Sessions

Patient generated health data (PGHD) integrates patients` values and preferences into decision-making. Digitalization enables the integration of PGHD with electronic patient records. However, the lack of digital tools and applications hampers the use of PGHD. The purpose of this workshop is to gather the current situation in research and to form a transdisciplinary network of researchers.Discussion topics:1.Identification of the researchers, research projects and digital tools and applications for PGHD to build a network of researchers in the field.2.Experiences and perceptions of the research and practice regarding the digital tools and applications for PGHD3.Recommendations for future research topics in the field of PGHD.Keywords. digitalization, shared decision making, patient generated health dataYou are warmly welcome!

With more than a decade of supporting its customers in their healthcare data standardization efforts, B2i Healthcare publicly launched the Snowray Terminology Service to a global audience. This demonstration will introduce the most important functionalities to future users. Users are welcome to follow along with a free account.During the demonstration, we will cover the processes of creating and publishing new standard resources, including Code Systems, Value Sets and Concept Maps.

Sharing our experience of mapping the Swiss Personalized Health Network Dataset to Fast Healthcare Interoperability Resources

Digital health innovations are designed to help save time, boost accuracy and efficiency, and combine technologies in ways that will revolutionize the new digital healthcare era. By optimizing the right tools and open system platforms increases the innovation for healthcare - which has created tangible benefits for the entire healthcare-chain from the profession to patient with real-time access to patient information and improving care processes. Finland is the frontrunner in implementing open data in ecosystem platforms, learn how the CIO Toni Suihko from Kanta-Häme Hospital District (KHSHP) has increased the speed of healthcare innovations.

Patients with cancer starting invasive treatment programs often develop depression that physicians struggle to recognize at an early stage. We developed a prediction model for early identification of patients at risk for depression within the first month of chemo- or radiotherapy treatment to assist physicians and healthcare workers. 

Norge, Danmark, Finland och Sverige arbetar alla med lösningar för att få till nationella gemensamma läkemedelslistor. Det finns stora likheter mellan länderna när det gäller digital informationshantering kring läkemedel. Alla har sedan många år e-recept och en central lagringsplats för dessa. Det finns dock betydande skillnader mellan de system som används eller är på väg att implementeras i de fyra länderna. I presentationen ger forskare från de olika länderna en översikt av nuläget i de fyra länderna, samt delar med sig av sina reflektioner kring utmaningar. Presentationen görs på engelska.
Norway, Denmark, Finland and Sweden are all working on solutions to achieve national common drug lists. There are great similarities between the countries when it comes to digital information management around medicines. For many years, everyone has had e-prescriptions and a central storage location for these. However, there are significant differences between the systems in use or about to be implemented in the four countries. In the presentation, researchers from the various countries give an overview of the current situation in the four countries, as well as share their reflections on challenges. The presentation is held in English.

Short introduction to the National Research Data Infrastructure for Personal Health Data (NFDI4Health) and proposed solutions towards findability and interoperability of clinical and epidemiological studies. Two services will be presented: the German Central Health Study Hub to support the findability of studies and the Metadata Annotation Workbench to support enrichment of data collection instruments with standardized vocabularies on the study item level.

Process mining is a relatively new method that connects data science and process modelling. In the past years a series of applications with health care production data have been presented in process discovery, conformance check and system enhancement. In this paper we apply process mining on clinical oncological data with the purpose of studying survival outcomes and chemotherapy treatment decision in a real-world cohort of small cell lung cancer patients treated at Karolinska University Hospital (Stockholm, Sweden). The results highlighted the potential role of process mining in oncology to study prognosis and survival outcomes with longitudinal models directly extracted from clinical data derived from healthcare.

Questions or else: richard.noll@kgu.de

Third party apps extend the capabilities of electronic health record systems by offering additional capabilities and features, streamlining processes in specific therapeutic areas, bringing in patient generated health data, and providing advanced analytics and AI functionalities to get more benefits out of the data in the system.The HL7 FHIR specification is an enabler for this. This showcase presents dozens of FHIR apps connected to dozens of FHIR capable platforms.

Most Nordic countries have created their own set of FHIR base profiles. There has not been harmonization between these efforts, rather each country has had their own internal process. However, harmonizing the base profiles would be really useful. A harmonized content format across the Nordic countries would allow a FHIR app developed in one country to be used in another without major modifications. It would also simplify sharing health data across borders.A new initiative is being launched to harmonize the FHIR base profiles across the Nordic countries.