To address the first research question, we identified the requirements for curriculum monitoring and change processes within the policy frameworks governing Austrian medical universities. We conducted a qualitative analysis of the most recent, publicly available higher education policy documents. The sample included national legislative frameworks retrieved from the Federal Legal Information System (RIS database), university-specific statutes, as well as quality audit reports and white papers sourced from the universities’ websites. A complete list of the included documents is provided in Table S1 in Multimedia Appendix 1.

The documents were systematically searched using the keywords “monitoring,” “quality,” “curriculum,” and “learning objectives.” Data analysis followed the qualitative content analysis framework proposed by Kuckartz and Rädiker [24]. The national policy and university-specific documents provided a foundational, saturated perspective, which was further triangulated with insights from quality reports and white papers. To ensure interpretive rigor, the analysis was performed by a researcher holding a master’s degree in business law.

For the second research question, the COREQ (Consolidated Criteria for Reporting Qualitative Research) checklist was applied [25].

Inclusion criteria targeted academic and clinical staff from MUW and MUI with significant involvement in the planning and operation of the medical curriculum. Specifically, individuals serving on either the curriculum governing body or the curriculum operations boards were eligible for participation (Figures 1 and 2). Other stakeholders, such as students, policymakers, and administrative staff, were excluded because they typically lacked in-depth knowledge in both areas: digitalization and curricular processes.

A modified snowball sampling approach was used for recruitment. Senior key individuals with long-standing experience in curriculum development and operations were identified and asked to nominate additional potential participants. To ensure a broad range of perspectives, the final sample was balanced across university governing bodies versus boards responsible for curriculum operations (Figures 1 and 2), as well as preclinical versus clinical teaching. Gender was also taken into account to ensure a balanced sample.

A qualitative study was conducted based on semistructured interviews with the following 4 key questions:

The semistructured interview guide was developed based on previous studies by Baumgartner et al [12,26] and Car et al [27] to gain a more in-depth understanding of both formal and informal processes involved in curriculum updating.

Before use, the interview guide was tested with a member of the research team who serves as Vice Dean for Clinical Education in Human Medicine at a university not involved in the study. All interviews were conducted in German using the video conferencing tool Webex (version 45.9.0.33069; Cisco Systems), utilizing its built-in transcription function. Individual video meetings were scheduled between each participant and the researcher. Interviews were planned to last approximately 50 minutes, beginning with the participant’s professional profile followed by the interview questions. Data analysis followed the framework proposed by Kuckartz and Rädiker [24]. As described in the framework, data collection and data analysis are interwoven. Thus, a first draft of inductive categories was developed and refined alongside the interviews.

All interviews were recorded and automatically transcribed. While data saturation was reached after 12 participants, a total of 14 interviews were conducted (7 per university) to satisfy the study’s preapproved sampling protocol.

The researcher who conducted the interviews also reviewed the automatic transcription against the video recordings; spelling errors and unclear words were corrected. The profiles of the interviewees were saved separately, and all data were anonymized. Each interviewee’s name was replaced with “Interviewee” plus a randomly assigned number and the abbreviation of the university (MUW for Medical University of Vienna and MUI for Medical University of Innsbruck). Text passages by the interviewer were marked with “Moderator.” To improve readability, repetitions and filler words (eg, “um” and “hm”) were removed.

For data management and analysis, the transcripts were loaded into the qualitative data analysis software ATLAS.ti for Windows (version 25.0.1; ATLAS.ti Scientific Software Development GmbH). The anonymized transcripts were reread, and the inductive categories were developed (Table S2 in Multimedia Appendix 2). Based on these categories, case summaries [24] were created for 3 randomly selected interviews. A second rater, not involved in the study, independently analyzed the interviews and developed additional case summaries. These summaries were compared, and discrepancies were discussed and resolved before the remaining case summaries were produced. Finally, all case summaries were consolidated and reorganized according to the established categories.

The ethics committee of the MUW deemed this study exempt from requiring a formal decision. Approval was granted by the data security board of the MUW. All participants received a formal invitation letter by email, including detailed information about the study purpose and a declaration of informed consent. Participation was voluntary.

