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Objective: At the Medical Faculty of the Goethe University Frankfurt am Main, the elective course “climate change and health” was offered to students in the clinical phase of their medical studies for the first time in the winter semester 2021/22 (any unfilled places were made available to interested students studying other subjects). Despite attracting considerable attention, this topic has not yet been incorporated into the curriculum of medical studies. Our aim was therefore to teach students about climate change and discuss its effects on human health. The students evaluated the elective in terms of various factors relating to knowledge, attitudes and behavior.Project description: The elective focused on the concept of Planetary Health, with an emphasis on the health consequences of climate change, as well as possibilities for action and adaptation in clinical and practical settings. The course took place in three live, online sessions (with inputs, discussion, case studies and work in small groups), as well as online preparation and a final written assignment for which students were asked to reflect on the subject. The standardized teaching evaluation questionnaire (=didactic dimension) of Goethe University was used online to evaluate the elective, whereby the questionnaire was extended to include the measurement of changes in students’ agreement with items (dimensions) relating to knowledge, attitudes and behavior (personal behavior and behavior as physicians) before and after the course (pre/post comparison).Results: Students expressed high levels of satisfaction with the course content, the presentation of the course, and the organization of the elective. This was reflected in very good to good overall ratings. The pre/post comparisons further showed a significant, positive shift in agreement ratings in almost all dimensions. The majority of respondents also wanted the topic to be firmly embedded in the medical curriculum. Conclusion: The evaluation shows that with respect to the impact of climate change on human health, the elective course had a clear influence on the knowledge, attitudes, and behaviors of the students. In view of the relevance of the topic, it is therefore important that this subject is included in medical curricula in the future.

A clinical decision support system based on different methods of artificial intelligence (AI) can support the diagnosis of patients with unclear diseases by providing tentative diagnoses as well as proposals for further steps. In a user-centred-design process, we aim to find out how general practitioners envision the user interface of an AI-based clinical decision support system for primary care. A first user-interface prototype was developed using the task model based on user requirements from preliminary work. Five general practitioners evaluated the prototype in two workshops. The discussion of the prototype resulted in categorized suggestions with key messages for further development of the AI-based clinical decision support system, such as the integration of intelligent parameter requests. The early inclusion of different user feedback facilitated the implementation of a user interface for a user-friendly decision support system. [ABSTRACT FROM AUTHOR]

Background: The majority of patients in disease management programs (DMPs) for type 2 diabetes (T2DM) and coronary heart disease (CHD) in Germany are enrolled by their general practitioner (GP). The aim of this study was, in the context of upcoming DMP expansions, to elicit GPs' current experiences and opinions regarding the perceived effectiveness and acceptance of the DMPs T2DM and CHD, as well as to determine beneficial and hindering aspects of the implementation of these programs from a GP's perspective., Methods: In August and September 2020, 20 GPs of teaching practices of the University Hospital Cologne with experiences in DMPs were interviewed in semi-structured focus group discussions. Their expectations, attitudes and opinions regarding the DMPs T2DM and CHD were evaluated and analyzed according to the content-structuring qualitative content analysis by Kuckartz., Results: The DMP T2DM was rated as generally positive by the respondents due to the structured treatment including regular foot and eye examinations, close patient contacts and perceptions of improved health outcomes. The DMP CHD was rated more negatively by the respondents because of a high and partly unnecessary documentation workload and limited therapeutic freedom, leading to a perceived ineffectiveness for patients' health outcomes. Thus, there was a discrepancy in the perceived effectiveness of the examined DMPs, causing a lower acceptance of the DMP CHD. Therefore, some of the respondents tended to enroll fewer patients into the DMP CHD or to drop out of the DMP CHD., Discussion: In order to increase the acceptance and sustainability of DMPs some elements of the DMP CHD as well as the remuneration and the documentation need to be reconsidered. Additionally, future studies on the acceptance of DMPs should differentiate between different DMPs in order to generate valid results., (Copyright © 2024. Published by Elsevier GmbH.)

A clinical decision support system based on different methods of artificial intelligence (AI) can support the diagnosis of patients with unclear diseases by providing tentative diagnoses as well as proposals for further steps. In a user-centred-design process, we aim to find out how general practitioners envision the user interface of an AI-based clinical decision support system for primary care. A first user-interface prototype was developed using the task model based on user requirements from preliminary work. Five general practitioners evaluated the prototype in two workshops. The discussion of the prototype resulted in categorized suggestions with key messages for further development of the AI-based clinical decision support system, such as the integration of intelligent parameter requests. The early inclusion of different user feedback facilitated the implementation of a user interface for a user-friendly decision support system.