[Identification of regional hospice and palliative care networks in Germany - Results of a multi-method survey]. / Identifikation regionaler Hospiz- und Palliativnetzwerke in Deutschland ­ Ergebnisse einer multimethodischen Bestandserhebung.

INTRODUCTION: In the course of the implementation of the German Healthcare Development Act [Gesundheitsversorgungsweiterentwicklungsgesetz] of 2021, a funding structure according to sect. 39d of the Social Code Book V [SGB V] was established to promote regional hospice and palliative care networks (RHPN). The funded networks are expected to support the multiprofessional cooperation of hospice and palliative care providers at the structural level. It is still unclear how many existing and newly established network structures are eligible for funding according to sect. 39d SGB V and where these network structures are located regionally. The proportion of actually funded networks is also unknown. METHODS: Between January and March 2023, network structures of hospice and palliative care were identified in a tripartite, multi-method survey procedure, consisting of a) research of databases, literature, and internet; b) open quantitative online-survey via SoSciSurvey software, and c) telephone survey of federal offices of health insurers. The data were first documented separately. Then, the research and survey data were combined and analysed via descriptive statistics using SPSS. RESULTS: Based on the aggregated data from the literature-, database- and internet research and the online survey, n=308 network structures of hospice and palliative care could be identified, of which n=37 have applied for network funding according to sect. 39d SGB V. In the survey period, n=47 applications for network funding according to sect. 39d SGB V were submitted to the health insurance funds. There is a high density of network structures in the northern, southern and western federal states, while there are only a few networks in the eastern states. According to the online-survey, 56% (n=136) of all the identified network structures with known sponsorship are organised by providers of specialised outpatient palliative care. 47% (n=29) of the networks with funding interest are organised as independent structures. Of the network structures with known funding status, 18% (n=26) plan to apply for funding according to sect. 39d SGB V in 2024 for the first time. DISCUSSION: There are numerous network structures in hospice and palliative care, but they are differently distributed among the German federal states. The multi-method survey was able to provide a first nation-wide inventory of network structures as well as an assessment of networks with funding interest according to sect. 39 SGB V. A clear distinction between general network structures and structural networks according to sect. 39d SGB V is a challenge. In the next years the number of funding applications is expected to rise. CONCLUSION: The identification of existing and funded network structures of hospice and palliative care in Germany can be a starting point for a deeper analysis of the structure and the activities of the networks. A quality assessment tool that takes into account both the heterogeneity of the networks and the different dimensions of networking would be helpful.

Examining supporting and constraining factors of physicians' acceptance of telemedical online consultations: a survey study.

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 (ß = .397, P < .001), effort expectancy (ß = .134, P = .03), and social influence (ß = .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 (ß = .193, P < .001) and effort expectancy (ß = .295, P < .001). Regarding potential barriers to usage intentions, we find that IT anxiety predicts performance (ß = -.342, P < .001) and effort expectancy (ß = -.364, P < .001), while performance expectancy fully mediates (ßdirect = .022, P = .71; ßindirect = -.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.

General Practitioners' Attitudes Toward Artificial Intelligence-Enabled Systems: Interview Study.

BACKGROUND: General practitioners (GPs) care for a large number of patients with various diseases in very short timeframes under high uncertainty. Thus, systems enabled by artificial intelligence (AI) are promising and time-saving solutions that may increase the quality of care. OBJECTIVE: This study aims to understand GPs' attitudes toward AI-enabled systems in medical diagnosis. METHODS: We interviewed 18 GPs from Germany between March 2020 and May 2020 to identify determinants of GPs' attitudes toward AI-based systems in diagnosis. By analyzing the interview transcripts, we identified 307 open codes, which we then further structured to derive relevant attitude determinants. RESULTS: We merged the open codes into 21 concepts and finally into five categories: concerns, expectations, environmental influences, individual characteristics, and minimum requirements of AI-enabled systems. Concerns included all doubts and fears of the participants regarding AI-enabled systems. Expectations reflected GPs' thoughts and beliefs about expected benefits and limitations of AI-enabled systems in terms of GP care. Environmental influences included influences resulting from an evolving working environment, key stakeholders' perspectives and opinions, the available information technology hardware and software resources, and the media environment. Individual characteristics were determinants that describe a physician as a person, including character traits, demographic characteristics, and knowledge. In addition, the interviews also revealed the minimum requirements of AI-enabled systems, which were preconditions that must be met for GPs to contemplate using AI-enabled systems. Moreover, we identified relationships among these categories, which we conflate in our proposed model. CONCLUSIONS: This study provides a thorough understanding of the perspective of future users of AI-enabled systems in primary care and lays the foundation for successful market penetration. We contribute to the research stream of analyzing and designing AI-enabled systems and the literature on attitudes toward technology and practice by fostering the understanding of GPs and their attitudes toward such systems. Our findings provide relevant information to technology developers, policymakers, and stakeholder institutions of GP care.