To understand the policy framework of the universities for curriculum monitoring and change processes, the relevant regulations were analyzed. Austrian universities are regulated by the Universities Act (Universitätsgesetz [UG]) [28], the Higher Education Quality Assurance Act (Hochschul-Qualitätssicherungsgesetz) [29], and the Austrian University Development Plan (Gesamtösterreichischer Entwicklungsplan) [30]. Specifically, § 2 para 1 UG references Art 17 of the Basic Law on the General Rights of Citizens, which guarantees the “Freedom of sciences and teaching” [31]. According to the common interpretation, this freedom encompasses both the content to be taught and the manner of teaching. §14 UG [28] defines the need for a university internal quality management system and continuous evaluations, while § 2a (2) Hochschul-Qualitätssicherungsgesetz [29] emphasizes that teaching must comply with the current state of knowledge within each respective discipline. Although these requirements remain relatively broad, they structurally favor siloed curriculum models where educational content is primarily viewed from the perspective of individual subject areas.

Based on these documents, the medical universities developed their institutional frameworks. Overall, the MUW documents primarily focus on ensuring that scientific lecturers align their teaching with current scientific knowledge [32]. However, certain peripheral annotations suggest an awareness of structural challenges. The White Paper on Teaching at the MUW [33] cites an external audit report recommending “Increased coordination of curriculum content and learning objectives.” The MUI emphasizes within their documents “Curricula are continuously updated and adapted to current development” [34,35]. They acknowledge “Intensity and speed of knowledge acquisition will continue to increase” and that “Innovation will be much more strongly orientated towards the boundaries between the established disciplines than before” [36].

Consequently, the institutional documents reveal distinct strategic orientations between the institutions. The MUI states its commitment to a proactive approach by regularly monitoring curricular content to adapt to rapidly changing knowledge and to strengthen intracurricular alignment [35]. The MUW follows a more reactive approach that relies on students and lecturer evaluations while focusing on the knowledge development within specific medical specialties [37].

Overall, the policy framework provides relatively loose guidelines for the universities. While it mandates a quality management system, it specifies neither the relevant topics and key performance indicators nor the concrete curricular renewal processes. Crucially, this lack of a rigid top-down prescription presents a distinct opportunity for universities, granting them the institutional autonomy required to develop their frameworks toward an agile curriculum change process. However, despite this flexibility, the institutional frameworks of universities remain predominantly focused on specialty-specific improvements, treating general curricular adaptability merely as a secondary consideration. These policy findings serve as background information for the development of the interview guide.

The interviews were conducted between March and July 2025 and lasted an average of 53:45 (SD 14:37) minutes. The participants included 7 participants from the MUW and 7 participants from the MUI. Seven participants identified as female and 7 as male. Twelve participants held a habilitation (the postdoctoral lecture qualification “venia legendi”), and 2 were medical residents. The participants were also balanced according to the following characteristics: university governing body versus boards for curriculum operations and preclinical teaching versus clinical teaching. To ensure anonymity, the profiles were not described in more detail. The key themes were identified and summarized as follows: society’s evolving needs for the health care system, impact on the doctor-patient relationship, curriculum governance and adaptation process, dynamics and challenges of curriculum adaptation, and current usage of learning objectives.

Digitalization in medicine is a relatively new field that has not emerged from traditional fields of medicine but rather from society’s need to streamline processes in the health care system and optimize health care spending. Furthermore, it does not affect only one medical specialty but is a cross-cutting technology. The implementation of such cross-cutting and fast-evolving content challenges existing decision-making and implementation processes in medical universities. Structures originally designed to accommodate the gradual growth of specialty-specific knowledge are increasingly overwhelmed by the influx of new, externally driven developments [41].

