Sessions

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.

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

Each epidemic and pandemic is accompanied by an infodemic. The infodemic during the COVID-19 pandemic was unprecedented. Accessing accurate information was difficult and misinformation harmed the pandemic response, the health of individuals, and trust in science, governments and societies. WHO built a community-centered information platform, the HIVE, to deliver on the vision of ensuring that all people everywhere have access to the right information, at the right time, in the right format in order to make decisions to protect their health.

Complementary and alternative medicine (CAM) is widely adopted by families with autistic children. This study aims to predict family caregivers' CAM implementation based on the behavioral (degree and betweenness), environmental (positive feedback and social persuasion), and personal features (language style) of family caregivers in online communities.

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.

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!

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

Lets talk about interoperable order set creation than can be used by any EMR

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

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.

CANCELLED. 
Research on real-world data is becoming increasingly important. The current restriction to clinical data in Germany limits the view of the patient. To gain comprehensive insights, claims data can be added to the existing knowledge. However, standardized transfer of German claims data into OMOP CDM is currently not possible. In this paper, we conducted an evaluation regarding the coverage of source vocabularies and data elements of German claims data in OMOP CDM. We point out the need to extend vocabularies and mappings to support research on German claims data.

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 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