SUPPORTING PEOPLE WITH CANCER TO MAKE BETTER TREATMENT DECISIONS
When someone is diagnosed with cancer, they are often faced with difficult choices. Chances of survival may differ by treatment option. And treatment options may also bring side effects that affect daily life, wellbeing, and independence. Making sense of treatment options can be overwhelming for patients, their families and their care teams. Moreover, the complexity of patients’ care paths makes it difficult for all involved to oversee all the steps, the healthcare providers who are involved, and the decisions that need to be made.
DECISION-SUPPORT TOOLS may help. These tools are designed to give patients clear and personalized information. Their aim is to support patients in better understanding the treatment options and in taking an active role in deciding about their treatment. Used well, such tools can support personalized care, improve health outcomes and can make healthcare more fair and inclusive. However, many tools fail short. They often focus only on survival and pay little attention to, for instance, quality of life. Decision-support tools are not yet widely used in everyday clinical care.
WHAT IS 4D PICTURE?
The core of the 4D PICTURE project is a new way of looking at cancer care: not just as a medical process, but as a lived experience. The 4D PICTURE PROJECT aims to do this by improving the use of decision-support tools. Its main goal is to redesign cancer care pathways and to integrate advanced, evidence-based decision-support tools directly into clinical practice.
By combining datasets of vast numbers of patient stories of their experiences, large clinical data sets, and innovative design methods, 4D PICTURE seeks to support patients and healthcare professionals in making better-informed decisions together.
To do this, the project further develops a promising service-design approach called MetroMapping (
https://metromapping.org/en/(s’ouvre dans une nouvelle fenêtre))
RETHINKING CANCER CARE WITH METROMAPPING
MetroMapping is a visual and human-centered method for understanding and improving care pathways. Inspired by metro maps, it shows the entire cancer journey in a clear and intuitive way.
MetroMapping captures:
• Patients’ and professionals experiences of care
• The full treatment journey, from diagnosis onward
• The information needed at each decision point
• The persons involved in decisions and care (patients, family members, healthcare professionals)
• The context, i.e. physical surroundings such as waiting rooms, objects (brochures, medical devices) that may impact decision making.
By making invisible problems visible (such as missing information or poorly timed decisions), MetroMapping helps teams redesign care pathways so they better support patients’ needs. The visual style of MetroMapping makes it easy to use, even for people with different levels of health literacy, and encourages collaboration across medical disciplines. (see Figure 1)
NEW TOOLS TO SUPPORT BETTER DECISIONS
In addition to MetroMapping, the 4D PICTURE consortium develops two types of decision-support tools:
1. PROGNOSTIC TOOLS
These tools help patients and healthcare professionals explore how different cancer treatments may affect both survival and quality of life. Using reliable clinical data and transparent prediction models, the tools present information in a clear, user-friendly way. The aim is not to tell patients what to choose, but to support meaningful conversations and shared decision-making.
WHO IT IS FOR:
Patients, their families, and healthcare professionals.
2. CONVERSATION TOOLS
Talking about cancer can be difficult. This tool helps open up conversations by using both text and visuals, allowing patients to express what matters most to them, such as their values, preferences, and the language they feel comfortable with.
The tool builds on the “Metaphor Menu” approach (
https://wp.lancs.ac.uk/melc/the-metaphor-menu/(s’ouvre dans une nouvelle fenêtre)) which uses metaphors to help people talk about complex and emotional experiences. It is developed using artificial intelligence and is based on insights from real patient stories shared in blogs and online forums.
