Health IT Adoption in German Hospitals: Could We See Any Changes Between 2017 and 2023?

INTRODUCTION: Increase in health IT adoption is often driven by financial support through the state. In 2020, the German Hospital Future Law passed Parliament with a schedule to see potential effects in 2023. The research question of the present study thus was if there were differences between 2017 and 2023 in selected application areas eligible for funding by the law. METHODS: Availability and percentage of use in clinical units was measured in a panel of 172 hospitals for these areas. A linear mixed model with repeated measures yielded a significant increase in "medication management" and "discharge management". RESULTS AND DISCUSSION: In "medication management", hospitals in a group as compared to single hospitals tripled the percentage of clinical units using IT systems for this purpose. Not-for-profit hospitals doubled their IT systems for "discharge management" when compared to for-profit hospitals. CONCLUSION: Whether these changes can be attributed to the Hospital Future Law is debatable due to severe delays in various fields, particularly in making funding available. There is room for speeding up particularly the administrative funding process and finally demonstrating results that are proportional to the government money invested.

Computational surgery in the management of patients with abdominal aortic aneurysms: Opportunities, challenges, and future directions.

Computational surgery (CS) is an interdisciplinary field that uses mathematical models and algorithms to focus specifically on operative planning, simulation, and outcomes analysis to improve surgical care provision. As the digital revolution transforms the surgical work environment through broader adoption of artificial intelligence and machine learning, close collaboration between surgeons and computational scientists is not only unavoidable, but will become essential. In this review, the authors summarize the main advances, as well as ongoing challenges and prospects, that surround the implementation of CS techniques in vascular surgery, with a particular focus on the care of patients affected by abdominal aortic aneurysms (AAAs). Several key areas of AAA care delivery, including patient-specific modelling, virtual surgery simulation, intraoperative imaging-guided surgery, and predictive analytics, as well as biomechanical analysis and machine learning, will be discussed. The overarching goals of these CS applications is to improve the precision and accuracy of AAA repair procedures, while enhancing safety and long-term outcomes. Accordingly, CS has the potential to significantly enhance patient care across the entire surgical journey, from preoperative planning and intraoperative decision making to postoperative surveillance. Moreover, CS-based approaches offer promising opportunities to augment AAA repair quality by enabling precise preoperative simulations, real-time intraoperative navigation, and robust postoperative monitoring. However, integrating these advanced computer-based technologies into medical research and clinical practice presents new challenges. These include addressing technical limitations, ensuring accuracy and reliability, and managing unique ethical considerations associated with their use. Thorough evaluation of these aspects of advanced computation techniques in AAA management is crucial before widespread integration into health care systems can be achieved.

e-Health and environmental sustainability in vascular surgery.

e-Health technology holds great promise for improving the management of patients with vascular diseases and offers a unique opportunity to mitigate the environmental impact of vascular care, which remains an under-investigated field. The innovative potential of e-Health operates in a complex environment with finite resources. As the expansion of digital health will increase demand for devices, contributing to the environmental burden of electronics and energy use, the sustainability of e-Health technology is of crucial importance, especially in the context of increasing prevalence of cardiovascular diseases. This review discusses the environmental impact of care related to vascular surgery and e-Health innovation, the potential of e-Health technology to mitigate greenhouse gas emissions generated by the health care sector, and to provide leads to research promoting e-Heath technology sustainability. A multifaceted approach, including ethical design, validated eco-audits methodology and reporting standards, technological refinement, electronic and medical devices reuse and recycling, and effective policies is required to provide a sustainable and optimal level of care to vascular patients.

Emerging Hybrid Intracoronary Imaging Technologies and Their Applications in Clinical Practice and Research.

