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Improving shared decision-making about cancer treatment through design-based data-driven decision-support tools and redesigning care paths: an overview of the 4D PICTURE project

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  • Judith A. C. Rietjens
  • Ingeborg Griffioen
  • Jorge Sierra-Pérez
  • Gaby Sroczynski
  • Uwe Siebert
  • Alena Buyx
  • Barbara Peric
  • Inge Marie Svane
  • Jasper B. P. Brands
  • Karina D. Steffensen
  • Carlos Romero Piqueras
  • Elham Hedayati
  • Maria M. Karsten
  • Norbert Couespel
  • Canan Akoglu
  • Roberto Pazo-Cid
  • Hester F. Lingsma
  • Maartje H. N. Schermer
  • Ewout W. Steyerberg
  • Ida J. Korfage
  • Anne M. Stiggelbout
  • Claudia Cruz Oliveira
  • Monique Roobol
  • Ignacio López-Forniés
  • Marleen Kunneman
  • Suzan Verberne
  • Anne Kuld
  • Erik M. van Mulligen
  • Bettina Mølri Knudsen
  • Jan A. Kors
  • Lionne D. F. Venderbos
  • Marco Donia
  • Linetta B. Koppert
  • Amara C. Nwosu
  • Elfi M. Verheul
  • Yeray Sañudo
  • Marie Kremer
  • Jorge Gracia
  • Antonio Antón
  • Maud Schreijer
  • Chris Bangma
  • Laura Hartman
  • David van Klaveren
  • Monserrat Aiger Valles
  • Lucia Pitarch
  • Lara R. Hallsson
  • Michel Wouters
  • Ellen Kapiteijn
  • Nienke de Glas
  • Marieke van Buchem
  • Frank Doornkamp
  • Simona Borštnar
  • Leonard Wee
  • Therese Pross
  • Marta Silva
  • Enea Venegoni
  • Nora Lorenzo
  • Susanne Wallberg
  • Kathrina Dankl
  • Teresa Puértolas de Jesús
  • Juan Lao Romera
  • Paula Gomila Pons
  • Paula Melo Signerez
  • Fernando Secomandi
  • Dirk Snelders
Article number1-15
<mark>Journal publication date</mark>31/01/2024
<mark>Journal</mark>Palliative Care and Social Practice
Number of pages15
Publication StatusPublished
<mark>Original language</mark>English


Background:: Patients with cancer often have to make complex decisions about treatment, with the options varying in risk profiles and effects on survival and quality of life. Moreover, inefficient care paths make it hard for patients to participate in shared decision-making. Data-driven decision-support tools have the potential to empower patients, support personalized care, improve health outcomes and promote health equity. However, decision-support tools currently seldom consider quality of life or individual preferences, and their use in clinical practice remains limited, partly because they are not well integrated in patients’ care paths. Aim and objectives:: The central aim of the 4D PICTURE project is to redesign patients’ care paths and develop and integrate evidence-based decision-support tools to improve decision-making processes in cancer care delivery. This article presents an overview of this international, interdisciplinary project. Design, methods and analysis:: In co-creation with patients and other stakeholders, we will develop data-driven decision-support tools for patients with breast cancer, prostate cancer and melanoma. We will support treatment decisions by using large, high-quality datasets with state-of-the-art prognostic algorithms. We will further develop a conversation tool, the Metaphor Menu, using text mining combined with citizen science techniques and linguistics, incorporating large datasets of patient experiences, values and preferences. We will further develop a promising methodology, MetroMapping, to redesign care paths. We will evaluate MetroMapping and these integrated decision-support tools, and ensure their sustainability using the Nonadoption, Abandonment, Scale-Up, Spread, and Sustainability (NASSS) framework. We will explore the generalizability of MetroMapping and the decision-support tools for other types of cancer and across other EU member states. Ethics:: Through an embedded ethics approach, we will address social and ethical issues. Discussion:: Improved care paths integrating comprehensive decision-support tools have the potential to empower patients, their significant others and healthcare providers in decision-making and improve outcomes. This project will strengthen health care at the system level by improving its resilience and efficiency.