Deriving Facilitators for Electronic Health Record Implementation: A Systematic Literature Review of Opportunities and Challenges

Electronic Health Records aim to remove information asymmetries between healthcare providers and contribute to improved healthcare quality and safety. Nevertheless, the successful and comprehensive implementation remains challenging and complex. Recently, increased interest of patients in their healthcare and enhanced technological opportunities led to new challenges and an emerging amount of research. To achieve an overarching overview of facilitators for EHR implementation, the perspectives of relevant stakeholders were considered. Therefore, we conducted a multidisciplinary systematic literature review involving five databases from public health, information systems, and interdisciplinary research. As a result, we first identified opportunities and challenges according to the stakeholder groups, environmental context, and implementation stages. Second, we derived five facilitators (individual stakeholder readiness, change management, accessibility and ownership, EHR structure, and external factors). Therefore, we lay a state-of-the-art foundation for EHR implementation for scientific studies and development activities in practice with our research

Navigating within the Digitalization Journey: Results and Implications of the First Maturity Assessment of German Public Health Agencies

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 prior-itize actions within digitalization projects. This paper discusses the digital ma-turity of German public health institutions and derives first insights into compo-nents spanning the PHAMM dimensions. Public health agencies can use these components to leverage their digital maturity in future digitalization projects. Im-plications are discussed for how digitalization projects with an enhanced impact can be defined and for future maturity modeling research

Das Reifegradmodell für den Öffentlichen Gesundheitsdienst:Ein Instrument zur Erfassung und Verbesserung des digitalen Reifegrades von deutschen Gesundheitsämtern

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

Artificial Intelligence in Radiology – A Qualitative Study on Imaging Specialists’ Perspectives

Artificial intelligence (AI) applications are particularly promising in the field of medical imaging. Especially in radiology, research presents various AI uses cases, highlighting AI applications\u27 potential to improve the quality and efficiency of healthcare. Further, despite numerous research projects of AI applications, an investigation from the real-world, practice-based point of view regarding AI applications is lacking. Consequently, little is known about medical imaging specialists’ perspective on AI applications. Following the Grounded Theory Methodology, we conducted 15 semi-structured interviews with medical imaging specialists. We derived four opportunities and five concerns representing medical imaging specialists’ perspective on AI applications