The rapid digitalization of public health systems demands a framework to ensure the responsible implementation of digital technologies. The Digital Responsibility (DR) framework, proposed by Trier et al. (2023), can serve this purpose but requires further contextualization — an objective pursued in this paper. We apply a content analysis approach to map the DR principles and levels to the Public Health Agency Maturity Model (PHAMM), which is widely used in the German public health service (PHS) to assess digital maturity and derive actions for its advancements. By mapping 354 PHAMM criteria to the DR framework, we identified areas for improvement in both models, contextualized DR for the PHS by identifying 16 subthemes, and extended the DR framework. The extended framework was discussed and evaluated in a focus group with nine experts. This process led to complementing the existing DR levels with an inter- and intracorporate relation and introduces an additional DR principle (Security). Moreover, the study draws crosscutting lessons learned.

Von 2021 bis 2026 profitierte der öffentliche Gesundheitsdienst in Deutschland von Fördermitteln aus dem „Pakt für den Öffentlichen Gesundheitsdienst“ für Digitalisierungsvorhaben. Die digitale Reife der Gesundheitsämter hat sich seither kontinuierlich weiterentwickelt, jedoch bleibt offen, wie dieser Transformationsprozess von Mitarbeitenden in den Gesundheitsämtern eingeordnet wird und welche Faktoren den Erfolg oder Misserfolg digitaler Implementierungen in der Praxis beeinflussen. Vor diesem Hintergrund untersucht diese Studie auf Basis von 16 leitfadengestützten Interviews mit Mitarbeitenden in Gesundheitsämtern, wie digitale Technologien im öffentlichen Gesundheitsdienst eingeführt, wahrgenommen und genutzt werden. Zur systematischen Analyse dient das Consolidated Framework for Implementation Research (CFIR), das technische, organisationale und kontextuelle Einflussfaktoren der Implementierung erfasst. Die Analyse zeigt, dass die Implementierung digitaler Technologien im öffentlichen Gesundheitsdienst von Herausforderungen geprägt ist. Dazu zählen ausgeprägte bürokratische Hürden, Defizite in der IT-Ausstattung, eine fehlende Standardisierung und begrenzte personelle Ressourcen für eine effiziente Umsetzung digitaler Lösungen. Gleichzeitig werden auch zentrale Erfolgsfaktoren sichtbar. Die Corona-Pandemie hat den Digitalisierungsdruck verstärkt und zu einer gesteigerten Akzeptanz digitaler Technologien beigetragen. Besonders die Unterstützung durch Führungskräfte, die aktive Einbindung der Mitarbeitenden sowie eine konsequente Bürgerorientierung erweisen sich als entscheidend für den Implementierungserfolg. Basierend auf der Analyse werden Maßnahmen abgeleitet, wie bestehende Barrieren überwunden und digitale Vorhaben im öffentlichen Sektor nachhaltig umgesetzt werden können. Die Studie leistet einen wichtigen Beitrag zur Kontextualisierung von Implementierungsfaktoren speziell für den ÖGD und bietet zudem übertragbare Impulse für die digitale Transformation öffentlicher Verwaltungen.

BackgroundVirtual reality (VR) technologies in health care, particularly in medical rehabilitation, have demonstrated effectiveness by enabling patient remobilization in virtual environments, offering real-time feedback, enhancing physical function and quality of life, and allowing patients to exercise autonomously. Nevertheless, VR technologies are facing slow adoption in routine rehabilitative practice due to health care professionals’ concerns regarding data security, lack of time, or perceived cost. ObjectiveThis study aimed to explore how previous experience with VR technologies influences health care professionals’ decisions to adopt or reject these technologies in medical rehabilitation. MethodsWe conducted 23 semistructured interviews with health care professionals from different rehabilitative fields in Germany, whom we grouped into VR-experienced “innovators” and nonexperienced “laggards” according to their level of innovativeness. When analyzing the interviews, we applied qualitative content analysis techniques and derived 56 preliminary categories from the transcripts. ResultsWe merged the preliminary categories into 26 adoption and rejection factors, which were grouped under the 4 overarching categories of the diffusion of innovation theory by Rogers. In addition to the pure identification of context-specific influencing factors, we were able to identify differences between these factors concerning the two different adopter groups. VR-experienced innovators exhibited key characteristics such as openness to new technologies, solution-oriented thinking, and opinion leadership, whereas nonexperienced laggards focused on barriers and relied on top-down knowledge transfer. Despite these differences, both groups agreed on the factors that promote the adoption of VR technologies. Our results indicate that addressing the unique needs of both groups is crucial for wider VR acceptance in health care. ConclusionsThis study demonstrates the importance of distinguishing between VR-experienced and nonexperienced health care professionals, providing actionable insights for developing adopter-specific communication strategies to overcome barriers and foster broader diffusion of VR technologies in the health care sector.

