks and benefits with your patients is important. In study looking at patients with breast cancer, the desire for high-quality, balanced and personalised information was important. It highlights the need for information to be acceptable and understandable to ensure truly informed decisions. Moving towards patient-friendly resources, co-created with patients, to enhance comprehension and support shared decision making is advocated.

Potter, S. Understandable, individualised information about risk is essential to help patients make fully informed decisions about breast cancer treatment: BMJ Oncology. 2025;4:e000762.

 

How can I help patients to make complex and important decisions about their healthcare?

Studying decision aids to help patients make complex and important decisions about their healthcare is an important research field.

Many healthcare decisions are relatively easy. For example:

  • The risks of untreated disease are high.
  • The toxicities of antibiotic treatment are low.
  • The benefits of antibiotic treatment are likely to include reduced mortality, morbidity, time off work, secondary complications of pneumonia.Should a fit 50-year-old have antibiotics to treat community acquired pneumonia?

 

However, there are many examples of situations where either the side effects and inconveniences of treatment are high, the efficacy is low, or the baseline risk of the patient is low. For example:

  • Adjuvant chemotherapy of low-risk early breast cancer
  • Lifelong therapy for mild hypercholesterolemia

 

Decision aids can use simple pictorial representations that display the baseline risk of the patient, and how that risk changes with treatment. Online decision aids can incorporate algorithms to calculate a baseline risk for an individual patient from clinical data.

CVDcheck.org.au calculates cardiovascular risk.

 

10 by 10 grid of icons shows 80 blue heart icons indicating patients who don't experience the negative event, and 20 yellow stethoscope icons indicating patients who experience the event.
Risk before intervention
Heart icon by Peter Lomas from Pixabay
Stethoscope icon by REDQUASAR from Pixabay
10 by 10 grid of icons shows 85 blue heart icons indicating patients who don't experience the negative event, and 15 yellow stethoscope icons indicating patients who experience the event.
Risk after intervention
Heart icon by Peter Lomas from Pixabay
Stethoscope icon by REDQUASAR from Pixabay

 

 

For example, 100 patients may be represented with different colours and icons for the event we are trying to avoid with treatment: blue hearts indicating patients who are well, and yellow stethoscopes indicating patients who experience the negative event.

This example shows a baseline risk of 20% in the patient, which is reduced to 15% after the intervention.

The relative risk reduction is 25%, the absolute risk reduction is 5%, but the pictures are simple to understand even if the concept of percentage is not clear to the patient.

 

How can I access decision aids?

Some decision aids may be available online. Ask a clinician with experience in that area to refer you to commonly used decision aids. Use your understanding of critical appraisal of electronic resources to ensure that the information is valid and applicable. An example includes the free online decision aid The Neoadjuvant Decision Aid which helps clinicians and patients make decisions about the use of adjuvant chemotherapy in early breast cancer.

  • Clinicians input patient and disease factors which allow an algorithm to calculate the patient’s risk of recurrence using published data on the effect of these factors on prognosis.
  • Clinicians and patients can then examine the benefits that a range of different chemotherapy or endocrine therapy options will provide, given that individual’s baseline risk.
  • The output is shown graphically and numerically, similarly to the diagram below, where the light blue bar represents patients who will relapse regardless of treatment, the blue bar represents those who will not relapse, the purple bar represents those who will die of other causes, and the green bar represents those who will avoid a breast cancer relapse if they have chemotherapy.

 

Listen to a highly recommended ABC radio interview with Dr Victor Montori presented on ‘The Health Report’.

Dr Montori, from the Mayo Clinic, Rochester, USA, is an expert in applying evidence-based practice.

Interview with Dr Montori

 

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