This study uses digitalization in medicine as an example to examine how efficiently existing processes for curriculum change and renewal can cope with the current pace of change in technology, information and data dissemination, and health care. To determine the current status, the results of a qualitative study with faculty members at 2 Austrian medical universities were compared with the curriculum development frameworks of Kern [5] and Harden [6]. Both frameworks stress the importance of clearly defined educational goals, learning objectives, and learning outcomes to hold medical educators accountable and to provide inputs for reforming and managing medical education [5,23]. Both also stress the importance of monitoring: monitoring the existing curriculum, as well as monitoring the continuous development of medical science, technology, and society’s needs. Kern [5] uses learning objectives to assess whether students achieve the expected outcomes, whereas Harden [7] organizes learning outcomes into curriculum maps to identify overlaps and gaps.

Study participants acknowledged the significant impact of digitalization on the medical profession. In addition to new tools that will change the way doctors do their work, digitalization is expected to transform health care delivery and the doctor-patient relationship. However, participants also agreed that these changes are not yet systematically reflected in the current curriculum.

The universities examined mainly rely on processes tailored to gradual, discipline-specific curriculum development. MUW’s bottom-up approach encourages incremental improvements and aligns well with past periods of slow curricular change. Hamsal [42] described this organizational behavior as the Icarus Paradox. In addition, MUW places a high value on teaching autonomy. This emphasis on academic freedom inadvertently reinforces resistance to reform, directly enabling the phenomenon of “curriculum hoarding” described by Romanelli [43] (see also Bearman et al [44]). In contrast, MUI applies a combined top-down and bottom-up approach, allowing for somewhat more flexible responses to external developments. Nevertheless, both universities depend primarily on external triggers for curricular change rather than on systematic internal review mechanisms.

Existing curriculum monitoring is established with a focus on student satisfaction and their learning experiences. While such evaluations fulfill formal requirements [28], they do not provide sufficient data to improve the organization of curricular content or the overall curriculum structure. Participants reported that learning objectives are mandatory for the approval of new modules; however, no procedures exist to monitor them thereafter. Although both universities originally developed integrated curricula and adopted learning objectives as a guiding principle, the lack of structured monitoring has led to growing gaps and overlaps over time. In slowly evolving environments, such shifts may pose limited issues. However, in fields characterized by rapid innovation, these inconsistencies can lead to curriculum fragmentation, as described by Harden [22], and to integrated modules without an integrated curriculum.

Although some module coordinators actively use learning objectives within their responsibilities, participants agreed that the absence of formal intermodule coordination contributes to divergence between modules. Without consistently monitoring learning objectives and learning outcomes, the university relies solely on student assessments to verify whether overarching educational goals are achieved. Consequently, curriculum mapping [7], which would make learning objectives and their interdependencies visible across the curriculum, is not implemented at the universities examined. Instead of a structured, evidence-informed discussion guided by shared priorities, the integration of new cross-cutting technologies, such as digitalization, becomes an exhausting negotiation for space in a packed curriculum.

In his work “The Integration Ladder,” Harden [22] discusses the importance of making interdependencies between modules visible and understandable. Visualizing these interdependencies helps to maintain curricular coherence and ensures that content is aligned with the overall educational goals. It also clarifies which modules need to be informed or adapted when changes are introduced elsewhere in the curriculum. Existing models illustrate potential approaches: for example, Theurich et al [45] compared the learning objectives of their curriculum against a national catalog to validate curricular relevance. Naylor and Torres [46] used student surveys to assess the implementation of learning objectives in 2 courses. In contrast, participants from both universities reported intensive intramodule coordination but no formal process for inter-module coordination. Participants are even reluctant to approach colleagues, as this could be perceived as intrusive.

This study shows that curriculum processes suitable for slow-evolving, specialty-specific development are not able to keep pace with today’s changes in technology, information and data dissemination, and health care delivery [47]. This mismatch generates a widening gap between current medical training and the competencies required by future health care systems. To reduce this gap, medical universities need to transform their curriculum governance and operational organization [48-51]. This transformation needs to address the tension between academic freedom and coordinated curriculum development [52]. While lecturers should maintain autonomy over teaching methods and disciplinary depth, aligning their content with overarching program competencies must become a centralized function. Therefore, the study indicates that modern curriculum governance must balance decentralized expertise with centralized coordination mechanisms capable of maintaining curricular coherence.