Background:Artificial intelligence (AI) applications hold great promise for improving accuracy and efficiency in medical imaging diagnostics. However, despite the expected benefit of AI applications, widespread adoption of the technology is progressing slower than expected due to technological, organizational, and regulatory obstacles, and user-related barriers, with physicians playing a central role in adopting AI applications. Objective:This study aims to provide guidance on enabling physicians to make an informed adoption decision regarding AI applications by identifying and discussing measures to address key barriers from physicians' perspectives. Methods:We used a 2-step qualitative research approach. First, we conducted a structured literature review by screening 865 papers to identify potential enabling measures. Second, we interviewed 14 experts to evaluate the literature-based measures and enriched them. Results:By analyzing the literature and interview transcripts, we revealed 11 measures, categorized into Enabling Adoption Decision Measures (eg, educating physicians, preparing future physicians, and providing transparency) and Supporting Adoption Measures (eg, implementation guidelines and AI marketplaces). These measures aim to inform physicians' decisions and support the adoption process. Conclusions:This study provides a comprehensive overview of measures to enable physicians to make an informed adoption decision on AI applications in medical imaging diagnostics. Thereby, we are the first to give specific recommendations on how to realize the potential of AI applications in medical imaging diagnostics from a user perspective.

Background: Hospital information systems (HISs) aim to support users in their time-critical routines on hospital wards with accurate and timely information. However, if these systems create blockages to workflows, nurses and physicians develop workarounds to provide care to the patients, nonetheless. Workarounds are considered negatively when associated with risks and positively when seen as feedback and a source of innovation. Learning about the antecedents of workarounds allows for the establishment of control mechanisms, under the promise of enhanced patient safety. Objective: This study seeks to explore which antecedents shape nurses' and physicians' workaround behavior in the context of HISs, how they influence behavior and interrelate, and the intentions with which they are carried out. Methods: Using 26 qualitative interviews with nurses, physicians, and health information technicians from Germany and the United States and applying grounded theory analysis techniques, we identify antecedents of HIS-related workarounds and respective relations. Results: From the interview transcripts, we derive 506 open codes which we cluster into 3 direct causes (organizational prerequisites, human factor, and system), and 4 influencing factors (regulations, sector funding, role of software providers, and role of ownership and management). While Influencing Factors constitute higher-level influences, they do not directly impact nurses' and physicians' behavior but rather depict the defaults that lead to conditions for Direct Causes of workarounds. Conclusions: This study provides an understanding of the antecedents of workarounds performed by medical personnel regarding HIS use, structures and categorizes them, and lays the foundation for an understanding of users' deviant behavior. Moreover, by revealing cause-effect relationships between the antecedents, we take on a behavioral perspective and provide a basis for developing effective strategies to prevent the need for workarounds. We contribute to the research stream of workarounds in health care and emphasize that once the reported and derived direct causes and influencing factors of workarounds have been tackled, working conditions, patient safety, and the overall quality of health care may improve under full digital support.

The COVID-19 pandemic revealed the need for Public Health Agencies to mature digitally. To help those agencies with their digitalization endeavor, a public health agency maturity model (PHAMM) has been developed, evaluated, and employed by 366 institutions to determine their digital maturity and to prioritize actions within digitalization projects. This paper discusses the digital maturity of German public health institutions and derives first insights into components spanning the PHAMM dimensions. Public health agencies can use these components to leverage their digital maturity in future digitalization projects. Implications are discussed for how digitalization projects with an enhanced impact can be defined and for future maturity modeling research.

To address increasing pressures experienced in the workplace, the use of wearables as part of workplace health promotion programs is on the rise. Even though the benefits are well-known, participation rates are often low due to privacy-related issues. Therefore, this study illuminates the area of privacy further by investigating the influence of the wearable's additional private use and limited data access on employees' intended use. Based on technology acceptance and Privacy Calculus Theory, this study applied a factorial survey experiment to test several literature-driven hypotheses. While restricting data access to the employee has a positive impact on employees' privacy concerns, perceived benefits, and intended use, the possibility of private use is only of secondary relevance for individuals' privacy perceptions and intention to use. The results provide empirical evidence on how the design of digital workplace health promotion programs can increase conscious participation.

