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Helping Cancer Patients to Choose the Best Treatment: Towards Automated Data-Driven and Personalized Information Presentation of Cancer Treatment Options

Authors Emiel Krahmer , Felix Clouth , Saar Hommes , Ruben Vromans , Steffen Pauws , Jeroen Vermunt , Lonneke van de Poll-Franse , Xander Verbeek

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Author Details

Emiel Krahmer
  • Department of Communication and Cognition, Tilburg University, The Netherlands
Felix Clouth
  • Department of Methodology and Statistics, Tilburg University, The Netherlands
  • Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, The Netherlands
Saar Hommes
  • Department of Communication and Cognition, Tilburg University, The Netherlands
  • Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, The Netherlands
Ruben Vromans
  • Department of Communication and Cognition, Tilburg University, The Netherlands
  • Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, The Netherlands
Steffen Pauws
  • Department of Communication and Cognition, Tilburg University, The Netherlands
  • Innovation Excellence, Innovation & Strategy, Philips, Eindhoven, The Netherlands
Jeroen Vermunt
  • Department of Methodology and Statistics, Tilburg University, The Netherlands
Lonneke van de Poll-Franse
  • Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, The Netherlands
  • Department of Medical and Clinical Psychology, Tilburg University, The Netherlands
  • Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
Xander Verbeek
  • Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, The Netherlands

Funding

This research was funded by the commit2data program from the Netherlands Organisation for Scientific Research (NWO) [Grant No. 628.001.030], by the Data Science Center Tilburg (DSC/t), by the "We Care" program from Tilburg University and Elisabeth-TweeSteden hospital [Grant No. 42001155], and by the Netherlands Organization for Health Research and Development (ZonMW), "Kennisvragen Uitkomstgerichte Zorg" [Project No. 80-83900-98-3003], which are all gratefully acknowledged.

Cite As Get BibTex

Emiel Krahmer, Felix Clouth, Saar Hommes, Ruben Vromans, Steffen Pauws, Jeroen Vermunt, Lonneke van de Poll-Franse, and Xander Verbeek. Helping Cancer Patients to Choose the Best Treatment: Towards Automated Data-Driven and Personalized Information Presentation of Cancer Treatment Options. In Commit2Data. Open Access Series in Informatics (OASIcs), Volume 124, pp. 3:1-3:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/OASIcs.Commit2Data.3

Abstract

When a person is diagnosed with cancer, difficult decisions about treatments need to be made. In this chapter, we describe an interdisciplinary research project which aims to automatically generate personalized descriptions of treatment options for patients. We relied on two large databases provided by the Netherlands Comprehensive Cancer Organisation (IKNL): The Netherlands Cancer Registry and the PROFILES dataset. Combining these datasets allowed us to extract personalized information about treatment options for different types of cancer. In a next step we provided personalized context to these numbers, both in verbal statements and in narratives, with the aim to facilitate shared decision making about treatments. We discuss strengths and limitations of our approach, illustrate how it generalizes to other health domains, and reflect on the overall research project.

Subject Classification

ACM Subject Classification
  • Human-centered computing → Human computer interaction (HCI)
  • Computing methodologies → Artificial intelligence
  • Applied computing → Life and medical sciences
Keywords
  • Oncology
  • Data-driven shared decision making
  • Latent class analysis
  • Risk communication
  • Narratives
  • Personalization

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