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Cocreation with Dutch patients of decision-relevant information to support shared decision-making about adjuvant treatment in breast cancer care. | LitMetric

AI Article Synopsis

  • - The study focused on creating patient decision aids (PtDAs) for breast cancer treatment to help patients with shared decision-making by providing personalized risk information, benefit/harm details, and value clarification methods in a patient-friendly manner.
  • - Researchers conducted sessions with breast cancer patients to gather input on information needs, which highlighted the desire for structured information immediately after diagnosis and clear benefit/harm data for treatment options.
  • - Findings suggested that a PtDA should present an overview of treatment options with layers for detailed information, utilize bar graphs for personalized survival rates, and clarify the concept of 'personalization' to enhance patient understanding.

Article Abstract

Background: To support patients in shared decision-making about treatment options, patient decision aids (PtDAs) usually provide benefit/harm information and value clarification methods (VCMs). Recently, personalized risk information from prediction models is also being integrated into PtDAs. This study aimed to design decision-relevant information (i.e., personalized survival rates, harm information and VCMs) about adjuvant breast cancer treatment in cocreation with patients, in a way that suits their needs and is easily understandable.

Methods: Three cocreation sessions with breast cancer patients (N = 7-10; of whom N = 5 low health literate) were performed. Participants completed creative assignments and evaluated prototypes of benefit/harm information and VCMs. Prototypes were further explored through user testing with patients (N = 10) and healthcare providers (N = 10). The researchers interpreted the collected data, for example, creative and homework assignments, and participants' presentations, to identify key themes. User tests were transcribed and analysed using ATLAS.ti to assess the understanding of the prototypes.

Results: Important information needs were: (a) need for overview/structure of information directly after diagnosis and; (b) need for transparent benefit/harm information for all treatment options, including detailed harm information. Regarding VCMs, patients stressed the importance of a summary/conclusion. A bar graph seemed the most appropriate way of displaying personalized survival rates; the impact of most other formats was perceived as too distressful. The concept of 'personalization' was not understood by multiple patients.

Conclusions: A PtDA about adjuvant breast cancer treatment should provide patients with an overview of the steps and treatment options, with layers for detailed information. Transparent information about the likelihood of benefits and harm should be provided. Given the current lack of information on the likelihood of side effects/late effects, efforts should be made to collect and share these data with patients. Further quantitative studies are needed to validate the results and to investigate how the concept of 'personalization' can be communicated.

Patient Or Public Contribution: Ten breast cancer patients participated in three cocreation sessions to develop decision-relevant information. Subsequent user testing included 10 patients. The Dutch Breast Cancer Association (BVN) was involved as an advisor in the general study design.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9327829PMC
http://dx.doi.org/10.1111/hex.13510DOI Listing

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