Radiology has always been considered a highly technological field in medicine. Recently, a new area of radiology has emerged with the adoption of Artificial Intelligence (AI)-based health information systems due to advancements in big data, deep learning, and increased computing power. While AI elevates prevention, diagnostics, and therapy to a new level, various obstacles hinder the adoption of AI technologies in radiology. To provide an overview on these obstacles as basis for corresponding solution approaches, we identify and comprehensively outline these obstacles by conducting a structured literature review. We find 17 obstacles, which we group into six categories. Furthermore, our research discusses relevant interrelations of the obstacles, most of which we have found to be related to user attitude. Besides, these complex interrelations we expose the necessity of approaching the obstacles simultaneously.

The COVID 19 crisis has highlighted the key role of the public health service (PHS), with its approximately 375 municipal health offices involved in the pandemic response. Here, in addition to a lack of human resources, the insufficient digital maturity of many public health departments posed a hurdle to effective and scalable infection reporting and contact tracing. In this article, we present the maturity model (MM) for the digitization of health offices, the development of which took place between January 2021 and February 2022 and was funded by the German Federal Ministry of Health. It has been applied since the beginning of 2022 with the aim of strengthening the digitization of the PHS. The MM aims to guide public health departments step by step to increase their digital maturity to be prepared for future challenges. The MM was developed and evaluated based on qualitative interviews with employees of public health departments and other experts in the public health sector as well as in workshops and with a quantitative survey. The MM allows the measurement of digital maturity in eight dimensions, each of which is subdivided into two to five subdimensions. Within the subdimensions a classification is made on five different maturity levels. Currently, in addition to recording the digital maturity of individual health departments, the MM also serves as a management tool for planning digitization projects. The aim is to use the MM as a basis for promoting targeted communication between the health departments to exchange best practices for the different dimensions.

Requests for a coordinated response during the COVID-19 pandemic revealed the limitations of locally-operating public health agencies (PHAs) and have resulted in a growing interest in their digitalization. However, digitalizing PHAs – i.e., transforming them technically and organizationally – toward the needs of both employees and citizens is challenging, especially in federally-managed local government settings. This paper reports on a project that develops and evaluates a continuous (vs. a staged) maturity model, the PHAMM, for digitalizing PHAs as a cornerstone of a digitally resilient public health system in the future. The model supports a coordinated approach to formulating a vision and structuring the steps toward it, engaging employees along the transformation journey necessary for a federally-managed field. Further, it is now being used to allocate substantial national funds to foster digitalization. By developing the model in a coordinated approach and using it for distributing federal resources, this work expands the potential usage cases for maturity models. The authors conclude with lessons learned and discuss how the model can incentivize local digitalization in federal fields.

Abstract As healthcare demands exceed outpatient physicians’ capacities, telemedicine holds far-reaching potential for both physicians and patients. It is crucial to holistically analyze physicians’ acceptance of telemedical applications, such as online consultations. This study seeks to identify supporting and constraining factors that influence outpatient physicians’ acceptance of telemedicine. We develop a model based on the unified theory of acceptance and use of technology (UTAUT). To empirically examine our research model, we conducted a survey among German physicians (n = 127) in 2018–2019. We used the partial least squares (PLS) modeling approach to test our model, including a mediation analysis. The results indicate that performance expectancy (β = .397, P < .001), effort expectancy (β = .134, P = .03), and social influence (β = .337, P < .001) strongly impact the intention to conduct online consultations and explain 55% of its variance. Structural conditions regarding data security comprise a key antecedent, associating with performance expectancy (β = .193, P < .001) and effort expectancy (β = .295, P < .001). Regarding potential barriers to usage intentions, we find that IT anxiety predicts performance (β = –.342, P < .001) and effort expectancy (β = –.364, P < .001), while performance expectancy fully mediates (βdirect = .022, P = .71; βindirect = -.138, P < .001) the direct relationship between IT anxiety and the intention to use telemedical applications. This research provides explanations for physicians’ behavioral intention to use online consultations, underlining UTAUT’s applicability in healthcare contexts. To boost acceptance, social influences, such as personal connections and networking are vital, as colleagues can serve as multipliers to reach convergence on online consultations among peers. To overcome physicians’ IT anxiety, training, demonstrations, knowledge sharing, and management incentives are recommended. Furthermore, regulations and standards to build trust in the compliance of online consultations with data protection guidelines need reinforcement from policymakers and hospital management alike.

