Dania Schütze

Background: Only few exercise trials have been conducted in the immediate time after a child’s first cancer diagnosis. The Exercise CC Trial was designed to study the effects of exercise during the first 8 weeks following the diagnosis. However, young patients have not been involved in designing an exercise intervention in this care-intensive period of time in which complying with regular exercise regimens may be particularly difficult. To understand factors facilitating compliance and to prevent drop-outs in this critical period, this study aims to engage adolescents with cancer in designing an exercise intervention by incorporating patient perspectives in research development. Methods: A workshop was conducted with adolescents who had previously participated in exercise therapy during their cancer treatment. This interactive session allowed participants to share their experiences and contribute to the intervention design prior to enrolling patients in the trial. Data was collected through a group discussion, which was recorded and transcribed for qualitative content analysis using MAXQDA20 software, ensuring a comprehensive understanding of participants’ views. Results: The workshop, attended by four patients aged 17 to 20, highlighted various aspects of exercise therapy. Participants valued the flexibility of choosing between various exercises and noted the psychological benefits of physical activity, which provided them with a constructive outlet and relief during treatment. They also appreciated the physical improvements and the motivational impact of monitoring progress. Importantly, the study revealed the need for personalized exercise regimes that consider individual physical conditions and preferences. Conclusions: We present an innovative approach in pediatric exercise oncology inviting the perspectives of adolescents and young adults to participate in research and shape the design of intervention details during the care-intensive phase immediately following a cancer diagnosis. We describe our “lessons learned” in giving adolescents a voice and share their knowledge and insights into their specific needs and preferences of exercise regimens in trials. This approach ensures that intervention details align with young patients’ expectations, which can be opposite to experts’ assumptions. Trial registration: DRKS-ID: DRKS00032259. Registered on 10.07.2024.

Background: Clinical decision support systems (CDSSs) have shown promise in improving diagnosis in primary care, particularly for chronic diseases. The SATURN (Smart Physician Portal for Patients With Unclear Disease) project developed a CDSS prototype for primary care in Germany that uses artificial intelligence to reduce diagnostic uncertainty in unclear and rare diseases. It generates recommendations based on clinical data from university hospitals stored in a standardized common data model. However, integrating primary care data in Germany remains challenging due to the use of country-specific vocabularies and heterogeneous data structures. Therefore, integration of medical concepts into general practitioners’ user interfaces (UIs) and improved workflow design is needed. Objective: This study investigates how the UI of a CDSS for primary care should be designed to facilitate the user-friendly entry of medical concepts. Methods: A structured, iterative user-centered design process of five steps was applied: (1) conceptualization, including analysis of requirements and objectives, (2) implementation of the CDSS UI, (3) analysis of user and expert feedback, (4) workshop with experts in the primary care electronic health record system, and (5) development of an extended concept for the system UI. Results: This study identified requirements and options for supporting data entry in the UI of a CDSS for primary care, thus providing a framework for future implementation and prototype development. Usability testing revealed the need to refine input support, particularly the language used to make the system easy for general practitioners to use. Further effort is required to map this. In addition, we have identified a system interface to electronic patient records in primary care as essential for the system. Conclusions: This paper demonstrates how standardized medical terminologies can be integrated into a CDSS UI for primary care. The user-centered design approach has been effective in developing CDSS UIs that align with clinicians’ workflows and provide a user-friendly experience. Although the current technical infrastructure presents significant challenges when connecting to primary care electronic health record systems, collaborating with experts enabled us to identify potential interface solutions. Overall, the results indicate a need for optimized physician language input support and interoperability, including standardized data entry, automated tools, and artificial intelligence–based approaches to enhance data quality and usability.

