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Lauren Clack’s research prioritizes rigorous development of implementation science methods in addition to furthering the fields to which implementation science is applied. Her research combines these aspects. While her previous research has primarily applied implementation science to the field of infectious diseases and hospital epidemiology, she has a broad interest in applying implementation science to fields with a demonstrated gap between research findings and current practice. Her specific research priorities include:
FTI-Krems
Rahel Naef’s research focuses on the
Her research focuses on the health and well-being of families in vulnerable situations, such as families engaged in caregiving and on families experiencing acute-critical illness, loss or bereavement.
Drawing on a wide range of methodological approaches, she investigates the impact of relational family systems, nursing interventions and models of care on individual and family illness management ability and health outcomes.
Rahel Naef has a particular interest in the study of knowledge translation strategies to promote the systematic uptake of evidence-based, interprofessional care delivery for people with cognitive impairment and their families entering acute care, as well as for those bereaved. The research work is at the intersection of nursing science and implementation science with a focus on family nursing.
Much of Prof. von Wyl’s work centers around Multiple Sclerosis (MS) and the Swiss MS Registry. This registry combines the approach of citizen sciences with digital health studies and has produced important findings to improve care for people with MS. Recent research activities include epidemiological analyses of the life course and disability progression of persons with MS, which combine patient survey data with clinical information, fitness wearables data and electronic patient diaries.
Other research interests include the development of methods for digital epidemiology (e.g., for the design and operation of digitally augmented observational studies), text analysis using crowdsourcing methods (e.g., to analyze patient diaries), and clustering methods for time-series data.
He is also involved in the effectiveness analysis of the SwissCovid Digital Proximity Tracing App.
In close collaboration with his interdisciplinary team and research partners, Tobias designs digital therapeutics for healthy longevity. More specifically, he designs and evaluates digital health interventions to prevent and manage non-communicable diseases (e.g., diabetes or hypertension) and common mental disorders (e.g., depression and anxiety). For this purpose, Professor Kowatsch brings together research teams at the intersection of information systems research, computer science, medicine, and economics. To this end, his research areas focus on
A selection of research projects:
More research projects Link
Janna Hastings’s research explores the impacts and opportunities associated with digitalization in the clinic. The overarching objectives of her research are to accelerate translation and integration of evidence into the clinic, to ensure that digital tools for clinical applications are aligned with the needs of clinicians, and to remove barriers to effective human-computer collaboration to improve patient outcomes.
Specific topics that the Medical Knowledge and Decision Support group researches include:
Evidence synthesis: Her group develops approaches that combine semantics with data extracted from the literature in order to support partial automation of medical evidence synthesis and thereby accelerate the translation of evidence into implementation in the clinic.
Semantic AI: Semantic, meaningful or human-centered artificial intelligence approaches are built around meaningful categories that are understandable to humans. They combine symbolic and sub-symbolic approaches to machine learning and reasoning, and can be used to reduce manual documentation burdens, provide human-friendly explanations, and accelerate the implementation of personalized medicine.
Clinician experiences of digitalization: The group aims to understand and amplify clinician experiences of and expectations of decision support and electronic health information systems, and aligns those with available technological capabilities in order to steer future technological developments towards greater alignment with the needs of clinicians.
Clinician and patient experiences of medical knowledge and evidence: The group aims to understand clinician and patient experiences of the wider medical knowledge and evidence ecosystem, in particular differences in perspectives between different clinicians (interdisciplinarity and interprofessionality) and between clinicians and patients, and how these different perspectives are negotiated in shared decision-making supported by digital tools.
Projects
HBCP: We are collaborators in the Human Behaviour-Change Project, funded by the Wellcome Trust and led by UCL’s Center for Behaviour Change. This project is developing a ‘knowledge system’ based on annotated intervention evidence reports, semantics in the form of an ontology, and an artificial intelligence-based system that is able to predict the outcomes of hypothetical behavior change interventions, applied to an initial case study of smoking cessation behaviors.
ClinDigEx: We are conducting a qualitative interview study of clinician experiences with digital tools in clinical settings in St. Gallen and Zurich. This study is funded by the HSG through startup funds awarded to Janna Hastings, and aims to create a comprehensive map of the landscape of digitalization in the clinic across different hospitals and clinical domains.
VascX: We are collaborators in the Sinergia project ‘Connecting properties of the micro- and macrovasculature from multimodal imaging through genetics and deep learning to better understand vascular pathomechanisms and predict disease risk’ led by the University of Lausanne. This project will explore the genetic basis of vasculatures in multimodal imaging datasets, and our group will explore the semantics of features learned by deep learning approaches.
CEDI: Digitalization is profoundly changing the healthcare ecosystem, with an enormous potential to provide improvements to healthcare professionals, patients and other healthcare stakeholders but is also affiliated with potential challenges and risks. Often clinicians encounter frustrating experiences, especially when digital solutions are developed and deployed with insufficient consideration and understanding of their needs and workflow requirements.
This project aims to study the experiences of clinicians, including physicians and nurses, and their use of digital tools that are an integrated part of their daily work. The objective is to explore how the transformational processes of digitalization impact the work, the use of current tools and workflows, and the professional identities of clinicians, in order to better understand the human experience of healthcare professionals on digital transformation in the clinic. We are interested in notable successes as well as particular pain points and daily frustrations, across all medical specialties, clinical roles, and types of digital tools, including electronic health records, decision support systems, and workflow automation.
In our project, we will perform interviews with clinicians in Switzerland to learn about their experience of using digital tools during their work in the clinic, and subsequently, we will analyze our findings aiming to understand how these tools affect their daily work life, workflow, and professional identity.
