Sessions

Questions or else: richard.noll@kgu.de

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.

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.

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. 

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

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.

The workshop aims at improving the completeness and interoperability of data dictionaries through harmonization and standardization. First, the focus lies on the syntactic and semantic level in order to derive concrete technical specifications and implementations: Based on a comprehensive review of existing standards and data dictionaries in common systems, frequently used attributes were identified. In a second step, a "Minimal Information Model" is discussed, in which typical description fields are listed, terminologically cleaned and arranged in a modular system to enable easy use and user-specific expansion. Crosswalks to existing vocabularies and conventions or to international standards are to be discussed.Practical mapping of your Data Dicitonary is possible as a practical exercise!

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!