Background: General practitioners are confronted with a wide variety of diseases and sometimes diagnostic uncertainty. Clinical decision support systems could be valuable to improve diagnosis, but existing tools are not adapted to the requirements and workflow in the primary setting. In project SATURN (Smart physician portal for patients with unclear disease), the prototype of a clinical decision support system based on artificial intelligence is being developed together with users specifically for primary care in Germany. It aims to reduce diagnostic uncertainty in cases of unclear and rare diseases and focuses on 3 medical fields. A user-centered design approach is applied for prototype development and evaluation. Objective: This study evaluates the usability of a high-fidelity prototype and explores aspects of user experience like the subjective impression, satisfaction, and areas of improvement. Methods: A total of 5 general practitioners participated in the evaluation, which consisted of (1) a remote think-aloud test, (2) a postsession interview, and (3) a survey with the System Usability Scale. During the think-aloud tests, the participants verbalized their thoughts and actions and solved several vignette-based tasks. Remarkable observations were logged, transcribed with quotes, and analyzed for usability problems and positive findings. All observations and interview responses were deductively assigned to the following categories: (1) content, (2) comprehensibility, (3) user-friendliness, (4) layout, (5) feedback, and (6) navigation. Usability problems were described in detail and solutions for improvement proposed. Median and total scores were calculated for all questionnaire items. Results: The evaluation detected both strengths and areas for improvement. The participants particularly liked the clear and well-structured layout of the prototype. Key issues identified were content-related limitations, such as the inability to enter unlisted symptoms, medications, and examination findings. Also, participants found the terminology for laboratory not suitable to their needs. Another key issue was a lack of user-friendliness concerning the time required to input medication plans and lab values. Participants expressed a need for faster data entry, potentially through direct imports from practice management systems or laboratory files. Adding symptom duration, weighting symptoms, and incorporating hereditary factors were suggestions made for improvement. Overall, the SATURN prototype was deemed useful and promising for future clinical use, despite the need for further refinements, particularly in the areas of data entry, as this is a key obstacle to its use. Conclusions: The usability evaluation methods combined proved to be location independent and easy to use. They provided important findings on usability issues and improvements that will be implemented in a second high-fidelity prototype, which will also be tested by users. Technically demanding user requirements, such as direct data transfer from the practice management system and entry options that require complex data models, were beyond the scope of this project, but should be considered in future development projects.

BACKGROUND Clinical decision support systems (CDSSs) have shown promise in improving diagnosis in primary care, particularly for chronic diseases. The SATURN (Smart Physician Portal for Patients With Unclear Disease) project developed a CDSS prototype for primary care in Germany that uses artificial intelligence to reduce diagnostic uncertainty in unclear and rare diseases. It generates recommendations based on clinical data from university hospitals stored in a standardized common data model. However, integrating primary care data in Germany remains challenging due to the use of country-specific vocabularies and heterogeneous data structures. Therefore, integration of medical concepts into general practitioners’ user interfaces (UIs) and improved workflow design is needed. OBJECTIVE This study investigates how the UI of a CDSS for primary care should be designed to facilitate the user-friendly entry of medical concepts. METHODS A structured, iterative user-centered design process of five steps was applied: (1) conceptualization, including analysis of requirements and objectives, (2) implementation of the CDSS UI, (3) analysis of user and expert feedback, (4) workshop with experts in the primary care electronic health record system, and (5) development of an extended concept for the system UI. RESULTS This study identified requirements and options for supporting data entry in the UI of a CDSS for primary care, thus providing a framework for future implementation and prototype development. Usability testing revealed the need to refine input support, particularly the language used to make the system easy for general practitioners to use. Further effort is required to map this. In addition, we have identified a system interface to electronic patient records in primary care as essential for the system. CONCLUSIONS This paper demonstrates how standardized medical terminologies can be integrated into a CDSS UI for primary care. The user-centered design approach has been effective in developing CDSS UIs that align with clinicians’ workflows and provide a user-friendly experience. Although the current technical infrastructure presents significant challenges when connecting to primary care electronic health record systems, collaborating with experts enabled us to identify potential interface solutions. Overall, the results indicate a need for optimized physician language input support and interoperability, including standardized data entry, automated tools, and artificial intelligence–based approaches to enhance data quality and usability.