Intravascular ultrasound and optical coherence tomography are used with increasing frequency for the care of coronary patients and in research studies. These imaging tools can identify culprit lesions in acute coronary syndromes, assess coronary stenosis severity, guide percutaneous coronary intervention (PCI), and detect vulnerable plaques and patients. However, they have significant limitations that have stimulated the development of multimodality intracoronary imaging catheters, which provide improvements in assessing vessel wall pathology and guiding PCI. Prototypes combining 2 or even 3 imaging probes with complementary attributes have been developed, and several multimodality systems have already been used in patients, with near-infrared spectroscopy intravascular ultrasound-based studies showing promising results for the identification of high-risk plaques. Moreover, postmortem histology studies have documented that hybrid imaging catheters can enable more accurate characterization of plaque morphology than standalone imaging. This review describes the evolution in the field of hybrid intracoronary imaging; presents the available multimodality catheters; and discusses their potential role in PCI guidance, vulnerable plaque detection, and the assessment of endovascular devices and emerging pharmacotherapies targeting atherosclerosis.

Pericardial Diseases: International Position Statement on New Concepts and Advances in Multimodality Cardiac Imaging.

Pericardial diseases have gained renewed clinical interest, leading to a renaissance in the field. There have been many recent advances in pericardial diseases in both multimodality cardiac imaging of diagnoses, such as recurrent, transient constrictive and effusive-constrictive pericarditis, and targeted therapeutics, especially anti-interleukin (IL)-1 agents that affect the inflammasome as part of autoinflammatory pathophysiology. There remains a large educational gap for clinicians, leading to variability in evaluation and management of these patients. The latest pericardial imaging (American Society of Echocardiography, European Association of Cardiovascular Imaging) and clinical guidelines (European Society of Cardiology) are >8-10 years of age and may not reflect current practice. Recent clinical trials involving anti-IL-1 agents in recurrent pericarditis, including anakinra (AIRTRIP), rilonacept (RHAPSODY), and goflikicept have demonstrated their efficacy. The present document represents an international position statement from world leaders in the pericardial field, focusing on novel concepts and emphasizing the role of multimodality cardiac imaging as well as new therapeutics in pericardial diseases.

Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Review.

BACKGROUND: Artificial intelligence (AI) use cases in health care are on the rise, with the potential to improve operational efficiency and care outcomes. However, the translation of AI into practical, everyday use has been limited, as its effectiveness relies on successful implementation and adoption by clinicians, patients, and other health care stakeholders. OBJECTIVE: As adoption is a key factor in the successful proliferation of an innovation, this scoping review aimed at presenting an overview of the barriers to and facilitators of AI adoption in health care. METHODS: A scoping review was conducted using the guidance provided by the Joanna Briggs Institute and the framework proposed by Arksey and O'Malley. MEDLINE, IEEE Xplore, and ScienceDirect databases were searched to identify publications in English that reported on the barriers to or facilitators of AI adoption in health care. This review focused on articles published between January 2011 and December 2023. The review did not have any limitations regarding the health care setting (hospital or community) or the population (patients, clinicians, physicians, or health care administrators). A thematic analysis was conducted on the selected articles to map factors associated with the barriers to and facilitators of AI adoption in health care. RESULTS: A total of 2514 articles were identified in the initial search. After title and abstract reviews, 50 (1.99%) articles were included in the final analysis. These articles were reviewed for the barriers to and facilitators of AI adoption in health care. Most articles were empirical studies, literature reviews, reports, and thought articles. Approximately 18 categories of barriers and facilitators were identified. These were organized sequentially to provide considerations for AI development, implementation, and the overall structure needed to facilitate adoption. CONCLUSIONS: The literature review revealed that trust is a significant catalyst of adoption, and it was found to be impacted by several barriers identified in this review. A governance structure can be a key facilitator, among others, in ensuring all the elements identified as barriers are addressed appropriately. The findings demonstrate that the implementation of AI in health care is still, in many ways, dependent on the establishment of regulatory and legal frameworks. Further research into a combination of governance and implementation frameworks, models, or theories to enhance trust that would specifically enable adoption is needed to provide the necessary guidance to those translating AI research into practice. Future research could also be expanded to include attempts at understanding patients' perspectives on complex, high-risk AI use cases and how the use of AI applications affects clinical practice and patient care, including sociotechnical considerations, as more algorithms are implemented in actual clinical environments.