Zusammenfassung Die COVID-19-Krise verdeutlichte die Schlüsselrolle des Öffentlichen Gesundheitsdienstes (ÖGD) mit den rund 375 kommunalen Gesundheitsämtern in der Pandemiebekämpfung. Dabei stellte neben fehlenden personellen Ressourcen auch die unzureichende digitale Reife vieler Gesundheitsämter eine Hürde für die effektive und skalierbare Infektionsmeldung und Kontaktnachverfolgung dar. In diesem Artikel stellen wir das Reifegradmodell (RGM) für die Digitalisierung von Gesundheitsämtern vor, dessen Erarbeitung im Zeitraum Januar 2021 bis Februar 2022 stattfand und durch das Bundesministerium für Gesundheit gefördert wurde. Es findet seit Anfang 2022 Anwendung mit dem Ziel der Stärkung der Digitalisierung des ÖGD. Das RGM zielt darauf ab, Gesundheitsämter Schritt für Schritt anzuleiten, ihre digitale Reife zu erhöhen, um so für zukünftige Herausforderungen gerüstet zu sein. Entwickelt und evaluiert wurde das RGM anhand qualitativer Interviews mit Mitarbeitenden der Gesundheitsämter und weiteren Expert*innen des ÖGD sowie in Workshops und im Rahmen einer quantitativen Umfrage. Das RGM erlaubt die Messung der digitalen Reife in 8 Dimensionen, welche jeweils in 2–5 Subdimensionen untergliedert sind. Innerhalb der Subdimensionen erfolgt eine Einstufung auf 5 verschiedenen Reifegradstufen. Derzeit dient das RGM neben der Erfassung der digitalen Reife der einzelnen Gesundheitsämter auch als Management-Tool für die Planung von Digitalisierungsprojekten. Ziel ist es, auf Basis des RGM eine zielgerichtete Kommunikation zwischen den Gesundheitsämtern zu fördern, um Best Practices für die einzelnen Dimensionen auszutauschen.

Hospital Information Systems (HIS) aim to support users in their time-critical routines on hospital wards with accurate and timely information. However, if these systems create blockages to workflows, nurses and physicians develop workarounds to provide care to the patients, nonetheless. Workarounds are both considered negatively, when associated with risks, and positively, when seen as feedback and source of innovation. Learning about the antecedents of workarounds allows for the establishment of control mechanisms, under the promise of enhanced patient safety. This study seeks to explore which antecedents shape nurses’ and physicians’ workaround behavior in the context of HIS, how they influence behavior and interrelate, along with the intentions with which they are carried out. Utilizing 26 qualitative interviews with nurses, physicians, and health information technicians from Germany and the USA and applying grounded theory analysis techniques, we identify antecedents of HIS-related workarounds and respective relations. From the interview transcripts, we derive 506 open codes, which we merge cluster into three Direct Causes (Organizational Prerequisites, Human Factor, System), and four Influencing Factors (Regulations, Sector Funding, Role of Software Providers, Role of Ownership and Management). While Influencing Factors constitute higher-level influences, they do not directly impact nurses' and physicians' behavior but rather depict the defaults that lead to conditions for Direct Causes of workarounds. This study provides an understanding of the antecedents of workarounds performed by medical personnel regarding HIS usage, structures and categorizes them, and lays the foundation for an understanding of users’ deviant behavior. Moreover, by revealing cause-effect relationships between the antecedents, we take on a behavioral perspective and provide a basis for developing effective strategies to prevent the need for workarounds. We contribute to the research stream of workarounds in healthcare and emphasize that once the reported and derived Direct Causes and Influencing Factors of workarounds have been tackled, working conditions, patient safety, and the overall quality of healthcare may improve under full digital support.

Zusammenfassung Kritische Infrastrukturen – wie diejenigen der Sektoren Wasser, Energie und Ernährung – bilden die Grundlage einer funktionierenden, modernen Gesellschaft. Eine Kompromittierung dieser Infrastrukturen kann zu weitreichenden Störungen und Gefahren für Leib und Leben führen. Der Schutz sowie die Sicherstellung des Betriebs kritischer Infrastrukturen sind deshalb von entscheidender Bedeutung. Während in der Vergangenheit hauptsächlich der physische Schutz vor Angriffen im Mittelpunkt stand, entstehen durch die zunehmende Digitalisierung kritischer Infrastrukturen zusätzliche Angriffspunkte und Risiken. Im Gegensatz zu herkömmlichen Ansätzen zur Absicherung kritischer Energieinfrastrukturen kann eine Absicherung mithilfe einer Zero-Trust-Architektur die mit diesen Entwicklungen einhergehenden Anforderungen erfüllen. Aufgrund der verhältnismäßig geringen Verbreitung von Zero-Trust-Architekturen im kritischen Energieinfrastruktursektor existiert bisher allerdings nur unzureichend praxisrelevante Literatur zur Entwicklung und Implementierung einer solchen Architektur. Diese Arbeit stellt daher sowohl die Erfahrungen aus einem laufenden Entwicklungs- und Implementierungsprojekt als auch die hiervon abgeleiteten technischen und organisationalen Handlungsempfehlungen im Rahmen eines Action-Design-Forschungsansatzes vor und trägt dadurch zur Schließung dieser Forschungslücke bei.