Scientific research is inaccessible to many people. For example, someone newly diagnosed with cancer might be told they need chemotherapy, immunotherapy, endocrine therapy, or targeted therapy. But to understand any research written about these therapies, a patient would also have to absorb more complex concepts: signal transduction pathways, gene expression modulators, apoptosis inducers, angiogenesis inhibitors....The volume of information can be overwhelming for most of us, and we can easily misinterpret or miss the data's significance.
In order to expand the reach of clinical data to patients, there is a need to create accurate simplifications of the research. Patients are requesting better access to the latest clinical research by attending major medical conferences and seeking content from trusted sources online. By clarifying key research findings, accessible data can help patients more easily discuss treatment options with their healthcare professional, empowering them to participate in their treatment decisions.
Medical publications are increasingly including Plain Language Summaries (PLS) and enhanced digital content with the original published articles. Among digital content, interactive data visualizations in particular have the potential to make data more understandable (data democratization) and facilitate the exchange of relevant data and concepts between and among healthcare professionals, patients, advocates, and the public. The combination of both written and visual simplifications of complicated scientific data can encourage data dissemination and result in better health literacy.
I love talking about research. For me, the combination of pictures AND words is a more powerful way to communicate concepts. These visualizations were created in Tableau as assignments for my certificate program in Infographics & Data Visualization with Parsons School of Design. Clicking on the image will take you to my Tableau Public site where these are published. I frequently revisit the data to refine and improve the information presented, so check back to see what has changed!
A plain language interpretation of the BRCA1 data as a subset derived from the paper: Rebbeck, Timothy R et al. “Mutational spectrum in a worldwide study of 29,700 families with BRCA1 or BRCA2 mutations.” Human mutation vol. 39,5 (2018): 593-620. doi:10.1002/humu.23406
An interpretation of Table 1 Incidence of the most common AEs occurring in >10% of patients from the paper: Robson, M E et al. “OlympiAD final overall survival and tolerability results: Olaparib versus chemotherapy treatment of physician's choice in patients with a germline BRCA mutation and HER2-negative metastatic breast cancer.” Annals of oncology : official journal of the European Society for Medical Oncology vol. 30,4 (2019): 558-566.
This data story explored the causes of cardiovascular disease as the leading cause of death globally.
This project looked at the location of waste sites in Illinois (where I lived for 20 years) and cancer rates.
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