Abstract: The typical structure of the healthcare sector involves (specialist) intertwined practices co-occurring in formal or informal networks. These practices must answer to the concerns and needs of all related stakeholders. Multimorbidity and the need to share knowledge for scientific development are among the driving factors for collaboration in healthcare. To establish and keep up a permanent collaborative link, it takes effort and understanding of the network characteristics that must be governed. It is not hard to find practices of Network Governance (NG) in a variety of industries. Still, there is a lack of insight in this subject, including knowledge on how to establish and maintain an effective healthcare network. Consequently, this study's research question is: How is network governance organized in the healthcare sector? A systematic literature study was performed to select 80 NG articles. Based on these publications the characteristics of NG are made explicit. The findings demonstrate that combinations of governance style (relational versus contractual governance) and governance structure (lead versus shared governance) lead to different network dynamics. Furthermore, the results show that in order to comprehend how networks in the healthcare sector emerge and can be regulated, it is vital to understand the current network type. Additionally, it informs us of the governing factors. Zie https://www.hbo-kennisbank.nl/details/sharekit_han:oai:surfsharekit.nl:e4f8fa3a-4af8-42ef-b2dd-c86d77b4cec6
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Het tweejarige onderzoeksprogramma The Network is the Message richt zich op de effectiviteit van sociale media: wanneer zijn ze effectief, wat bepaalt die effectiviteit en hoe kunnen we dit meten? Startpunt in deze management summary fase 2B is het inzicht dat inhakers belangrijke dragers van brand content zijn, maar dat er ook nog een wereld te winnen is. Dit is nu niet direct een oproep aan alle merken om meteen met inhakers aan de slag te gaan; ‘inhaakmoeheid’ ligt op de loer. In deze management summary wordt beschreven wat goede inhakers zijn, wat een inhaker nou eigenlijk effectief maakt. We beschrijven de vier stappen die een rol spelen bij het ontwikkelen van kwalitatief goede inhakers.
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Abstract Healthcare organizations operate within a network of governments, insurers, inspection services and other healthcare organizations to provide clients with the best possible care. The parties involved must collaborate and are accountable to each other for the care provided. This has led to a diversity of administrative processes that are supported by a multi-system landscape, resulting in administrative burdens among healthcare professionals. Management methods, such as Enterprise Architecture (EA), should help to develop and manage such landscapes, but they are systematic, while the network of healthcare parties is dynamic. The aim of this research is therefore to develop an EA framework that fits the dynamics of network organizations (such as long-term healthcare). This research proposal outlines the practical and scientific relevance of this research and the proposed method. The current status and next steps are also described.
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Objectives Most complex healthcare interventions target a network of healthcare professionals. Social network analysis (SNA) is a powerful technique to study how social relationships within a network are established and evolve. We identified in which phases of complex healthcare intervention research SNA is used and the value of SNA for developing and evaluating complex healthcare interventions. Methods A scoping review was conducted using the Arksey and O’Malley methodological framework. We included complex healthcare intervention studies using SNA to identify the study characteristics,level of complexity of the healthcare interventions, reported strengths and limitations, and reported implications of SNA. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews 2018 was used to guide the reporting. Results Among 2466 identified studies, 40 studies were selected for analysis. At first, the results showed that SNA seems underused in evaluating complex intervention research. Second, SNA was not used in the development phase of the included studies. Third, the reported implications in the evaluation and implementation phase reflect the value of SNA in addressing the implementation and population complexity. Fourth, pathway complexity and contextual complexity of the included interventions were unclear or unable to access. Fifth, the use of a mixed methods approach was reported as a strength, as the combination and integration of a quantitative and qualitative method clearly establishes the results. Conclusion SNA is a widely applicable method that can be used in different phases of complex intervention research. SNA can be of value to disentangle and address the level of complexity of complex healthcare interventions. Furthermore, the routine use of SNA within a mixed method approach could yield actionable insights that would be useful in the transactional context of complex interventions.
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Background: Due to multimorbidity and geriatric problems, older people often require both psychosocial and medical care. Collaboration between medical and social professionals is a prerequisite to deliver high-quality care for community-living older people. Effective, safe, and person-centered care relies on skilled interprofessional collaboration and practice. Little is known about interprofessional education to increase interprofessional collaboration in practice (IPCP) in the context of community care for older people. This study examines the feasibility of the implementation of an IPCP program in three community districts and determines its potential to increase interprofessional collaboration between primary healthcare professionals caring for older people. Method: A feasibility study was conducted to determine the acceptability and feasibility of data collection and analysis regarding interprofessional collaboration in network development. A questionnaire was used to measure the learning experience and the acquisition of knowledge and skills regarding the program. Network development was assessed by distributing a social network survey among professionals attending the program as well as professionals not attending the program at baseline and 5.5 months after. Network development was determined by calculating the number, reciprocity, value, and diversity of contacts between professionals using social network analysis. Results: The IPCP program was found to be instructive and the knowledge and skills gained were applicable in practice. Social network analysis was feasible to conduct and revealed a spill-over effect regarding network development. Program participants, as well as non-program participants, had larger, more reciprocal, and more diverse interprofessional networks than they did before the program. Conclusions: This study showed the feasibility of implementing an IPCP program in terms of acceptability, feasibility of data collection, and social network analysis to measure network development, and indicated potential to increase interprofessional collaboration between primary healthcare professionals. Both program participants and non-program participants developed a larger, more collaborative, and diverse interprofessional network.
