Programpunkter

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.

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.

I am pleased to confirm my availability to present the poster from 10 am to 12 pm during the initial two days of the conference schedule.This is a retrospective study of 812 patients aged 50 years or older who had dual-energy X-ray absorptiometry (DXA) and radiographs of the hands within 12 months of each other. This dataset was randomly split into training/validation (n=533) and test (n=136) datasets. A deep learning (DL) framework was used to predict osteoporosis/osteopenia. Correlations between the textural analysis of the bones and DXA measurements were obtained. We found that the DL model had an accuracy of 82.00%, sensitivity of 87.03%, specificity of 61.00% and an area under the curve (AUC) of 74.00% to detect osteoporosis/osteopenia. Our findings show that radiographs of the hand can be used to screen for osteoporosis/osteopenia and identify patients who should get formal DXA evaluation.

Separate registration required: https://www.mie2023.org/tutorials, openEHR consists of open specifications and clinical models for building healthcare and welfare information systems. This Master Class presents the problems openEHR addresses and how openEHR addresses them using its reference model and the clinical models that consist of archetypes and templates. It will further be explained how openEHR relates to other standards, how openEHR can be localised and implemented and how the organisation openEHR International and its surrounding community work.

OpenDataPsy offers a set of ready-to-use standardized datasets for research in psychiatry.

The aim of this presentation and paper is to identify the underlying obstacles and provide recommendations to promote the dissemination of competency-based learning objectives catalogs for curricular development in health data and information sciences.