Programpunkter

The European Digital Innovation Hub (EDIH) project Health Data Sweden (HDS), initiated in January 2023, aims to support this development by creating a more effective access to services to regarding digitalisation of the health care system both regionally and nationally, through the use of health data. The HDS connects 17 partners from all over Sweden, who currently offer services in health data and related fields such as digital care and e-health, to various target groups and stakeholders. HDS will also connect with other EDIHs throughout Europe, to transfer knowledge and share best practices concerning the use of health data and related fields, in order to improve healthcare on the EU level.In this panel, we will present some of the main challenges and needs in the health data context identified by the partners behind EDIH-HDS, and discuss how the project will address these obstacles. The five main work packages (the focus of WP1 is primarily administrative) will provide the structure for the presentation. In order to engage the audience and stimulate feedback and discussion, the panel will contain interactive elements throughout.

Separate registration required: https://www.mie2023.org/tutorials,With this tutorial, participants will gain a detailed insight into the Data Sharing Framework (DSF). The open source DSF enables users to execute biomedical research and healthcare delivery processes across organizations, and the tutorial will demonstrate this with examples from the German Medical Informatics Initiative (MII) funded by the Federal Ministry of Education and Research (BMBF). The tutorial will cover fundamental concepts of distributed processes, the DSFs architecture and key standards such as HL7 FHIR and BPMN 2.0. Participants will have the opportunity to gain hands-on experience with the DSF by working with different processes in a lab setting. Technical aspects such as authentication and authorization will be covered, as well as guidance on using the DSF for other use cases. This tutorial is designed for those involved in distributed research projects, including project members and software developers, as well as individuals interested in multi-organizational research projects.Additional information: https://dsf.dev/tutorials/MIE2023.html

Equal access to health data is far from reality today and there is a lack of comparison between countries. To motivate, understand and increase progress, we start from the position that highlighting current status, sharing evidence related to practices and policies, and identifying major enablers and obstacles across national and regional boundaries is necessary. Therefore, we have invited panel participants to introduce five different countries, representing five different stages of and approaches to patients’ ORA implementation.

It is of utmost importance to understand better the requirements for a Digital Therapeutics (DTx) design and trial service that supports the design of DTx and their efficient evaluation via feasibility studies, optimization trials (e.g., micro-randomized trials), efficacy or effectiveness trials (e.g., randomized controlled trials). This workshop has, therefore, the objective of gathering such requirements by applying the World Café methodology and discussing several complex care scenarios. We welcome participants with various backgrounds (e.g., technical, regulatory, medical, ethical) who bring in different perspectives.

It is an obvious paradox that we as citizens, present in all clinical health encounters, lack tools to take full advantage of ongoing digital transformation in health care. In this panel we will discuss user needs and design of digital tool to improve access to personally relevant health information from trusted sources. Of special interest is adherence to treatment. The attendees can learn about opportunities to “collect, curate and control” relevant, personal health information, and digital services for personal health data and access trustworthy, up-to-date information that better meet situated, everyday needs.

Predicting Progression of Type 2 Diabetes using Primary Care Data with the Help of Machine Learning

A demonstration of an open source software prototype for improving infection control in hospitals called Smart Infection Control System (SmICS). It provides services for tracing contacts between patients, showing in-depth details for microbiological findings, patients movements and wards and offers epidemiological curves without having a vendor-dependent data storage within the application, because it is fully based upon an open interoperability standard (openEHR).

The MIE conference has always been a hub for innovation and cutting-edge technology. This year was no exception several demonstrators showcase their unique solutions to healthcare problems. Use the opportunity to take a closer look at some of the most striking demonstrators present at the conference, highlighting their diversity and the potential impact they could have on various healthcare-related challenges

The automatic de-identification of clinical narrative text offers efficient patient data privacy protection and eases reuse of clinical data. CliniDeID applies an ensemble method combining deep and shallow machine learning with rule-based algorithms and is released as free and open-source solution to de-identify unstructured clinical text with high accuracy. It was recently evaluated with a selection of clinical text corpora and reached high sensitivity and positive predictive value.

The MIE conference has always been a hub for innovation and cutting-edge technology. This year was no exception several demonstrators showcase their unique solutions to healthcare problems. Use the opportunity to take a closer look at some of the most striking demonstrators present at the conference, highlighting their diversity and the potential impact they could have on various healthcare-related challenges