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This paper analyzes connectivity and efficiency of a SME network across two industries. These characteristics are likely to be different for networks of various industries. The concept of 'small worlds' is used to judge overall network efficiency. The actual network can be classified as one in which a small world is present. Visualization of the results shows a single core group in the network. It was found that non-profit as well as science actors were overrepresented in the core of the field.
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This study focuses on SME networks of design and high-tech companies in Southeast Netherland. By highlighting the personal networks of members across design and high-tech industries, the study attempts to identify the main brokers in this dynamic environment. In addition, we investigate whether specific characteristics are associated with these brokers. The main contribution of the paper lies in the fact that, in contrast to most other work, it is quantitative and that it focuses on brokers identified in an actual network (based on both suppliers and users of the knowledge infrastructure). Studying the phenomenon of brokerage provides us with clear insights into the concept of brokerage regarding SME networks in different fields. In particular we highlight how third parties contribute to the transfer and development of knowledge. Empirical results show, among others that the most influential brokers are found in the nonprofit and science sector and have a long track record in their branch.
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OBJECTIVE: This work aims to gain insight into the long-term impact of depression course on social network size and perceived loneliness in older people living in the community. METHODS: Within a large representative sample of older people in the community (Longitudinal Aging Study Amsterdam (LASA)), participants with clinically relevant levels of depressive symptoms (scores >16 on the Center for Epidemiological Studies Depression Scale) were followed up over a period of 13 years of the LASA study (five waves). General estimating equations were used to estimate the impact of depression course on network size and loneliness and the interaction with gender and age. RESULTS: An unfavorable course of depression was found to be associated with smaller network sizes and higher levels of loneliness over time, especially in men and older participants. CONCLUSIONS: The findings of this study stress the importance of clinical attention to the negative consequences of chronicity in depressed older people. Clinicians should assess possible erosion of the social network over time and be aware of increased feelings of loneliness in this patient group.
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Background: Adverse outcome pathway (AOP) networks are versatile tools in toxicology and risk assessment that capture and visualize mechanisms driving toxicity originating from various data sources. They share a common structure consisting of a set of molecular initiating events and key events, connected by key event relationships, leading to the actual adverse outcome. AOP networks are to be considered living documents that should be frequently updated by feeding in new data. Such iterative optimization exercises are typically done manually, which not only is a time-consuming effort, but also bears the risk of overlooking critical data. The present study introduces a novel approach for AOP network optimization of a previously published AOP network on chemical-induced cholestasis using artificial intelligence to facilitate automated data collection followed by subsequent quantitative confidence assessment of molecular initiating events, key events, and key event relationships. Methods: Artificial intelligence-assisted data collection was performed by means of the free web platform Sysrev. Confidence levels of the tailored Bradford-Hill criteria were quantified for the purpose of weight-of-evidence assessment of the optimized AOP network. Scores were calculated for biological plausibility, empirical evidence, and essentiality, and were integrated into a total key event relationship confidence value. The optimized AOP network was visualized using Cytoscape with the node size representing the incidence of the key event and the edge size indicating the total confidence in the key event relationship. Results: This resulted in the identification of 38 and 135 unique key events and key event relationships, respectively. Transporter changes was the key event with the highest incidence, and formed the most confident key event relationship with the adverse outcome, cholestasis. Other important key events present in the AOP network include: nuclear receptor changes, intracellular bile acid accumulation, bile acid synthesis changes, oxidative stress, inflammation and apoptosis. Conclusions: This process led to the creation of an extensively informative AOP network focused on chemical-induced cholestasis. This optimized AOP network may serve as a mechanistic compass for the development of a battery of in vitro assays to reliably predict chemical-induced cholestatic injury.
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The network economy typically signifies a notion from the information society where new products and services are developed by collaborating individuals and/or businesses organised in virtual networks. The network economy has important characteristics in common with Northern European governance models, which suggests a direction for developing workable governance models for businesses engaging in network economy activities. This resemblance presents a unique perspective on global economic development. Innovation can and should be combined with high ethical, social and environmental standards. This is illustrated by empirical data on Hidden Champions in Europe: middlesized companies that are dominant in their specific market niches. We suggest that the rise of the network economy could have far-reaching consequences for the way businesses should be organised and managed.
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