BACKGROUND In the project SATURN (Smart physician portal for patients with unclear disease) the prototype of a clinical decision support system based on artificial intelligence is being developed specifically for primary care in Germany. It aims to reduce diagnostic uncertainty in cases of unclear and rare diseases and focuses on three medical fields. A user-centered design approach is applied for prototype development and evaluation. OBJECTIVE This study explores the usability of a high-fidelity prototype. Aspects of user experience like the subjective impression, satisfaction, and improvement requests are also investigated. METHODS Five general practitioners participated in the evaluation of the prototype which consisted of (1) a remote think-aloud test, (2) a post-session interview, and (3) a survey with the System Usability Scale. All three parts were consecutively carried out in individual remote sessions. During the think-aloud tests, which were video- and audiotaped, the participants verbalized their thoughts and actions and had to solve several tasks which were based on a primary care case vignette. Remarkable observations were logged, transcribed with quotes, and analyzed for usability problems and positive findings. All observations and interview responses were deductively assigned to the following categories: (1) Content, (2) Comprehensibility, (3) User-friendliness, (4) Layout, (5) Feedback, (6) Navigation. Usability problems were described in detail and solutions for improvement proposed. Median and total scores were calculated for all questionnaire items. RESULTS The evaluation detected both strengths and areas for improvement. Key issues identified were content-related limitations, such as the inability to enter unlisted symptoms, medications, and examination findings in the dropdown menus. Participants also found the terminology for laboratory values did not match their day-to-day vocabulary, as common abbreviations were not recognized. Suggestions for improving the content of the system were also made and included adding symptom duration, weighting symptoms, and incorporating hereditary factors. Another key issue was a lack of user-friendliness concerning the time required to input medication plans and lab values. This aspect was criticized for being cumbersome, with participants expressing a need for faster data entry, potentially through direct imports from practice management systems or laboratory files. Despite these challenges, participants praised other aspects of user-friendliness (use of stored diagnoses and symptoms) and navigation (top navigation bar), and particularly liked the clear and well-structured layout. Overall, the SATURN prototype was deemed useful and promising for future clinical use, despite the need for further refinements, particularly in the areas of data entry. CONCLUSIONS The usability evaluation methods combined proved to be location independent and easy to use, and were apt to detect usability problems in detail. Technically demanding user requirements, such as direct data transfer from the practice management system and entry options that require complex data models were beyond the scope of this project. However, they should be considered in future development projects. CLINICALTRIAL not applicable

Hintergrund: In der allgemeinmedizinischen Forschung in Deutschland haben sich in den letzten Jahren zunehmend partizipative Forschungsansätze etabliert. Bei dieser Art der Forschung werden die Sichtweisen und das Erfahrungswissen relevanter Interessensgruppen, sogenannte Stakeholder, die bisher oftmals nur Forschungsobjekt waren, aktiv in den Forschungsprozess eingebunden. Im Bereich der Allgemeinmedizin sind neben hausärztlichen Praxisteams (Hausärzt:innen, Medizinische Fachangestellte, weitere Professionen) insbesondere Patient:innen sowie Bürger:innen relevante Stakeholder, durch deren aktive Beteiligung die Relevanz und Machbarkeit von Forschungsprojekten gesteigert werden kann. Zielsetzung: Mit dieser erfahrungsbasierten Handreichung sollen Wissenschaftler:innen zur aktiven Beteiligung von Stakeholdern an Forschung ermutigt und der Einsatz partizipativer Forschungsansätze weiter gefördert werden. Dabei legt diese Handreichung den Fokus bewusst auf die Besonderheiten allgemeinmedizinischer Forschung und der in diesem Kontext relevanten Stakeholder. Die Handreichung soll Hilfestellungen geben, wie ein Einstieg gelingen kann und was es bei der Planung und Umsetzung von Beteiligungsaktivitäten mit Patient:innen, Bürger:innen, Hausärzt:innen und Medizinischen Fachangestellten zu berücksichtigen gilt. Methode: Die Eckpunkte für diese Handreichung wurden im Rahmen eines Forschungssymposiums der Initiative Deutscher Forschungspraxennetze DESAM-ForNet erarbeitet, das im April 2024 in Frankfurt am Main stattfand. Bei dem Forschungssymposium kamen 35 Wissenschaftler:innen, Studienassistent:innen und weitere interessierte Mitarbeitende aus allgemeinmedizinischen Forschungspraxennetzen und anderen Institutionen zusammen, um sich zu der Frage „Wie gelingt aktive Forschungsbeteiligung von Patient:innen, Bürger:innen, Hausärzt:innen und Medizinischen Fachangestellten an der allgemeinmedizinische Forschung?“ auszutauschen. Hierfür diskutierten die Teilnehmenden in zwei World Cafés zu den Themen (1) Partizipation planen und umsetzen sowie (2) Besonderheiten der Stakeholder. Die erarbeiteten Inhalte wurden jeweils auf Moderationskarten gesammelt und thematisch geclustert. Auf Grundlage dieser Erfahrungssammlung arbeiteten die Teilnehmenden des Symposiums im Nachgang in kleinen Autor:innengruppen die einzelnen Kapitel der Handreichung aus. Im Sinne der Beteiligung wurde die Handreichung vor Finalisierung durch zwei Patient:innen, zwei Hausärzt:innen und zwei Medizinische Fachangestellte geprüft und kommentiert. Ergebnisse: Mit Fokus auf der allgemeinmedizinischen Forschung gibt die Handreichung einen umfassenden Überblick über die Zielsetzungen und Gründe aktiver Forschungsbeteiligung, mögliche Methoden, Aspekte der Planung und Organisation von Beteiligungsaktivitäten sowie Ansätze und Instrumente für deren Evaluation. Darüber hinaus beleuchtet sie Besonderheiten der drei zentralen Stakeholdergruppen Patient:innen/Bürger:innen, Hausärzt:innen und Medizinischen Fachangestellte im Hinblick auf Diversität, geeignete Beteiligungsformate, zielgruppengerechte Ansprache, Erwartungsmanagement sowie passende Anreize für die Beteiligung. Da die Inhalte überwiegend erfahrungsbasiert und dadurch limitierend bezüglich der Übertragbarkeit auf andere Kontexte sind, wir die Handreichung durch eine Sammlung an Verweisen auf weitere hilfreicher Ressourcen wie Handbücher, Glossare und Checklisten ergänzt. Schlussfolgerung: Diese Handreichung zur aktiven Beteiligung von Stakeholdern an allgemeinmedizinischer Forschung spiegelt die Erfahrungen der Autor:innengruppe wider. Sie soll auf diese Weise möglichst anwendungsorientierte und passgenaue Anregungen für den Kontext Allgemeinmedizin geben und noch mehr Kolleg:innen ermutigen, Stakeholder aktiv an Forschung zu beteiligen.

