ABOUT
Whether it is data sharing between healthcare organisations, assistive technologies aiding patients with dementia or technology aiding specialist in surgery, the digital and technological revolution is creating a paradigm shift in healthcare. For example, advances in data collection and storage, e.g. in the form of electronic health records or medical devices, have created tremendous opportunities for new discoveries within the field of health care. In addition, the increasing amount of available technological devices that support patients and their (in)formal caregivers are driving healthcare innovations. Health care research will have to reflect these advancements.
Since 2018, I am working as an assistant professor at the Living Lab in Ageing and Long-Term Care AWO-L, part of the Maastricht University. Our Living Lab was established by Maastricht University in 1998. To date, Maastricht University, nine large long-term care organisations, Gilde Intermediate Vocational Training Institute, VISTA College (secondary vocational education) and Zuyd University of Applied Sciences participate in this Living Lab. Our mission is to improve by means of scientific research: (1) quality of life for older people and their families; (2) quality of care; and (3) quality of work for those employed in long-term care (Verbeek et al., 2019).
As an assistant professor specializing in data science in LTC, Sil advocate for the use of data and innovative methods to enhance our understanding of quality of care, quality of life, and quality of work. Her research is transdisciplinary, drawing evidence from diverse fields including gerontology, psychology, and data science, while adhering to high standards of research integrity and ethics. She actively participates in ethical committees and has regularly published on the intersection of ethics and data. Throughout her academic journey, including her Ph.D. and research experience at the National Institutes of Health (USA), she focused on analyzing large datasets using advanced techniques like Natural Language Processing and web-scraping.
After seven years at Fontys University expanding her skills in teaching and practice-based research, she returned to Maastricht University to establish her own research line regarding datascience in LTC. In 2020, she founded the interdisciplinary core group Data Science, fostering collaborations between 13 care and educational institutions to promote the utilization of data in LTC. This interdisciplinairy initiative led to a ZonMw grant in 2023 akker at improving data-informed LTC.
Sil highly prioritizes team science by engaging stakeholders from various backgrounds to merge science, education, and daily care practice. She (co)leads several projects on AI, incl. the NWO-KIC project QoLead (AI & dementia) and is involved in the AI UM/MUMC+ group. She also highly values open science, as the codes of all her AI projects are freely accessible on Github.
Beyond academia, she engages in policy development and societal impact by contributing to white papers (e.g., Actiz) and advising organizations like VWS (kennisagenda) and the RIVM on data-informed practices. She often communicates her research to non-academic audiences, participate in collaborations with organizations like Verenso and Actiz. In education, she integrates science with daily care practices, co-founded a new bachelor’s program ‘Digital Technology & Care’ and coordinates and teach several courses on statistics and AI (including a Python programming course), which are essential for her research endeavors. She is an assistant editor for the journal Exploration of Digital Health Technologies.
Questions that interest me and that are related to my research line:
Which role can data (and the analyses thereof) play in studying quality: i.e. how can these types of data improve the quality of care, quality of life and quality of work in long-term care for older adults?*
How can we create a learning environment/network regarding ‘data-informed care’ in our long-term care organisations?*
How can NLP and deepen our understanding on quality of care, quality of life and quality of work in long-term care settings? For example by analysing electronic health records.*
How can we combine data from various sources (e.g. electronic health records, sensors, wearables etc) in order to acquire innovative insights, for example related to challenging behavior of cliënts?*
In my role as a researcher, I am also a so-called Linking Pin at Cicero Zorggroep. A Linking Pin focuses on stimulating scientific research within a long-term care organisation. Our role is to coordinate scientific research and corresponding teaching activities, lead a multidisciplinary working group of LTC professionals, and together with staff and older people assist in identifying problems in practice that need further investigation by means of scientific research.
On this website you will find, among other things, my portfolio and a list of my publications including downloadable PDFs or links to websites in case of online articles. In addition, also some of my datavisualisations are displayed here even as my blog posts.
Interests in keywords
Data-informed care, data (science) (incl. text-mining), R(stats) (learning Python), Quality of Care, Long-term Elderly Care, Nursing Home Care, Statistical Analysis, Qualitative Research, Technology Acceptance & Implementation 🤖, Ethics.
You can also find my work @
https://orcid.org/0000-0002-3121-412X https://www.researchgate.net/profile/Sil_Aarts https://www.maastrichtuniversity.nl/s.aarts