To operationalize this balance, the Kern needs-based curriculum development concept and the Harden systematic curriculum monitoring and integration concept provide a solid theoretical foundation. Building on these models, institutions can draw on established change management frameworks tailored to medical education. For instance, Gale and Grant (AMEE Medical Education Guide Number 10) [53] provide structured guidelines for organizational change in a medical context, while Odiaga et al [51] demonstrate how the Kotter change model can successfully drive the required cultural transformation. Implementing these frameworks requires raising curriculum planning quality by providing faculty development on learning objectives, curriculum integration, and curriculum monitoring and mapping. As a result, the curriculum development process will move from reactive, module-centered change toward proactive, program-level governance.

Regulatory bodies can further support this transition by requiring continuous, forward-looking monitoring of learning objectives and educational goals to meet the needs of society, patients, medical students, and health care providers in the 21st century.

This study evaluates existing curriculum processes by mapping them onto the frameworks of Kern and Harden. Since the analysis is grounded in these specific frameworks, the application of alternative frameworks might reveal different perspectives on the identified challenges. Although the results represent a snapshot of curriculum processes at only 2 of the 4 Austrian public medical universities, the findings may not be fully transferable to medical universities operating under different legal, cultural, or accreditation frameworks.

Participant recruitment followed a snowball sampling approach, where senior key individuals nominated additional participants. This strategy may have introduced selection bias. Furthermore, as attitudes toward new technologies often vary with age, a potential age-related bias among participants cannot be excluded.

Because this study required in-depth knowledge of curriculum change processes, other stakeholders, such as students, policymakers, and administrative staff, were excluded. While these groups were omitted due to the study’s specific focus, customized research targeting these cohorts could provide a valuable external perspective on curriculum change processes.

Finally, this study did not include an analysis of existing documented curriculum processes, teaching materials, or learning outcomes. Consequently, no conclusions can be drawn regarding the actual impact of the observed curricular structures and processes on student learning.

In this study, digitalization in medicine serves as an example of how existing curriculum processes are challenged by emerging topics. The challenge lies not primarily in the rapid addition of new content but in the development of agile, integrated processes that support strategically coordinated curriculum design and enable timely, future-oriented adaptation. Curriculum management driven predominantly by operational considerations risks adding new content without systematically removing less relevant material. Integrating established curriculum development frameworks into curriculum management processes can support prioritization and help maintain curricula that are both agile and future-oriented. As students already provide feedback via web-based evaluation, one simple step forward is to include the successful achievement of individual learning objectives within this evaluation. This approach would provide immediate feedback to lecturer and curriculum coordinators.

Learning objectives, in particular, provide a powerful tool for tracking curriculum content, coordinating modules, and embedding cross-cutting topics such as digitalization throughout the curriculum. In addition, strengthening mechanisms for cross-module coordination and systematic curriculum monitoring is crucial. Through such approaches, medical education can ensure that graduates are not only familiar with digital tools but also resilient, critical, and adaptable to continuous change. While governmental initiatives strongly support the development of digital skills in general, more comprehensive and legally binding guidelines for agile curriculum processes could further facilitate the integration of rapidly evolving knowledge into medical education.

Even though the study was conducted in Austria and the specific governance structures may differ across countries, the underlying challenge of integrating fast-moving knowledge into traditionally slow-changing curricula appears universal. In highly regulated systems, curriculum adaptation may be constrained by accreditation standards or national competency frameworks. In less regulated or resource-constrained systems, challenges may include limited digital infrastructure, faculty expertise, or institutional capacity. Here, structured learning objectives provide relatively low-cost mechanisms for alignment, prioritization, and continuous adaptation.

This study contributes to the growing body of knowledge on curriculum development and renewal and highlights areas for future research. Further studies should include qualitative interviews with curriculum planners to explore challenges in implementing curriculum renewal in greater depth. This research aims to provide curriculum planners with a practical toolbox for the efficient and effective management of curriculum processes, enabling even resource-limited medical degree programs to adopt a future-oriented approach. Ultimately, this field of research is essential for a holistic understanding of medical curricula and for strengthening the shared sense of responsibility among medical educators.