Programpunkter

How can digital therapeutics and software based medical devices play a role in healthcare innovation?
Using them as tools for innovating and rethinking treatment pathways, this creates leeway to improve efficiency for healthcare professionals and personalised care for patients. Katrina Laks shares the story of Migrevention, her own experience and the hurdles and possibilities for software-based medical devices in changing the mindset for the future of healthcare.

Presentation of the six years of experience in using mixed reality applications in planning liver and heart surgery at Oslo University Hospital. Description of research, development and implementation of clinical applications from image data to surgical strategies in 3D. It was initiated by clinicians based on clinical challenges to be fully compatible with clinical reality. Efficient workflow, fully integrated with hospital infrastructures cloud/browser-based with no need for specialized workstations.Ample experience is derived from surgical planning sessions for colorectal liver cancers and structural heart diseases. Not only limited to the most complex surgical cases. In pediatric heart surgery, holographic visualization brings enhanced 3D anatomical understanding of complex heart defects. It provides insight that reduces the risk of damaging critical structures in the surgical area. Holographic information impacts surgical plans in about half of the tested cases.In liver cancer surgery, holographic visualization brings anatomical overview and improves spatial understanding of internal anatomical structures in relation to the tumour. This is important when planning intricate surgical paths within the liver. Additionally, it better utilizes already available preoperative data to be used in surgical planning as an adjunct to the standard of care.Industrial collaboration has been vital in the establishment of minimum viable products as well as in establishing a start-up. This paved a path towards regulatory approvals and the distribution of applications for clinical use outside our hospital. We will present published and unpublished results from our department - where we have failed and succeeded and what we have learned in the process.Finally, we will provide a glimpse of the future trend in the current project and what is coming next. 

Experiences with collaboration between hospital and vendor on information modelling, templating and software development attempting to increase speed and quality of product.

Introduction to the session "Northern Excellence in Online Records" and short presentation of the NORDeHEALTH project.

Finnish Social and Health Data Permit Authority Findata is the first one-stop shop in the world that issues permits for secondary use of social welfare and health care data. This presentation highlights the Finnish experiences of secondary use from past three years, as the whole EU is now planning to take similar steps towards the European Health Data Space.

EHDS (European Health Data Space) proposes a common European legislation which among other things ensures access to health data for secondary use.In this presentation, we look at the informatics associated with secondary use of health data, established standards and techniques for making data available for secondary use (including OMOP), international real world examples and how healthcare organizations can benefit internally from tools for secondary use.

The Norwegian project "Safer health apps" has looked at how Norway can increase the uptake of health apps in the society – as part of the national, public health service – and developed a "how-to" guide for quality assessment of health apps and similar technologies.

Schedule, track, and manage the entire breakdown and maintenance/calibration process, from opening a work order request to tracking all related operational costs. What's more? AI is at your fingertips, fixing the breakdown by just clicking a button in the app. RTLS  availability takes this CMMS to the next level, providing significant staff time savings by instantly accessing the real-time location of your assets. 

EIT Health is a strong European network in healthcare education, research, technology, business creation and corporate and social innovation. EIT Health is a unique concept for widening participation and outreach across Europe connects the different activities in innovation, business creation, and education towards common targets.

Remarkable progress in artificial intelligence (AI) algorithms performance, and the fast growth in “real world” data available in electronic form generate high hopes for healthcare quality, efficiency, and accessibility improvements. But this game changing progress also causes growing concerns about the effects of growing AI use and its unintended, unanticipated, or even intentionally unethical consequences. Numerous issues and limitations of the algorithms and data used in healthcare and beyond have become more visible, and several organizations and researchers have proposed advice and guidelines to help address these concerns, issues, and limitations. Principles of Responsible AI are now promoted by several important organizations and stakeholders in the AI industry, but there is a need to move these principles towards practical realization and application in real-world scenarios. This panel will address several key aspects of responsible AI in health: explainability and interpretability; bias and fairness; reliability, reusability, and efficiency; privacy and confidentiality protection.

Available for discussion on Tue (23/5) between 9:30 am and 10:30 am and on Thu (25/5) between 9:30 am and 10:30 am.

Reproducibility imposes some special requirements at different stages of each project, including reproducible workflows for the analysis including to follow best practices regarding code style and to make the creation of the manuscript reproducible as well. Available tools therefore include version control systems such as Git and document creation tools such as Quarto or R Markdown. However, a re-usable project template mapping the entire process from performing the data analysis to finally writing the manuscript in a reproducible manner is yet lacking. This work aims to fill this gap by presenting an open source template for conducting reproducible research projects utilizing a containerized framework for both developing and conducting the analysis and summarizing the results in a manuscript. This template can be used instantly without any customization.