Shifting from Theoretical Best Evidence to Practical Best Evidence: an Approach to Overcome Structural Conservatism of Evidence-Based Medicine and Health Policy. / Von der theoretisch besten Evidenz zur praktisch besten Evidenz: ein Ansatz zur Überwindung des Strukturkonservatismus in der evidenzbasierten Medizin und Gesundheitspolitik.

There is disparity in the healthcare sector between the extent of innovation in medical products (e. g., drugs) and healthcare structures. The reason is not a lack of ideas, concepts, or (quasi-) experimental studies on structural innovations. Instead, we argue that the slow implementation of structural innovations has created this disparity partly because evidence-based medicine (EBM) instruments are well suited to evaluate product innovations but less suited to evaluate structural innovations. This article argues that the unintentional interplay between EBM, which has changed significantly over time to become primarily theoretical, on the one hand, and caution and inertia in health policy, on the other, has resulted in structural conservatism. Structural conservatism is present when healthcare structures persistently and essentially resist innovation. We interpret this phenomenon as an unintended consequence of deliberate EBM action. Therefore, we propose a new assessment framework to respond to structural innovations in healthcare, centered on the differentiation between the theoretical best (possible) evidence, the practical best (possible) evidence, and the best available evidence.

Artificial Intelligence in Chronic Obstructive Pulmonary Disease: Research Status, Trends, and Future Directions --A Bibliometric Analysis from 2009 to 2023.

Objective: A bibliometric analysis was conducted using VOSviewer and CiteSpace to examine studies published between 2009 and 2023 on the utilization of artificial intelligence (AI) in chronic obstructive pulmonary disease (COPD). Methods: On March 24, 2024, a computer search was conducted on the Web of Science (WOS) core collection dataset published between January 1, 2009, and December 30, 2023, to identify literature related to the application of artificial intelligence in chronic obstructive pulmonary disease (COPD). VOSviewer was utilized for visual analysis of countries, institutions, authors, co-cited authors, and keywords. CiteSpace was employed to analyze the intermediary centrality of institutions, references, keyword outbreaks, and co-cited literature. Relevant descriptive analysis tables were created using Excel2021 software. Results: This study included a total of 646 papers from WOS. The number of papers remained small and stable from 2009 to 2017 but started increasing significantly annually since 2018. The United States had the highest number of publications among countries/regions while Silverman Edwin K and Harvard Medical School were the most prolific authors and institutions respectively. Lynch DA, Kirby M. and Vestbo J. were among the top three most cited authors overall. Scientific Reports had the largest number of publications while Radiology ranked as one of the top ten influential journals. The Genetic Epidemiology of COPD (COPDGene) Study Design was frequently cited. Through keyword clustering analysis, all keywords were categorized into four groups: epidemiological study of COPD; AI-assisted imaging diagnosis; AI-assisted diagnosis; and AI-assisted treatment and prognosis prediction in the COPD research field. Currently, hot research topics include explainable artificial intelligence framework, chest CT imaging, and lung radiomics. Conclusion: At present, AI is predominantly employed in genetic biology, early diagnosis, risk staging, efficacy evaluation, and prediction modeling of COPD. This study's results offer novel insights and directions for future research endeavors related to COPD.

The New Partnership: Technology Adoption, Development, Deployment, and Diffusion.

Children's Hospital of Philadelphia (CHOP) is a preeminent leader in pediatric healthcare delivery, research, and education. CHOP has three inpatient locations, 31 primary care centers, 16 ambulatory centers, and four dedicated research buildings. CHOP's health system provides care for children from around the world and close to home in West Philadelphia and Southern New Jersey. Technology innovation has been a key element to the hospital's success during the last 165 years.