Background: Error management plays a key role in patient safety. It is a systematic approach aimed at identifying and learning from critical incidents by reporting, documenting and analyzing them. Almost nothing is known about the incidents physicians in outpatient care consider to be critical and how they deal with them. We carried out an interview study to explore outpatient physicians’ views on error management, discover what they regard as critical incidents, and find out how error management is put into practice in ambulatory care. Methods: We conducted 72 semi-structured interviews with physicians from ambulatory practices. We asked participants what they considered to be a critical incident, how they reacted following an incident, how they discussed incidents with their coworkers, and whether they used critical incident reporting systems. The interviews were transcribed verbatim and analyzed using qualitative content analysis. Results: Interviewed physicians defined the term “critical incident” differently. Most participants reported that they recorded information on incidents and discussed them in their teams. Several physicians reported taking a ‘pay better attention next time-approach’ to the analysis of incidents. Systematic error management involving incident documentation, analysis, preventive measure development, and follow-up, was the exception. Conclusions: To promote error management, medical training should include teaching on the topic, so that medical professionals can learn about critical incidents and how to deal with them in an open and structured manner. This would help establish the culture of safety that has long been called for internationally.

Background: As the first point of contact for patients with health issues, general practitioners (GPs) are frequently confronted with patients presenting with non-specific symptoms of unclear origin. This can result in delayed, prolonged or false diagnoses. To accelerate and improve the diagnosis of diseases, clinical decision support systems would appear to be an appropriate tool. The objective of the project ‘Smart physician portal for patients with unclear disease’ (SATURN) is to employ a user-centered design process based on the requirements analysis presented in this paper to develop an artificial Intelligence (AI)-based diagnosis support system that specifically addresses the needs of German GPs. Methods: Requirements analysis for a GP-specific diagnosis support system was conducted in an iterative process with five GPs. First, interviews were conducted to analyze current workflows and the use of digital applications in cases of diagnostic uncertainty (as-is situation). Second, we focused on collecting and prioritizing tasks to be performed by an ideal smart physician portal (to-be situation) in a workshop. We then developed a task model with corresponding user requirements. Results: Numerous GP-specific user requirements were identified concerning the tasks and subtasks: performing data entry (open system, enter patient data), reviewing results (receiving and evaluating results), discussing results (with patients and colleagues), scheduling further diagnostic procedures, referring to specialists (select, contact, make appointments), and case closure. Suggested features particularly concerned the process of screening and assessing results: e.g., the system should focus more on atypical patterns of common diseases than on rare diseases only, display probabilities of differential diagnoses, ensure sources and results are transparent, and mark diagnoses that have already been ruled out. Moreover, establishing a means of using the platform to communicate with colleagues and transferring patient data directly from electronic patient records to the system was strongly recommended. Conclusions: Essential user requirements to be considered in the development and design of a diagnosis system for primary care could be derived from the analysis. They form the basis for mockup-development and system engineering.