Diffusion of the Shared Citizenship Paradigm: Strategies and Next Steps.

The field of disabilities is being challenged to adopt a paradigm that can be used to guide the transformation of services, supports, and research practices to ensure and enhance the personal autonomy, rights, and community inclusion of people with disabilities. This article describes strategies associated with the systematic diffusion and sustainability of an innovation such as the emerging Shared Citizenship Paradigm (SCP), which has the potential to guide the transformation. The systematic diffusion process incorporates five components: knowledge, persuasion, decision, implementation, and confirmation. The systematic process also addresses the risks of dissonance, backlash, unintended consequences, and backsliding that can emerge when the sustainability of a paradigm is not supported. Throughout the article, we stress that meaningful change in organizations and systems requires use of a paradigm such as the SCP and its principles and foundation pillars to guide the change, and a systematic process such as that described in this article to bring about and sustain the change.

All Hands on Deck. Transforming the Health System Requires Innovation, Through Individual- and Diffusion Efforts Comment on "Employee-Driven Innovation in Health Organizations: Insights From a Scoping Review".

Employee driven innovation (EDI) is essential in transforming hospitals and other providers, but the challenge is also to have impact on health systems as a whole. Usually a mix from top down measures and bottom up initiatives leads to an innovative culture. An important aspect is the innate difference between types of providers related to initiating, facilitating and rewarding innovation. Second the rewarding system within organisations but also in science and scientific journals. Especially nursing and other non-medical professions can be emancipated in this regard. Further there is a growing interdependence with digitalisation in all its forms and awareness of the related team effort is needed to actually realise innovative projects within a standing organisation. Lastly change the paradigm related to the spread of innovations from "not invented here" to "proudly copied from," create trust and organize collaboration between providers and spend sufficient attention to credible evidence on the effectiveness.

Barriers to diffusion and implementation of pediatric minimally invasive surgery in Brazil.

BACKGROUND: The main barriers to the broad implementation of pediatric minimally invasive surgery (MIS) are technological, technical, and epistemological barriers, as well as the rarity of certain pathologies. These issues are presumed to be more significant in low- and middle-income countries. This study aimed to identify and analyze the factors limiting the diffusion and implementation of pediatric MIS in Brazil. METHODS: A nationwide cross-sectional survey was conducted via an online questionnaire in Brazil from January 2022 to July 2022. The sample was taken by convenience from the population of pediatric surgeons in Brazil. A total of 187 surgeons were included. The collected data were divided into three sections to evaluate technological, technical, and epistemological limitations to pediatric MIS implementation. RESULTS: Although 85% of the participants had previous training, a lack of adequate training was identified as a significant limiting factor, particularly among those who had taken only short courses (42.3% vs. 64.3%, p = 0.033). Only 14% of the participants reported performing MIS for major pediatric procedures. With respect to intracorporeal suturing, 38.1% of the surgeons with extensive training considered it a limiting factor compared with 60.7% (p = 0.029) of those without prior training. Among those without previous training, 61% cited a lack of financial support or encouragement from their department as the reason. Additionally, 65% of the surgeons considered the lack of basic instruments a limiting factor. Although 95% of the participants agreed that simulation training is indispensable, pediatric surgery fellowship programs in Brazil do not include a standardized curriculum or mandatory training in MIS, and only 47% reported providing training space for their current fellows. CONCLUSION: A combination of technological, technical, and epistemological barriers hinders the implementation of pediatric MIS. Despite its limitations, this study serves as a foundational guide for future analysis and overcoming the identified barriers.

Montenegrin Digital Academic Innovation Hub: Experience in Supporting Digital Health Innovations.

Montenegrin Digital Academic Innovation Hub established within Erasmus+ project DigNEST is essential institutional support for developing innovations in the field of health in academic-business cooperation and partnership. Experience of 18 months in running Hub service provides preliminary results in analysis received innovation ideas, provided support and potentials/capacities in medical informatics advancements at national, regional and global level.